Evaluation of computer-aided detection and diagnosis systems.
Petrick, Nicholas; Sahiner, Berkman; Armato, Samuel G; Bert, Alberto; Correale, Loredana; Delsanto, Silvia; Freedman, Matthew T; Fryd, David; Gur, David; Hadjiiski, Lubomir; Huo, Zhimin; Jiang, Yulei; Morra, Lia; Paquerault, Sophie; Raykar, Vikas; Samuelson, Frank; Summers, Ronald M; Tourassi, Georgia; Yoshida, Hiroyuki; Zheng, Bin; Zhou, Chuan; Chan, Heang-Ping
2013-08-01
Computer-aided detection and diagnosis (CAD) systems are increasingly being used as an aid by clinicians for detection and interpretation of diseases. Computer-aided detection systems mark regions of an image that may reveal specific abnormalities and are used to alert clinicians to these regions during image interpretation. Computer-aided diagnosis systems provide an assessment of a disease using image-based information alone or in combination with other relevant diagnostic data and are used by clinicians as a decision support in developing their diagnoses. While CAD systems are commercially available, standardized approaches for evaluating and reporting their performance have not yet been fully formalized in the literature or in a standardization effort. This deficiency has led to difficulty in the comparison of CAD devices and in understanding how the reported performance might translate into clinical practice. To address these important issues, the American Association of Physicists in Medicine (AAPM) formed the Computer Aided Detection in Diagnostic Imaging Subcommittee (CADSC), in part, to develop recommendations on approaches for assessing CAD system performance. The purpose of this paper is to convey the opinions of the AAPM CADSC members and to stimulate the development of consensus approaches and "best practices" for evaluating CAD systems. Both the assessment of a standalone CAD system and the evaluation of the impact of CAD on end-users are discussed. It is hoped that awareness of these important evaluation elements and the CADSC recommendations will lead to further development of structured guidelines for CAD performance assessment. Proper assessment of CAD system performance is expected to increase the understanding of a CAD system's effectiveness and limitations, which is expected to stimulate further research and development efforts on CAD technologies, reduce problems due to improper use, and eventually improve the utility and efficacy of CAD in clinical practice.
Evaluation of computer-aided detection and diagnosis systemsa)
Petrick, Nicholas; Sahiner, Berkman; Armato, Samuel G.; Bert, Alberto; Correale, Loredana; Delsanto, Silvia; Freedman, Matthew T.; Fryd, David; Gur, David; Hadjiiski, Lubomir; Huo, Zhimin; Jiang, Yulei; Morra, Lia; Paquerault, Sophie; Raykar, Vikas; Samuelson, Frank; Summers, Ronald M.; Tourassi, Georgia; Yoshida, Hiroyuki; Zheng, Bin; Zhou, Chuan; Chan, Heang-Ping
2013-01-01
Computer-aided detection and diagnosis (CAD) systems are increasingly being used as an aid by clinicians for detection and interpretation of diseases. Computer-aided detection systems mark regions of an image that may reveal specific abnormalities and are used to alert clinicians to these regions during image interpretation. Computer-aided diagnosis systems provide an assessment of a disease using image-based information alone or in combination with other relevant diagnostic data and are used by clinicians as a decision support in developing their diagnoses. While CAD systems are commercially available, standardized approaches for evaluating and reporting their performance have not yet been fully formalized in the literature or in a standardization effort. This deficiency has led to difficulty in the comparison of CAD devices and in understanding how the reported performance might translate into clinical practice. To address these important issues, the American Association of Physicists in Medicine (AAPM) formed the Computer Aided Detection in Diagnostic Imaging Subcommittee (CADSC), in part, to develop recommendations on approaches for assessing CAD system performance. The purpose of this paper is to convey the opinions of the AAPM CADSC members and to stimulate the development of consensus approaches and “best practices” for evaluating CAD systems. Both the assessment of a standalone CAD system and the evaluation of the impact of CAD on end-users are discussed. It is hoped that awareness of these important evaluation elements and the CADSC recommendations will lead to further development of structured guidelines for CAD performance assessment. Proper assessment of CAD system performance is expected to increase the understanding of a CAD system's effectiveness and limitations, which is expected to stimulate further research and development efforts on CAD technologies, reduce problems due to improper use, and eventually improve the utility and efficacy of CAD in clinical practice. PMID:23927365
Analog Computer-Aided Detection (CAD) information can be more effective than binary marks.
Cunningham, Corbin A; Drew, Trafton; Wolfe, Jeremy M
2017-02-01
In socially important visual search tasks, such as baggage screening and diagnostic radiology, experts miss more targets than is desirable. Computer-aided detection (CAD) programs have been developed specifically to improve performance in these professional search tasks. For example, in breast cancer screening, many CAD systems are capable of detecting approximately 90% of breast cancer, with approximately 0.5 false-positive detections per image. Nevertheless, benefits of CAD in clinical settings tend to be small (Birdwell, 2009) or even absent (Meziane et al., 2011; Philpotts, 2009). The marks made by a CAD system can be "binary," giving the same signal to any location where the signal is above some threshold. Alternatively, a CAD system presents an analog signal that reflects strength of the signal at a location. In the experiments reported, we compare analog and binary CAD presentations using nonexpert observers and artificial stimuli defined by two noisy signals: a visible color signal and an "invisible" signal that informed our simulated CAD system. We found that analog CAD generally yielded better overall performance than binary CAD. The analog benefit is similar at high and low target prevalence. Our data suggest that the form of the CAD signal can directly influence performance. Analog CAD may allow the computer to be more helpful to the searcher.
Computer-aided detection (CAD) of breast cancer on full field digital and screening film mammograms
NASA Astrophysics Data System (ADS)
Sun, Xuejun; Qian, Wei; Song, Xiaoshan; Qian, Yuyan; Song, Dansheng; Clark, Robert A.
2003-05-01
Full-field digital mammography (FFDM) as a new breast imaging modality has potential to detect more breast cancers or to detect them at smaller sizes and earlier stages compared with screening film mammography (SFM). However, its performance needs verification, and it would pose new problems for the development of CAD methods for breast cancer detection and diagnosis. Performance evaluation of CAD systems on FFDM and SFM has been conducted in this study, respectively. First, an adaptive CAD system employing a series of advanced modules has been developed on FFDM. Second, a standardization approach has been developed to make the CAD system independent of characteristics of digitizer or imaging modalities for mammography. CAD systems developed previously for SFM and developed in this study for FFDM have been evaluated on FFDM and SFM images without and with standardization, respectively, to examine the performance improvement of the CAD system developed in this study. Computerized free-response receiver operating characteristic (FROC) analysis has been adopted as performance evaluation method. Compared with previous one, the CAD system developed in this study demonstrated significantly performance improvements. However, the comparison results have shown that the performances of final CAD system in this study are not significantly different on FFDM and on SFM after standardization. It needs further study on the assessment of CAD system performance on FFDM and SFM modalities.
Analog Computer-Aided Detection (CAD) information can be more effective than binary marks
Cunningham, Corbin A.; Drew, Trafton; Wolfe, Jeremy M.
2017-01-01
In socially important visual search tasks such as baggage screening and diagnostic radiology, experts miss more targets than is desirable. Computer Aided Detection (CAD) programs have been developed specifically to help improve performance in these professional search tasks. For example, in breast cancer screening, many CAD systems are capable of detecting approximately 90% of breast cancer, with approximately 0.5 false positive detections per image. Nevertheless, benefits of CAD in clinical settings tend to be small (Birdwell, 2009) or even absent (Meziane et al., 2011; Philpotts, 2009). The marks made by a CAD system can be “Binary”, giving the same signal to any location where the signal is above some threshold. Alternatively, a CAD system present an Analog signal that reflected strength of the signal at a location. In the experiments reported here, we compare analog and binary CAD presentations using non-expert observers and artificial stimuli defined by two noisy signals: a visible color signal and an "invisible" signal that informed our simulated CAD system. We found that analog CAD generally yielded better overall performance than binary CAD. The analog benefit is similar at high and low target prevalence. Our data suggest that the form of the CAD signal can directly influence performance. Analog CAD may allow the computer to be more helpful to the searcher. PMID:27928658
Al-Masni, Mohammed A; Al-Antari, Mugahed A; Park, Jeong-Min; Gi, Geon; Kim, Tae-Yeon; Rivera, Patricio; Valarezo, Edwin; Choi, Mun-Taek; Han, Seung-Moo; Kim, Tae-Seong
2018-04-01
Automatic detection and classification of the masses in mammograms are still a big challenge and play a crucial role to assist radiologists for accurate diagnosis. In this paper, we propose a novel Computer-Aided Diagnosis (CAD) system based on one of the regional deep learning techniques, a ROI-based Convolutional Neural Network (CNN) which is called You Only Look Once (YOLO). Although most previous studies only deal with classification of masses, our proposed YOLO-based CAD system can handle detection and classification simultaneously in one framework. The proposed CAD system contains four main stages: preprocessing of mammograms, feature extraction utilizing deep convolutional networks, mass detection with confidence, and finally mass classification using Fully Connected Neural Networks (FC-NNs). In this study, we utilized original 600 mammograms from Digital Database for Screening Mammography (DDSM) and their augmented mammograms of 2,400 with the information of the masses and their types in training and testing our CAD. The trained YOLO-based CAD system detects the masses and then classifies their types into benign or malignant. Our results with five-fold cross validation tests show that the proposed CAD system detects the mass location with an overall accuracy of 99.7%. The system also distinguishes between benign and malignant lesions with an overall accuracy of 97%. Our proposed system even works on some challenging breast cancer cases where the masses exist over the pectoral muscles or dense regions. Copyright © 2018 Elsevier B.V. All rights reserved.
Foundation and methodologies in computer-aided diagnosis systems for breast cancer detection.
Jalalian, Afsaneh; Mashohor, Syamsiah; Mahmud, Rozi; Karasfi, Babak; Saripan, M Iqbal B; Ramli, Abdul Rahman B
2017-01-01
Breast cancer is the most prevalent cancer that affects women all over the world. Early detection and treatment of breast cancer could decline the mortality rate. Some issues such as technical reasons, which related to imaging quality and human error, increase misdiagnosis of breast cancer by radiologists. Computer-aided detection systems (CADs) are developed to overcome these restrictions and have been studied in many imaging modalities for breast cancer detection in recent years. The CAD systems improve radiologists' performance in finding and discriminating between the normal and abnormal tissues. These procedures are performed only as a double reader but the absolute decisions are still made by the radiologist. In this study, the recent CAD systems for breast cancer detection on different modalities such as mammography, ultrasound, MRI, and biopsy histopathological images are introduced. The foundation of CAD systems generally consist of four stages: Pre-processing, Segmentation, Feature extraction, and Classification. The approaches which applied to design different stages of CAD system are summarised. Advantages and disadvantages of different segmentation, feature extraction and classification techniques are listed. In addition, the impact of imbalanced datasets in classification outcomes and appropriate methods to solve these issues are discussed. As well as, performance evaluation metrics for various stages of breast cancer detection CAD systems are reviewed.
A computer-aided detection (CAD) system with a 3D algorithm for small acute intracranial hemorrhage
NASA Astrophysics Data System (ADS)
Wang, Ximing; Fernandez, James; Deshpande, Ruchi; Lee, Joon K.; Chan, Tao; Liu, Brent
2012-02-01
Acute Intracranial hemorrhage (AIH) requires urgent diagnosis in the emergency setting to mitigate eventual sequelae. However, experienced radiologists may not always be available to make a timely diagnosis. This is especially true for small AIH, defined as lesion smaller than 10 mm in size. A computer-aided detection (CAD) system for the detection of small AIH would facilitate timely diagnosis. A previously developed 2D algorithm shows high false positive rates in the evaluation based on LAC/USC cases, due to the limitation of setting up correct coordinate system for the knowledge-based classification system. To achieve a higher sensitivity and specificity, a new 3D algorithm is developed. The algorithm utilizes a top-hat transformation and dynamic threshold map to detect small AIH lesions. Several key structures of brain are detected and are used to set up a 3D anatomical coordinate system. A rule-based classification of the lesion detected is applied based on the anatomical coordinate system. For convenient evaluation in clinical environment, the CAD module is integrated with a stand-alone system. The CAD is evaluated by small AIH cases and matched normal collected in LAC/USC. The result of 3D CAD and the previous 2D CAD has been compared.
Foundation and methodologies in computer-aided diagnosis systems for breast cancer detection
Jalalian, Afsaneh; Mashohor, Syamsiah; Mahmud, Rozi; Karasfi, Babak; Saripan, M. Iqbal B.; Ramli, Abdul Rahman B.
2017-01-01
Breast cancer is the most prevalent cancer that affects women all over the world. Early detection and treatment of breast cancer could decline the mortality rate. Some issues such as technical reasons, which related to imaging quality and human error, increase misdiagnosis of breast cancer by radiologists. Computer-aided detection systems (CADs) are developed to overcome these restrictions and have been studied in many imaging modalities for breast cancer detection in recent years. The CAD systems improve radiologists' performance in finding and discriminating between the normal and abnormal tissues. These procedures are performed only as a double reader but the absolute decisions are still made by the radiologist. In this study, the recent CAD systems for breast cancer detection on different modalities such as mammography, ultrasound, MRI, and biopsy histopathological images are introduced. The foundation of CAD systems generally consist of four stages: Pre-processing, Segmentation, Feature extraction, and Classification. The approaches which applied to design different stages of CAD system are summarised. Advantages and disadvantages of different segmentation, feature extraction and classification techniques are listed. In addition, the impact of imbalanced datasets in classification outcomes and appropriate methods to solve these issues are discussed. As well as, performance evaluation metrics for various stages of breast cancer detection CAD systems are reviewed. PMID:28435432
Computed-aided diagnosis (CAD) in the detection of breast cancer.
Dromain, C; Boyer, B; Ferré, R; Canale, S; Delaloge, S; Balleyguier, C
2013-03-01
Computer-aided detection (CAD) systems have been developed for interpretation to improve mammographic detection of breast cancer at screening by reducing the number of false-negative interpretation that can be caused by subtle findings, radiologist distraction and complex architecture. They use a digitized mammographic image that can be obtained from both screen-film mammography and full field digital mammography. Its performance in breast cancer detection is dependent on the performance of the CAD itself, the population to which it is applied and the radiologists who use it. There is a clear benefit to the use of CAD in less experienced radiologist and in detecting breast carcinomas presenting as microcalcifications. This review gives a detailed description CAD systems used in mammography and their performance in assistance of reading in screening mammography and as an alternative to double reading. Other CAD systems developed for MRI and ultrasound are also presented and discussed. Copyright © 2012. Published by Elsevier Ireland Ltd.
NASA Astrophysics Data System (ADS)
Liu, Jiamin; Wang, Shijun; Kabadi, Suraj; Summers, Ronald M.
2009-02-01
CT colonography (CTC) is a feasible and minimally invasive method for the detection of colorectal polyps and cancer screening. Computer-aided detection (CAD) of polyps has improved consistency and sensitivity of virtual colonoscopy interpretation and reduced interpretation burden. A CAD system typically consists of four stages: (1) image preprocessing including colon segmentation; (2) initial detection generation; (3) feature selection; and (4) detection classification. In our experience, three existing problems limit the performance of our current CAD system. First, highdensity orally administered contrast agents in fecal-tagging CTC have scatter effects on neighboring tissues. The scattering manifests itself as an artificial elevation in the observed CT attenuation values of the neighboring tissues. This pseudo-enhancement phenomenon presents a problem for the application of computer-aided polyp detection, especially when polyps are submerged in the contrast agents. Second, general kernel approach for surface curvature computation in the second stage of our CAD system could yield erroneous results for thin structures such as small (6-9 mm) polyps and for touching structures such as polyps that lie on haustral folds. Those erroneous curvatures will reduce the sensitivity of polyp detection. The third problem is that more than 150 features are selected from each polyp candidate in the third stage of our CAD system. These high dimensional features make it difficult to learn a good decision boundary for detection classification and reduce the accuracy of predictions. Therefore, an improved CAD system for polyp detection in CTC data is proposed by introducing three new techniques. First, a scale-based scatter correction algorithm is applied to reduce pseudo-enhancement effects in the image pre-processing stage. Second, a cubic spline interpolation method is utilized to accurately estimate curvatures for initial detection generation. Third, a new dimensionality reduction classifier, diffusion map and local linear embedding (DMLLE), is developed for classification and false positives (FP) reduction. Performance of the improved CAD system is evaluated and compared with our existing CAD system (without applying those techniques) using CT scans of 1186 patients. These scans are divided into a training set and a test set. The sensitivity of the improved CAD system increased 18% on training data at a rate of 5 FPs per patient and 15% on test data at a rate of 5 FPs per patient. Our results indicated that the improved CAD system achieved significantly better performance on medium-sized colonic adenomas with higher sensitivity and lower FP rate in CTC.
Noise detection in heart sound recordings.
Zia, Mohammad K; Griffel, Benjamin; Fridman, Vladimir; Saponieri, Cesare; Semmlow, John L
2011-01-01
Coronary artery disease (CAD) is the leading cause of death in the United States. Although progression of CAD can be controlled using drugs and diet, it is usually detected in advanced stages when invasive treatment is required. Current methods to detect CAD are invasive and/or costly, hence not suitable as a regular screening tool to detect CAD in early stages. Currently, we are developing a noninvasive and cost-effective system to detect CAD using the acoustic approach. This method identifies sounds generated by turbulent flow through partially narrowed coronary arteries to detect CAD. The limiting factor of this method is sensitivity to noises commonly encountered in the clinical setting. Because the CAD sounds are faint, these noises can easily obscure the CAD sounds and make detection impossible. In this paper, we propose a method to detect and eliminate noise encountered in the clinical setting using a reference channel. We show that our method is effective in detecting noise, which is essential to the success of the acoustic approach.
NASA Astrophysics Data System (ADS)
B. Shokouhi, Shahriar; Fooladivanda, Aida; Ahmadinejad, Nasrin
2017-12-01
A computer-aided detection (CAD) system is introduced in this paper for detection of breast lesions in dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). The proposed CAD system firstly compensates motion artifacts and segments the breast region. Then, the potential lesion voxels are detected and used as the initial seed points for the seeded region-growing algorithm. A new and robust region-growing algorithm incorporating with Fuzzy C-means (FCM) clustering and vesselness filter is proposed to segment any potential lesion regions. Subsequently, the false positive detections are reduced by applying a discrimination step. This is based on 3D morphological characteristics of the potential lesion regions and kinetic features which are fed to the support vector machine (SVM) classifier. The performance of the proposed CAD system is evaluated using the free-response operating characteristic (FROC) curve. We introduce our collected dataset that includes 76 DCE-MRI studies, 63 malignant and 107 benign lesions. The prepared dataset has been used to verify the accuracy of the proposed CAD system. At 5.29 false positives per case, the CAD system accurately detects 94% of the breast lesions.
NASA Astrophysics Data System (ADS)
Wormanns, Dag; Beyer, Florian; Butzbach, Arnauld; Zierott, Livia; Heindel, Walter
2006-03-01
The purpose of the presented study was to determine the impact of two different CAD systems used as concur-rent reader for detection of actionable nodules (>4 mm) on the interpretation of chest CT scans during routine reporting. Fifty consecutive MDCT scans (1 mm or 1.25 mm slice thickness, 0.8 mm reconstruction increment) were se-lected from clinical routine. All cases were read by a resident and a staff radiologist, and a written report was available in the radiology information system (RIS). The RIS report mentioned at least one actionable pulmonary nodule in 18 cases (50%) and did not report any pulmonary nodule in the remaining 32 cases. Two different recent CAD systems were independently applied to the 50 CT scans as concurrent reader with two radiologists: Siemens LungCare NEV and MEDIAN CAD-Lung. Two radiologists independently reviewed the CAD results and determined if a CAD result was a true positive or a false positive finding. Patients were classified into two groups: in group A if at least one actionable nodule was detected and in group B if no actionable nodules were found. The effect of CAD on routine reporting was simulated as set union of the findings of routine reporting and CAD thus applying CAD as concurrent reader. According to the RIS report group A (patients with at least one actionable nodule) contained 18 cases (36% of all 50 cases), and group B contained 32 cases. Application of a CAD system as concurrent reader resulted in detec-tion of additional CT scans with actionable nodules and reclassification into group A in 16 resp. 18 cases (radi-ologist 1 resp. radiologist 2) with Siemens NEV and in 19 resp. 18 cases with MEDIAN CAD-Lung. In seven cases MEDIAN CAD-Lung and in four cases Siemens NEV reclassified a case into group A while the other CAD system missed the relevant finding. Sensitivity on a nodule (>4 mm) base was .45 for Siemens NEV and .55 for MEDIAN CAD-Lung; the difference was not yet significant (p=.077). In our study use of CAD as second reader in routine reporting doubled the percentage of patients with actionable nodules larger than 4 mm.
A CAD System for Hemorrhagic Stroke.
Nowinski, Wieslaw L; Qian, Guoyu; Hanley, Daniel F
2014-09-01
Computer-aided detection/diagnosis (CAD) is a key component of routine clinical practice, increasingly used for detection, interpretation, quantification and decision support. Despite a critical need, there is no clinically accepted CAD system for stroke yet. Here we introduce a CAD system for hemorrhagic stroke. This CAD system segments, quantifies, and displays hematoma in 2D/3D, and supports evacuation of hemorrhage by thrombolytic treatment monitoring progression and quantifying clot removal. It supports seven-step workflow: select patient, add a new study, process patient's scans, show segmentation results, plot hematoma volumes, show 3D synchronized time series hematomas, and generate report. The system architecture contains four components: library, tools, application with user interface, and hematoma segmentation algorithm. The tools include a contour editor, 3D surface modeler, 3D volume measure, histogramming, hematoma volume plot, and 3D synchronized time-series hematoma display. The CAD system has been designed and implemented in C++. It has also been employed in the CLEAR and MISTIE phase-III, multicenter clinical trials. This stroke CAD system is potentially useful in research and clinical applications, particularly for clinical trials.
Detecting Anomalous Insiders in Collaborative Information Systems
Chen, You; Nyemba, Steve; Malin, Bradley
2012-01-01
Collaborative information systems (CISs) are deployed within a diverse array of environments that manage sensitive information. Current security mechanisms detect insider threats, but they are ill-suited to monitor systems in which users function in dynamic teams. In this paper, we introduce the community anomaly detection system (CADS), an unsupervised learning framework to detect insider threats based on the access logs of collaborative environments. The framework is based on the observation that typical CIS users tend to form community structures based on the subjects accessed (e.g., patients’ records viewed by healthcare providers). CADS consists of two components: 1) relational pattern extraction, which derives community structures and 2) anomaly prediction, which leverages a statistical model to determine when users have sufficiently deviated from communities. We further extend CADS into MetaCADS to account for the semantics of subjects (e.g., patients’ diagnoses). To empirically evaluate the framework, we perform an assessment with three months of access logs from a real electronic health record (EHR) system in a large medical center. The results illustrate our models exhibit significant performance gains over state-of-the-art competitors. When the number of illicit users is low, MetaCADS is the best model, but as the number grows, commonly accessed semantics lead to hiding in a crowd, such that CADS is more prudent. PMID:24489520
Prakashini, K; Babu, Satish; Rajgopal, K V; Kokila, K Raja
2016-01-01
To determine the overall performance of an existing CAD algorithm with thin-section computed tomography (CT) in the detection of pulmonary nodules and to evaluate detection sensitivity at a varying range of nodule density, size, and location. A cross-sectional prospective study was conducted on 20 patients with 322 suspected nodules who underwent diagnostic chest imaging using 64-row multi-detector CT. The examinations were evaluated on reconstructed images of 1.4 mm thickness and 0.7 mm interval. Detection of pulmonary nodules, initially by a radiologist of 2 years experience (RAD) and later by CAD lung nodule software was assessed. Then, CAD nodule candidates were accepted or rejected accordingly. Detected nodules were classified based on their size, density, and location. The performance of the RAD and CAD system was compared with the gold standard that is true nodules confirmed by consensus of senior RAD and CAD together. The overall sensitivity and false-positive (FP) rate of CAD software was calculated. Of the 322 suspected nodules, 221 were classified as true nodules on the consensus of senior RAD and CAD together. Of the true nodules, the RAD detected 206 (93.2%) and 202 (91.4%) by the CAD. CAD and RAD together picked up more number of nodules than either CAD or RAD alone. Overall sensitivity for nodule detection with the CAD program was 91.4%, and FP detection per patient was 5.5%. The CAD showed comparatively higher sensitivity for nodules of size 4-10 mm (93.4%) and nodules in hilar (100%) and central (96.5%) location when compared to RAD's performance. CAD performance was high in detecting pulmonary nodules including the small size and low-density nodules. CAD even with relatively high FP rate, assists and improves RAD's performance as a second reader, especially for nodules located in the central and hilar region and for small nodules by saving RADs time.
Drew, Trafton; Cunningham, Corbin; Wolfe, Jeremy
2012-01-01
Rational and Objectives Computer Aided Detection (CAD) systems are intended to improve performance. This study investigates how CAD might actually interfere with a visual search task. This is a laboratory study with implications for clinical use of CAD. Methods 47 naïve observers in two studies were asked to search for a target, embedded in 1/f2.4 noise while we monitored their eye-movements. For some observers, a CAD system marked 75% of targets and 10% of distractors while other observers completed the study without CAD. In Experiment 1, the CAD system’s primary function was to tell observers where the target might be. In Experiment 2, CAD provided information about target identity. Results In Experiment 1, there was a significant enhancement of observer sensitivity in the presence of CAD (t(22)=4.74, p<.001), but there was also a substantial cost. Targets that were not marked by the CAD system were missed more frequently than equivalent targets in No CAD blocks of the experiment (t(22)=7.02, p<.001). Experiment 2 showed no behavioral benefit from CAD, but also no significant cost on sensitivity to unmarked targets (t(22)=0.6, p=n.s.). Finally, in both experiments, CAD produced reliable changes in eye-movements: CAD observers examined a lower total percentage of the search area than the No CAD observers (Ex 1: t(48)=3.05, p<.005; Ex 2: t(50)=7.31, p<.001). Conclusions CAD signals do not combine with observers’ unaided performance in a straight-forward manner. CAD can engender a sense of certainty that can lead to incomplete search and elevated chances of missing unmarked stimuli. PMID:22958720
The design and integration of retinal CAD-SR to diabetes patient ePR system
NASA Astrophysics Data System (ADS)
Wu, Huiqun; Wei, Yufang; Liu, Brent J.; Shang, Yujuan; Shi, Lili; Jiang, Kui; Dong, Jiancheng
2017-03-01
Diabetic retinopathy (DR) is one of the serious complications of diabetes that could lead to blindness. Digital fundus camera is often used to detect retinal changes but the diagnosis relies too much on ophthalmologist's experience. Based on our previously developed algorithms for quantifying retinal vessels and lesions, we developed a computer aided detection-structured report (CAD-SR) template and implemented it into picture archiving and communication system (PACS). Furthermore, we mapped our CAD-SR into HL7 CDA to integrate CAD findings into diabetes patient electronic patient record (ePR) system. Such integration could provide more quantitative features from fundus image into ePR system, which is valuable for further data mining researches.
NASA Astrophysics Data System (ADS)
Mostapha, Mahmoud; Khalifa, Fahmi; Alansary, Amir; Soliman, Ahmed; Gimel'farb, Georgy; El-Baz, Ayman
2013-10-01
Early detection of renal transplant rejection is important to implement appropriate medical and immune therapy in patients with transplanted kidneys. In literature, a large number of computer-aided diagnostic (CAD) systems using different image modalities, such as ultrasound (US), magnetic resonance imaging (MRI), computed tomography (CT), and radionuclide imaging, have been proposed for early detection of kidney diseases. A typical CAD system for kidney diagnosis consists of a set of processing steps including: motion correction, segmentation of the kidney and/or its internal structures (e.g., cortex, medulla), construction of agent kinetic curves, functional parameter estimation, diagnosis, and assessment of the kidney status. In this paper, we survey the current state-of-the-art CAD systems that have been developed for kidney disease diagnosis using dynamic MRI. In addition, the paper addresses several challenges that researchers face in developing efficient, fast and reliable CAD systems for the early detection of kidney diseases.
Computer Aided Detection (CAD) Systems for Mammography and the Use of GRID in Medicine
NASA Astrophysics Data System (ADS)
Lauria, Adele
It is well known that the most effective way to defeat breast cancer is early detection, as surgery and medical therapies are more efficient when the disease is diagnosed at an early stage. The principal diagnostic technique for breast cancer detection is X-ray mammography. Screening programs have been introduced in many European countries to invite women to have periodic radiological breast examinations. In such screenings, radiologists are often required to examine large numbers of mammograms with a double reading, that is, two radiologists examine the images independently and then compare their results. In this way an increment in sensitivity (the rate of correctly identified images with a lesion) of up to 15% is obtained.1,2 In most radiological centres, it is a rarity to find two radiologists to examine each report. In recent years different Computer Aided Detection (CAD) systems have been developed as a support to radiologists working in mammography: one may hope that the "second opinion" provided by CAD might represent a lower cost alternative to improve the diagnosis. At present, four CAD systems have obtained the FDA approval in the USA. † Studies3,4 show an increment in sensitivity when CAD systems are used. Freer and Ulissey in 2001 5 demonstrated that the use of a commercial CAD system (ImageChecker M1000, R2 Technology) increases the number of cancers detected up to 19.5% with little increment in recall rate. Ciatto et al.,5 in a study simulating a double reading with a commercial CAD system (SecondLook‡), showed a moderate increment in sensitivity while reducing specificity (the rate of correctly identified images without a lesion). Notwithstanding these optimistic results, there is an ongoing debate to define the advantages of the use of CAD as second reader: the main limits underlined, e.g., by Nishikawa6 are that retrospective studies are considered much too optimistic and that clinical studies must be performed to demonstrate a statistically significant benefit from the use of CAD.
Detection of Anomalous Insiders in Collaborative Environments via Relational Analysis of Access Logs
Chen, You; Malin, Bradley
2014-01-01
Collaborative information systems (CIS) are deployed within a diverse array of environments, ranging from the Internet to intelligence agencies to healthcare. It is increasingly the case that such systems are applied to manage sensitive information, making them targets for malicious insiders. While sophisticated security mechanisms have been developed to detect insider threats in various file systems, they are neither designed to model nor to monitor collaborative environments in which users function in dynamic teams with complex behavior. In this paper, we introduce a community-based anomaly detection system (CADS), an unsupervised learning framework to detect insider threats based on information recorded in the access logs of collaborative environments. CADS is based on the observation that typical users tend to form community structures, such that users with low a nity to such communities are indicative of anomalous and potentially illicit behavior. The model consists of two primary components: relational pattern extraction and anomaly detection. For relational pattern extraction, CADS infers community structures from CIS access logs, and subsequently derives communities, which serve as the CADS pattern core. CADS then uses a formal statistical model to measure the deviation of users from the inferred communities to predict which users are anomalies. To empirically evaluate the threat detection model, we perform an analysis with six months of access logs from a real electronic health record system in a large medical center, as well as a publicly-available dataset for replication purposes. The results illustrate that CADS can distinguish simulated anomalous users in the context of real user behavior with a high degree of certainty and with significant performance gains in comparison to several competing anomaly detection models. PMID:25485309
Computer-Aided Diagnosis in Medical Imaging: Historical Review, Current Status and Future Potential
Doi, Kunio
2007-01-01
Computer-aided diagnosis (CAD) has become one of the major research subjects in medical imaging and diagnostic radiology. In this article, the motivation and philosophy for early development of CAD schemes are presented together with the current status and future potential of CAD in a PACS environment. With CAD, radiologists use the computer output as a “second opinion” and make the final decisions. CAD is a concept established by taking into account equally the roles of physicians and computers, whereas automated computer diagnosis is a concept based on computer algorithms only. With CAD, the performance by computers does not have to be comparable to or better than that by physicians, but needs to be complementary to that by physicians. In fact, a large number of CAD systems have been employed for assisting physicians in the early detection of breast cancers on mammograms. A CAD scheme that makes use of lateral chest images has the potential to improve the overall performance in the detection of lung nodules when combined with another CAD scheme for PA chest images. Because vertebral fractures can be detected reliably by computer on lateral chest radiographs, radiologists’ accuracy in the detection of vertebral fractures would be improved by the use of CAD, and thus early diagnosis of osteoporosis would become possible. In MRA, a CAD system has been developed for assisting radiologists in the detection of intracranial aneurysms. On successive bone scan images, a CAD scheme for detection of interval changes has been developed by use of temporal subtraction images. In the future, many CAD schemes could be assembled as packages and implemented as a part of PACS. For example, the package for chest CAD may include the computerized detection of lung nodules, interstitial opacities, cardiomegaly, vertebral fractures, and interval changes in chest radiographs as well as the computerized classification of benign and malignant nodules and the differential diagnosis of interstitial lung diseases. In order to assist in the differential diagnosis, it would be possible to search for and retrieve images (or lesions) with known pathology, which would be very similar to a new unknown case, from PACS when a reliable and useful method has been developed for quantifying the similarity of a pair of images for visual comparison by radiologists. PMID:17349778
Prakashini, K; Babu, Satish; Rajgopal, KV; Kokila, K Raja
2016-01-01
Aims and Objectives: To determine the overall performance of an existing CAD algorithm with thin-section computed tomography (CT) in the detection of pulmonary nodules and to evaluate detection sensitivity at a varying range of nodule density, size, and location. Materials and Methods: A cross-sectional prospective study was conducted on 20 patients with 322 suspected nodules who underwent diagnostic chest imaging using 64-row multi-detector CT. The examinations were evaluated on reconstructed images of 1.4 mm thickness and 0.7 mm interval. Detection of pulmonary nodules, initially by a radiologist of 2 years experience (RAD) and later by CAD lung nodule software was assessed. Then, CAD nodule candidates were accepted or rejected accordingly. Detected nodules were classified based on their size, density, and location. The performance of the RAD and CAD system was compared with the gold standard that is true nodules confirmed by consensus of senior RAD and CAD together. The overall sensitivity and false-positive (FP) rate of CAD software was calculated. Observations and Results: Of the 322 suspected nodules, 221 were classified as true nodules on the consensus of senior RAD and CAD together. Of the true nodules, the RAD detected 206 (93.2%) and 202 (91.4%) by the CAD. CAD and RAD together picked up more number of nodules than either CAD or RAD alone. Overall sensitivity for nodule detection with the CAD program was 91.4%, and FP detection per patient was 5.5%. The CAD showed comparatively higher sensitivity for nodules of size 4–10 mm (93.4%) and nodules in hilar (100%) and central (96.5%) location when compared to RAD's performance. Conclusion: CAD performance was high in detecting pulmonary nodules including the small size and low-density nodules. CAD even with relatively high FP rate, assists and improves RAD's performance as a second reader, especially for nodules located in the central and hilar region and for small nodules by saving RADs time. PMID:27578931
Li, Feng
2015-07-01
This review paper is based on our research experience in the past 30 years. The importance of radiologists' role is discussed in the development or evaluation of new medical images and of computer-aided detection (CAD) schemes in chest radiology. The four main topics include (1) introducing what diseases can be included in a research database for different imaging techniques or CAD systems and what imaging database can be built by radiologists, (2) understanding how radiologists' subjective judgment can be combined with technical objective features to improve CAD performance, (3) sharing our experience in the design of successful observer performance studies, and (4) finally, discussing whether the new images and CAD systems can improve radiologists' diagnostic ability in chest radiology. In conclusion, advanced imaging techniques and detection/classification of CAD systems have a potential clinical impact on improvement of radiologists' diagnostic ability, for both the detection and the differential diagnosis of various lung diseases, in chest radiology.
Kao, E-Fong; Liu, Gin-Chung; Lee, Lo-Yeh; Tsai, Huei-Yi; Jaw, Twei-Shiun
2015-06-01
The ability to give high priority to examinations with pathological findings could be very useful to radiologists with large work lists who wish to first evaluate the most critical studies. A computer-aided detection (CAD) system for identifying chest examinations with abnormalities has therefore been developed. To evaluate the effectiveness of a CAD system on report turnaround times of chest examinations with abnormalities. The CAD system was designed to automatically mark chest examinations with possible abnormalities in the work list of radiologists interpreting chest examinations. The system evaluation was performed in two phases: two radiologists interpreted the chest examinations without CAD in phase 1 and with CAD in phase 2. The time information recorded by the radiology information system was then used to calculate the turnaround times. All chest examinations were reviewed by two other radiologists and were divided into normal and abnormal groups. The turnaround times for the examinations with pathological findings with and without the CAD system assistance were compared. The sensitivity and specificity of the CAD for chest abnormalities were 0.790 and 0.697, respectively, and use of the CAD system decreased the turnaround time for chest examinations with abnormalities by 44%. The turnaround times required for radiologists to identify chest examinations with abnormalities could be reduced by using the CAD system. This system could be useful for radiologists with large work lists who wish to first evaluate the most critical studies. © The Foundation Acta Radiologica 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.
NASA Astrophysics Data System (ADS)
Wei, Jun; Sahiner, Berkman; Hadjiiski, Lubomir M.; Chan, Heang-Ping; Helvie, Mark A.; Roubidoux, Marilyn A.; Zhou, Chuan; Ge, Jun; Zhang, Yiheng
2006-03-01
We are developing a two-view information fusion method to improve the performance of our CAD system for mass detection. Mass candidates on each mammogram were first detected with our single-view CAD system. Potential object pairs on the two-view mammograms were then identified by using the distance between the object and the nipple. Morphological features, Hessian feature, correlation coefficients between the two paired objects and texture features were used as input to train a similarity classifier that estimated a similarity scores for each pair. Finally, a linear discriminant analysis (LDA) classifier was used to fuse the score from the single-view CAD system and the similarity score. A data set of 475 patients containing 972 mammograms with 475 biopsy-proven masses was used to train and test the CAD system. All cases contained the CC view and the MLO or LM view. We randomly divided the data set into two independent sets of 243 cases and 232 cases. The training and testing were performed using the 2-fold cross validation method. The detection performance of the CAD system was assessed by free response receiver operating characteristic (FROC) analysis. The average test FROC curve was obtained from averaging the FP rates at the same sensitivity along the two corresponding test FROC curves from the 2-fold cross validation. At the case-based sensitivities of 90%, 85% and 80% on the test set, the single-view CAD system achieved an FP rate of 2.0, 1.5, and 1.2 FPs/image, respectively. With the two-view fusion system, the FP rates were reduced to 1.7, 1.3, and 1.0 FPs/image, respectively, at the corresponding sensitivities. The improvement was found to be statistically significant (p<0.05) by the AFROC method. Our results indicate that the two-view fusion scheme can improve the performance of mass detection on mammograms.
Information fusion for diabetic retinopathy CAD in digital color fundus photographs.
Niemeijer, Meindert; Abramoff, Michael D; van Ginneken, Bram
2009-05-01
The purpose of computer-aided detection or diagnosis (CAD) technology has so far been to serve as a second reader. If, however, all relevant lesions in an image can be detected by CAD algorithms, use of CAD for automatic reading or prescreening may become feasible. This work addresses the question how to fuse information from multiple CAD algorithms, operating on multiple images that comprise an exam, to determine a likelihood that the exam is normal and would not require further inspection by human operators. We focus on retinal image screening for diabetic retinopathy, a common complication of diabetes. Current CAD systems are not designed to automatically evaluate complete exams consisting of multiple images for which several detection algorithm output sets are available. Information fusion will potentially play a crucial role in enabling the application of CAD technology to the automatic screening problem. Several different fusion methods are proposed and their effect on the performance of a complete comprehensive automatic diabetic retinopathy screening system is evaluated. Experiments show that the choice of fusion method can have a large impact on system performance. The complete system was evaluated on a set of 15,000 exams (60,000 images). The best performing fusion method obtained an area under the receiver operator characteristic curve of 0.881. This indicates that automated prescreening could be applied in diabetic retinopathy screening programs.
NASA Astrophysics Data System (ADS)
Wormanns, Dag; Fiebich, Martin; Wietholt, Christian; Diederich, Stefan; Heindel, Walter
2000-06-01
We evaluated the practical application of a Computer-Aided Diagnosis (CAD) system for viewing spiral computed tomography (CT) of the chest low-dose screening examinations which includes an automatic detection of pulmonary nodules. A UNIX- based CAD system was developed including a detection algorithm for pulmonary nodules and a user interface providing an original axial image, the same image with nodules highlighted, a thin-slab MIP, and a cine mode. As yet, 26 CT examinations with 1625 images were reviewed in a clinical setting and reported by an experienced radiologist using both the CAD system and hardcopies. The CT studies exhibited 19 nodules found on the hardcopies in consensus reporting of 2 experienced radiologists. Viewing with the CAD system was more time consuming than using hardcopies (4.16 vs. 2.92 min) due to analyzing MIP and cine mode. The algorithm detected 49% (18/37) pulmonary nodules larger than 5 mm and 30% (21/70) of all nodules. It produced an average of 6.3 false positive findings per CT study. Most of the missed nodules were adjacent to the pleura. However, the program detected 6 nodules missed by the radiologists. Automatic nodule detection increases the radiologists's awareness of pulmonary lesions. Simultaneous display of axial image and thin-slab MIP makes the radiologist more confident in diagnosis of smaller pulmonary nodules. The CAD system improves the detection of pulmonary nodules at spiral CT. Lack of sensitivity and specificity is still an issue to be addressed but does not prevent practical use.
Tourassi, Georgia D; Harrawood, Brian; Singh, Swatee; Lo, Joseph Y; Floyd, Carey E
2007-01-01
The purpose of this study was to evaluate image similarity measures employed in an information-theoretic computer-assisted detection (IT-CAD) scheme. The scheme was developed for content-based retrieval and detection of masses in screening mammograms. The study is aimed toward an interactive clinical paradigm where physicians query the proposed IT-CAD scheme on mammographic locations that are either visually suspicious or indicated as suspicious by other cuing CAD systems. The IT-CAD scheme provides an evidence-based, second opinion for query mammographic locations using a knowledge database of mass and normal cases. In this study, eight entropy-based similarity measures were compared with respect to retrieval precision and detection accuracy using a database of 1820 mammographic regions of interest. The IT-CAD scheme was then validated on a separate database for false positive reduction of progressively more challenging visual cues generated by an existing, in-house mass detection system. The study showed that the image similarity measures fall into one of two categories; one category is better suited to the retrieval of semantically similar cases while the second is more effective with knowledge-based decisions regarding the presence of a true mass in the query location. In addition, the IT-CAD scheme yielded a substantial reduction in false-positive detections while maintaining high detection rate for malignant masses.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Tourassi, Georgia D.; Harrawood, Brian; Singh, Swatee
The purpose of this study was to evaluate image similarity measures employed in an information-theoretic computer-assisted detection (IT-CAD) scheme. The scheme was developed for content-based retrieval and detection of masses in screening mammograms. The study is aimed toward an interactive clinical paradigm where physicians query the proposed IT-CAD scheme on mammographic locations that are either visually suspicious or indicated as suspicious by other cuing CAD systems. The IT-CAD scheme provides an evidence-based, second opinion for query mammographic locations using a knowledge database of mass and normal cases. In this study, eight entropy-based similarity measures were compared with respect to retrievalmore » precision and detection accuracy using a database of 1820 mammographic regions of interest. The IT-CAD scheme was then validated on a separate database for false positive reduction of progressively more challenging visual cues generated by an existing, in-house mass detection system. The study showed that the image similarity measures fall into one of two categories; one category is better suited to the retrieval of semantically similar cases while the second is more effective with knowledge-based decisions regarding the presence of a true mass in the query location. In addition, the IT-CAD scheme yielded a substantial reduction in false-positive detections while maintaining high detection rate for malignant masses.« less
Computer-aided detection of breast masses: Four-view strategy for screening mammography
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wei Jun; Chan Heangping; Zhou Chuan
2011-04-15
Purpose: To improve the performance of a computer-aided detection (CAD) system for mass detection by using four-view information in screening mammography. Methods: The authors developed a four-view CAD system that emulates radiologists' reading by using the craniocaudal and mediolateral oblique views of the ipsilateral breast to reduce false positives (FPs) and the corresponding views of the contralateral breast to detect asymmetry. The CAD system consists of four major components: (1) Initial detection of breast masses on individual views, (2) information fusion of the ipsilateral views of the breast (referred to as two-view analysis), (3) information fusion of the corresponding viewsmore » of the contralateral breast (referred to as bilateral analysis), and (4) fusion of the four-view information with a decision tree. The authors collected two data sets for training and testing of the CAD system: A mass set containing 389 patients with 389 biopsy-proven masses and a normal set containing 200 normal subjects. All cases had four-view mammograms. The true locations of the masses on the mammograms were identified by an experienced MQSA radiologist. The authors randomly divided the mass set into two independent sets for cross validation training and testing. The overall test performance was assessed by averaging the free response receiver operating characteristic (FROC) curves of the two test subsets. The FP rates during the FROC analysis were estimated by using the normal set only. The jackknife free-response ROC (JAFROC) method was used to estimate the statistical significance of the difference between the test FROC curves obtained with the single-view and the four-view CAD systems. Results: Using the single-view CAD system, the breast-based test sensitivities were 58% and 77% at the FP rates of 0.5 and 1.0 per image, respectively. With the four-view CAD system, the breast-based test sensitivities were improved to 76% and 87% at the corresponding FP rates, respectively. The improvement was found to be statistically significant (p<0.0001) by JAFROC analysis. Conclusions: The four-view information fusion approach that emulates radiologists' reading strategy significantly improves the performance of breast mass detection of the CAD system in comparison with the single-view approach.« less
Machine Learning in Ultrasound Computer-Aided Diagnostic Systems: A Survey
Zhang, Fan; Li, Xuelong
2018-01-01
The ultrasound imaging is one of the most common schemes to detect diseases in the clinical practice. There are many advantages of ultrasound imaging such as safety, convenience, and low cost. However, reading ultrasound imaging is not easy. To support the diagnosis of clinicians and reduce the load of doctors, many ultrasound computer-aided diagnosis (CAD) systems are proposed. In recent years, the success of deep learning in the image classification and segmentation led to more and more scholars realizing the potential of performance improvement brought by utilizing the deep learning in the ultrasound CAD system. This paper summarized the research which focuses on the ultrasound CAD system utilizing machine learning technology in recent years. This study divided the ultrasound CAD system into two categories. One is the traditional ultrasound CAD system which employed the manmade feature and the other is the deep learning ultrasound CAD system. The major feature and the classifier employed by the traditional ultrasound CAD system are introduced. As for the deep learning ultrasound CAD, newest applications are summarized. This paper will be useful for researchers who focus on the ultrasound CAD system. PMID:29687000
Machine Learning in Ultrasound Computer-Aided Diagnostic Systems: A Survey.
Huang, Qinghua; Zhang, Fan; Li, Xuelong
2018-01-01
The ultrasound imaging is one of the most common schemes to detect diseases in the clinical practice. There are many advantages of ultrasound imaging such as safety, convenience, and low cost. However, reading ultrasound imaging is not easy. To support the diagnosis of clinicians and reduce the load of doctors, many ultrasound computer-aided diagnosis (CAD) systems are proposed. In recent years, the success of deep learning in the image classification and segmentation led to more and more scholars realizing the potential of performance improvement brought by utilizing the deep learning in the ultrasound CAD system. This paper summarized the research which focuses on the ultrasound CAD system utilizing machine learning technology in recent years. This study divided the ultrasound CAD system into two categories. One is the traditional ultrasound CAD system which employed the manmade feature and the other is the deep learning ultrasound CAD system. The major feature and the classifier employed by the traditional ultrasound CAD system are introduced. As for the deep learning ultrasound CAD, newest applications are summarized. This paper will be useful for researchers who focus on the ultrasound CAD system.
Kobayashi, Hajime; Ohkubo, Masaki; Narita, Akihiro; Marasinghe, Janaka C; Murao, Kohei; Matsumoto, Toru; Sone, Shusuke
2017-01-01
Objective: We propose the application of virtual nodules to evaluate the performance of computer-aided detection (CAD) of lung nodules in cancer screening using low-dose CT. Methods: The virtual nodules were generated based on the spatial resolution measured for a CT system used in an institution providing cancer screening and were fused into clinical lung images obtained at that institution, allowing site specificity. First, we validated virtual nodules as an alternative to artificial nodules inserted into a phantom. In addition, we compared the results of CAD analysis between the real nodules (n = 6) and the corresponding virtual nodules. Subsequently, virtual nodules of various sizes and contrasts between nodule density and background density (ΔCT) were inserted into clinical images (n = 10) and submitted for CAD analysis. Results: In the validation study, 46 of 48 virtual nodules had the same CAD results as artificial nodules (kappa coefficient = 0.913). Real nodules and the corresponding virtual nodules showed the same CAD results. The detection limits of the tested CAD system were determined in terms of size and density of peripheral lung nodules; we demonstrated that a nodule with a 5-mm diameter was detected when the nodule had a ΔCT > 220 HU. Conclusion: Virtual nodules are effective in evaluating CAD performance using site-specific scan/reconstruction conditions. Advances in knowledge: Virtual nodules can be an effective means of evaluating site-specific CAD performance. The methodology for guiding the detection limit for nodule size/density might be a useful evaluation strategy. PMID:27897029
[Computed tomography with computer-assisted detection of pulmonary nodules in dogs and cats].
Niesterok, C; Piesnack, S; Köhler, C; Ludewig, E; Alef, M; Kiefer, I
2015-01-01
The aim of this study was to assess the potential benefit of computer-assisted detection (CAD) of pulmonary nodules in veterinary medicine. Therefore, the CAD rate was compared to the detection rates of two individual examiners in terms of its sensitivity and false-positive findings. We included 51 dogs and 16 cats with pulmonary nodules previously diagnosed by computed tomography. First, the number of nodules ≥ 3 mm was recorded for each patient by two independent examiners. Subsequently, each examiner used the CAD software for automated nodule detection. With the knowledge of the CAD results, a final consensus decision on the number of nodules was achieved. The software used was a commercially available CAD program. The sensitivity of examiner 1 was 89.2%, while that of examiner 2 reached 87.4%. CAD had a sensitivity of 69.4%. With CAD, the sensitivity of examiner 1 increased to 94.7% and that of examiner 2 to 90.8%. The CAD-system, which we used in our study, had a moderate sensitivity of 69.4%. Despite its severe limitations, with a high level of false-positive and false-negative results, CAD increased the examiners' sensitivity. Therefore, its supportive role in diagnostics appears to be evident.
NASA Astrophysics Data System (ADS)
Qiu, Yuchen; Wang, Xingwei; Chen, Xiaodong; Li, Yuhua; Liu, Hong; Li, Shibo; Zheng, Bin
2010-02-01
Visually searching for analyzable metaphase chromosome cells under microscopes is quite time-consuming and difficult. To improve detection efficiency, consistency, and diagnostic accuracy, an automated microscopic image scanning system was developed and tested to directly acquire digital images with sufficient spatial resolution for clinical diagnosis. A computer-aided detection (CAD) scheme was also developed and integrated into the image scanning system to search for and detect the regions of interest (ROI) that contain analyzable metaphase chromosome cells in the large volume of scanned images acquired from one specimen. Thus, the cytogeneticists only need to observe and interpret the limited number of ROIs. In this study, the high-resolution microscopic image scanning and CAD performance was investigated and evaluated using nine sets of images scanned from either bone marrow (three) or blood (six) specimens for diagnosis of leukemia. The automated CAD-selection results were compared with the visual selection. In the experiment, the cytogeneticists first visually searched for the analyzable metaphase chromosome cells from specimens under microscopes. The specimens were also automated scanned and followed by applying the CAD scheme to detect and save ROIs containing analyzable cells while deleting the others. The automated selected ROIs were then examined by a panel of three cytogeneticists. From the scanned images, CAD selected more analyzable cells than initially visual examinations of the cytogeneticists in both blood and bone marrow specimens. In general, CAD had higher performance in analyzing blood specimens. Even in three bone marrow specimens, CAD selected 50, 22, 9 ROIs, respectively. Except matching with the initially visual selection of 9, 7, and 5 analyzable cells in these three specimens, the cytogeneticists also selected 41, 15 and 4 new analyzable cells, which were missed in initially visual searching. This experiment showed the feasibility of applying this CAD-guided high-resolution microscopic image scanning system to prescreen and select ROIs that may contain analyzable metaphase chromosome cells. The success and the further improvement of this automated scanning system may have great impact on the future clinical practice in genetic laboratories to detect and diagnose diseases.
NASA Astrophysics Data System (ADS)
Tsehay, Yohannes K.; Lay, Nathan S.; Roth, Holger R.; Wang, Xiaosong; Kwak, Jin Tae; Turkbey, Baris I.; Pinto, Peter A.; Wood, Brad J.; Summers, Ronald M.
2017-03-01
Prostate cancer (PCa) is the second most common cause of cancer related deaths in men. Multiparametric MRI (mpMRI) is the most accurate imaging method for PCa detection; however, it requires the expertise of experienced radiologists leading to inconsistency across readers of varying experience. To increase inter-reader agreement and sensitivity, we developed a computer-aided detection (CAD) system that can automatically detect lesions on mpMRI that readers can use as a reference. We investigated a convolutional neural network based deep-learing (DCNN) architecture to find an improved solution for PCa detection on mpMRI. We adopted a network architecture from a state-of-the-art edge detector that takes an image as an input and produces an image probability map. Two-fold cross validation along with a receiver operating characteristic (ROC) analysis and free-response ROC (FROC) were used to determine our deep-learning based prostate-CAD's (CADDL) performance. The efficacy was compared to an existing prostate CAD system that is based on hand-crafted features, which was evaluated on the same test-set. CADDL had an 86% detection rate at 20% false-positive rate while the top-down learning CAD had 80% detection rate at the same false-positive rate, which translated to 94% and 85% detection rate at 10 false-positives per patient on the FROC. A CNN based CAD is able to detect cancerous lesions on mpMRI of the prostate with results comparable to an existing prostate-CAD showing potential for further development.
NASA Astrophysics Data System (ADS)
Wormanns, Dag; Fiebich, Martin; Saidi, Mustafa; Diederich, Stefan; Heindel, Walter
2001-05-01
The purpose of the study was to evaluate a computer aided diagnosis (CAD) workstation with automatic detection of pulmonary nodules at low-dose spiral CT in a clinical setting for early detection of lung cancer. Two radiologists in consensus reported 88 consecutive spiral CT examinations. All examinations were reviewed using a UNIX-based CAD workstation with a self-developed algorithm for automatic detection of pulmonary nodules. The algorithm was designed to detect nodules with at least 5 mm diameter. The results of automatic nodule detection were compared to the consensus reporting of two radiologists as gold standard. Additional CAD findings were regarded as nodules initially missed by the radiologists or as false positive results. A total of 153 nodules were detected with all modalities (diameter: 85 nodules <5mm, 63 nodules 5-9 mm, 5 nodules >= 10 mm). Reasons for failure of automatic nodule detection were assessed. Sensitivity of radiologists for nodules >=5 mm was 85%, sensitivity of CAD was 38%. For nodules >=5 mm without pleural contact sensitivity was 84% for radiologists at 45% for CAD. CAD detected 15 (10%) nodules not mentioned in the radiologist's report but representing real nodules, among them 10 (15%) nodules with a diameter $GREW5 mm. Reasons for nodules missed by CAD include: exclusion because of morphological features during region analysis (33%), nodule density below the detection threshold (26%), pleural contact (33%), segmentation errors (5%) and other reasons (2%). CAD improves detection of pulmonary nodules at spiral CT significantly and is a valuable second opinion in a clinical setting for lung cancer screening. Optimization of region analysis and an appropriate density threshold have a potential for further improvement of automatic nodule detection.
Computer aided detection of surgical retained foreign object for prevention
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hadjiiski, Lubomir, E-mail: lhadjisk@umich.edu; Marentis, Theodore C.; Rondon, Lucas
2015-03-15
Purpose: Surgical retained foreign objects (RFOs) have significant morbidity and mortality. They are associated with approximately $1.5 × 10{sup 9} annually in preventable medical costs. The detection accuracy of radiographs for RFOs is a mediocre 59%. The authors address the RFO problem with two complementary technologies: a three-dimensional (3D) gossypiboma micro tag, the μTag that improves the visibility of RFOs on radiographs, and a computer aided detection (CAD) system that detects the μTag. It is desirable for the CAD system to operate in a high specificity mode in the operating room (OR) and function as a first reader for themore » surgeon. This allows for fast point of care results and seamless workflow integration. The CAD system can also operate in a high sensitivity mode as a second reader for the radiologist to ensure the highest possible detection accuracy. Methods: The 3D geometry of the μTag produces a similar two dimensional (2D) depiction on radiographs regardless of its orientation in the human body and ensures accurate detection by a radiologist and the CAD. The authors created a data set of 1800 cadaver images with the 3D μTag and other common man-made surgical objects positioned randomly. A total of 1061 cadaver images contained a single μTag and the remaining 739 were without μTag. A radiologist marked the location of the μTag using an in-house developed graphical user interface. The data set was partitioned into three independent subsets: a training set, a validation set, and a test set, consisting of 540, 560, and 700 images, respectively. A CAD system with modules that included preprocessing μTag enhancement, labeling, segmentation, feature analysis, classification, and detection was developed. The CAD system was developed using the training and the validation sets. Results: On the training set, the CAD achieved 81.5% sensitivity with 0.014 false positives (FPs) per image in a high specificity mode for the surgeons in the OR and 96.1% sensitivity with 0.81 FPs per image in a high sensitivity mode for the radiologists. On the independent test set, the CAD achieved 79.5% sensitivity with 0.003 FPs per image in a high specificity mode for the surgeons and 90.2% sensitivity with 0.23 FPs per image in a high sensitivity mode for the radiologists. Conclusions: To the best of the authors’ knowledge, this is the first time a 3D μTag is used to produce a recognizable, substantially similar 2D projection on radiographs regardless of orientation in space. It is the first time a CAD system is used to search for man-made objects over anatomic background. The CAD system for the μTags achieved reasonable performance in both the high specificity and the high sensitivity modes.« less
Computer-Aided Diagnosis Systems for Lung Cancer: Challenges and Methodologies
El-Baz, Ayman; Beache, Garth M.; Gimel'farb, Georgy; Suzuki, Kenji; Okada, Kazunori; Elnakib, Ahmed; Soliman, Ahmed; Abdollahi, Behnoush
2013-01-01
This paper overviews one of the most important, interesting, and challenging problems in oncology, the problem of lung cancer diagnosis. Developing an effective computer-aided diagnosis (CAD) system for lung cancer is of great clinical importance and can increase the patient's chance of survival. For this reason, CAD systems for lung cancer have been investigated in a huge number of research studies. A typical CAD system for lung cancer diagnosis is composed of four main processing steps: segmentation of the lung fields, detection of nodules inside the lung fields, segmentation of the detected nodules, and diagnosis of the nodules as benign or malignant. This paper overviews the current state-of-the-art techniques that have been developed to implement each of these CAD processing steps. For each technique, various aspects of technical issues, implemented methodologies, training and testing databases, and validation methods, as well as achieved performances, are described. In addition, the paper addresses several challenges that researchers face in each implementation step and outlines the strengths and drawbacks of the existing approaches for lung cancer CAD systems. PMID:23431282
PACS-Based Computer-Aided Detection and Diagnosis
NASA Astrophysics Data System (ADS)
Huang, H. K. (Bernie); Liu, Brent J.; Le, Anh HongTu; Documet, Jorge
The ultimate goal of Picture Archiving and Communication System (PACS)-based Computer-Aided Detection and Diagnosis (CAD) is to integrate CAD results into daily clinical practice so that it becomes a second reader to aid the radiologist's diagnosis. Integration of CAD and Hospital Information System (HIS), Radiology Information System (RIS) or PACS requires certain basic ingredients from Health Level 7 (HL7) standard for textual data, Digital Imaging and Communications in Medicine (DICOM) standard for images, and Integrating the Healthcare Enterprise (IHE) workflow profiles in order to comply with the Health Insurance Portability and Accountability Act (HIPAA) requirements to be a healthcare information system. Among the DICOM standards and IHE workflow profiles, DICOM Structured Reporting (DICOM-SR); and IHE Key Image Note (KIN), Simple Image and Numeric Report (SINR) and Post-processing Work Flow (PWF) are utilized in CAD-HIS/RIS/PACS integration. These topics with examples are presented in this chapter.
Huo, Zhimin; Summers, Ronald M.; Paquerault, Sophie; Lo, Joseph; Hoffmeister, Jeffrey; Armato, Samuel G.; Freedman, Matthew T.; Lin, Jesse; Ben Lo, Shih-Chung; Petrick, Nicholas; Sahiner, Berkman; Fryd, David; Yoshida, Hiroyuki; Chan, Heang-Ping
2013-01-01
Computer-aided detection/diagnosis (CAD) is increasingly used for decision support by clinicians for detection and interpretation of diseases. However, there are no quality assurance (QA) requirements for CAD in clinical use at present. QA of CAD is important so that end users can be made aware of changes in CAD performance both due to intentional or unintentional causes. In addition, end-user training is critical to prevent improper use of CAD, which could potentially result in lower overall clinical performance. Research on QA of CAD and user training are limited to date. The purpose of this paper is to bring attention to these issues, inform the readers of the opinions of the members of the American Association of Physicists in Medicine (AAPM) CAD subcommittee, and thus stimulate further discussion in the CAD community on these topics. The recommendations in this paper are intended to be work items for AAPM task groups that will be formed to address QA and user training issues on CAD in the future. The work items may serve as a framework for the discussion and eventual design of detailed QA and training procedures for physicists and users of CAD. Some of the recommendations are considered by the subcommittee to be reasonably easy and practical and can be implemented immediately by the end users; others are considered to be “best practice” approaches, which may require significant effort, additional tools, and proper training to implement. The eventual standardization of the requirements of QA procedures for CAD will have to be determined through consensus from members of the CAD community, and user training may require support of professional societies. It is expected that high-quality CAD and proper use of CAD could allow these systems to achieve their true potential, thus benefiting both the patients and the clinicians, and may bring about more widespread clinical use of CAD for many other diseases and applications. It is hoped that the awareness of the need for appropriate CAD QA and user training will stimulate new ideas and approaches for implementing such procedures efficiently and effectively as well as funding opportunities to fulfill such critical efforts. PMID:23822459
NASA Astrophysics Data System (ADS)
Lee, Donghoon; Kim, Ye-seul; Choi, Sunghoon; Lee, Haenghwa; Jo, Byungdu; Choi, Seungyeon; Shin, Jungwook; Kim, Hee-Joung
2017-03-01
The chest digital tomosynthesis(CDT) is recently developed medical device that has several advantage for diagnosing lung disease. For example, CDT provides depth information with relatively low radiation dose compared to computed tomography (CT). However, a major problem with CDT is the image artifacts associated with data incompleteness resulting from limited angle data acquisition in CDT geometry. For this reason, the sensitivity of lung disease was not clear compared to CT. In this study, to improve sensitivity of lung disease detection in CDT, we developed computer aided diagnosis (CAD) systems based on machine learning. For design CAD systems, we used 100 cases of lung nodules cropped images and 100 cases of normal lesion cropped images acquired by lung man phantoms and proto type CDT. We used machine learning techniques based on support vector machine and Gabor filter. The Gabor filter was used for extracting characteristics of lung nodules and we compared performance of feature extraction of Gabor filter with various scale and orientation parameters. We used 3, 4, 5 scales and 4, 6, 8 orientations. After extracting features, support vector machine (SVM) was used for classifying feature of lesions. The linear, polynomial and Gaussian kernels of SVM were compared to decide the best SVM conditions for CDT reconstruction images. The results of CAD system with machine learning showed the capability of automatically lung lesion detection. Furthermore detection performance was the best when Gabor filter with 5 scale and 8 orientation and SVM with Gaussian kernel were used. In conclusion, our suggested CAD system showed improving sensitivity of lung lesion detection in CDT and decide Gabor filter and SVM conditions to achieve higher detection performance of our developed CAD system for CDT.
Computer aided detection system for lung cancer using computer tomography scans
NASA Astrophysics Data System (ADS)
Mahesh, Shanthi; Rakesh, Spoorthi; Patil, Vidya C.
2018-04-01
Lung Cancer is a disease can be defined as uncontrolled cell growth in tissues of the lung. If we detect the Lung Cancer in its early stage, then that could be the key of its cure. In this work the non-invasive methods are studied for assisting in nodule detection. It supplies a Computer Aided Diagnosis System (CAD) for early detection of lung cancer nodules from the Computer Tomography (CT) images. CAD system is the one which helps to improve the diagnostic performance of radiologists in their image interpretations. The main aim of this technique is to develop a CAD system for finding the lung cancer using the lung CT images and classify the nodule as Benign or Malignant. For classifying cancer cells, SVM classifier is used. Here, image processing techniques have been used to de-noise, to enhance, for segmentation and edge detection of an image is used to extract the area, perimeter and shape of nodule. The core factors of this research are Image quality and accuracy.
Computer-aided detection in musculoskeletal projection radiography: A systematic review.
Gundry, M; Knapp, K; Meertens, R; Meakin, J R
2018-05-01
To investigated the accuracy of computer-aided detection (CAD) software in musculoskeletal projection radiography via a systematic review. Following selection screening, eligible studies were assessed for bias, and had their study characteristics extracted resulting in 22 studies being included. Of these 22 three studies had tested their CAD software in a clinical setting; the first study investigated vertebral fractures, reporting a sensitivity score of 69.3% with CAD, compared to 59.8% sensitivity without CAD. The second study tested dental caries diagnosis producing a sensitivity score of 68.8% and specificity of 94.1% with CAD, compared to sensitivity of 39.3% and specificity of 96.7% without CAD. The third indicated osteoporotic cases based on CAD, resulting in 100% sensitivity and 81.3% specificity. The current evidence reported shows a lack of development into the clinical testing phase; however the research does show future promise in the variation of different CAD systems. Copyright © 2017 The College of Radiographers. Published by Elsevier Ltd. All rights reserved.
Computer-aided detection of brain metastasis on 3D MR imaging: Observer performance study.
Sunwoo, Leonard; Kim, Young Jae; Choi, Seung Hong; Kim, Kwang-Gi; Kang, Ji Hee; Kang, Yeonah; Bae, Yun Jung; Yoo, Roh-Eul; Kim, Jihang; Lee, Kyong Joon; Lee, Seung Hyun; Choi, Byung Se; Jung, Cheolkyu; Sohn, Chul-Ho; Kim, Jae Hyoung
2017-01-01
To assess the effect of computer-aided detection (CAD) of brain metastasis (BM) on radiologists' diagnostic performance in interpreting three-dimensional brain magnetic resonance (MR) imaging using follow-up imaging and consensus as the reference standard. The institutional review board approved this retrospective study. The study cohort consisted of 110 consecutive patients with BM and 30 patients without BM. The training data set included MR images of 80 patients with 450 BM nodules. The test set included MR images of 30 patients with 134 BM nodules and 30 patients without BM. We developed a CAD system for BM detection using template-matching and K-means clustering algorithms for candidate detection and an artificial neural network for false-positive reduction. Four reviewers (two neuroradiologists and two radiology residents) interpreted the test set images before and after the use of CAD in a sequential manner. The sensitivity, false positive (FP) per case, and reading time were analyzed. A jackknife free-response receiver operating characteristic (JAFROC) method was used to determine the improvement in the diagnostic accuracy. The sensitivity of CAD was 87.3% with an FP per case of 302.4. CAD significantly improved the diagnostic performance of the four reviewers with a figure-of-merit (FOM) of 0.874 (without CAD) vs. 0.898 (with CAD) according to JAFROC analysis (p < 0.01). Statistically significant improvement was noted only for less-experienced reviewers (FOM without vs. with CAD, 0.834 vs. 0.877, p < 0.01). The additional time required to review the CAD results was approximately 72 sec (40% of the total review time). CAD as a second reader helps radiologists improve their diagnostic performance in the detection of BM on MR imaging, particularly for less-experienced reviewers.
Tanaka, Toyohiko; Nitta, Norihisa; Ohta, Shinichi; Kobayashi, Tsuyoshi; Kano, Akiko; Tsuchiya, Keiko; Murakami, Yoko; Kitahara, Sawako; Wakamiya, Makoto; Furukawa, Akira; Takahashi, Masashi; Murata, Kiyoshi
2009-12-01
A computer-aided detection (CAD) system was evaluated for its ability to detect microcalcifications and masses on images obtained with a digital phase-contrast mammography (PCM) system, a system characterised by the sharp images provided by phase contrast and by the high resolution of 25-μm-pixel mammograms. Fifty abnormal and 50 normal mammograms were collected from about 3,500 mammograms and printed on film for reading on a light box. Seven qualified radiologists participated in an observer study based on receiver operating characteristic (ROC) analysis. The average of the areas under ROC curve (AUC) values for the ROC analysis with and without CAD were 0.927 and 0.897 respectively (P = 0.015). The AUC values improved from 0.840 to 0.888 for microcalcifications (P = 0.034) and from 0.947 to 0.962 for masses (P = 0.025) respectively. The application of CAD to the PCM system is a promising approach for the detection of breast cancer in its early stages.
A citizen science approach to optimising computer aided detection (CAD) in mammography
NASA Astrophysics Data System (ADS)
Ionescu, Georgia V.; Harkness, Elaine F.; Hulleman, Johan; Astley, Susan M.
2018-03-01
Computer aided detection (CAD) systems assist medical experts during image interpretation. In mammography, CAD systems prompt suspicious regions which help medical experts to detect early signs of cancer. This is a challenging task and prompts may appear in regions that are actually normal, whilst genuine cancers may be missed. The effect prompting has on readers performance is not fully known. In order to explore the effects of prompting errors, we have created an online game (Bat Hunt), designed for non-experts, that mirrors mammographic CAD. This allows us to explore a wider parameter space. Users are required to detect bats in images of flocks of birds, with image difficulty matched to the proportions of screening mammograms in different BI-RADS density categories. Twelve prompted conditions were investigated, along with unprompted detection. On average, players achieved a sensitivity of 0.33 for unprompted detection, and sensitivities of 0.75, 0.83, and 0.92 respectively for 70%, 80%, and 90% of targets prompted, regardless of CAD specificity. False prompts distract players from finding unprompted targets if they appear in the same image. Player performance decreases when the number of false prompts increases, and increases proportionally with prompting sensitivity. Median lowest d' was for unprompted condition (1.08) and the highest for sensitivity 90% and 0.5 false prompts per image (d'=4.48).
Gubern-Mérida, Albert; Vreemann, Suzan; Martí, Robert; Melendez, Jaime; Lardenoije, Susanne; Mann, Ritse M; Karssemeijer, Nico; Platel, Bram
2016-02-01
To evaluate the performance of an automated computer-aided detection (CAD) system to detect breast cancers that were overlooked or misinterpreted in a breast MRI screening program for women at increased risk. We identified 40 patients that were diagnosed with breast cancer in MRI and had a prior MRI examination reported as negative available. In these prior examinations, 24 lesions could retrospectively be identified by two breast radiologists in consensus: 11 were scored as visible and 13 as minimally visible. Additionally, 120 normal scans were collected from 120 women without history of breast cancer or breast surgery participating in the same MRI screening program. A fully automated CAD system was applied to this dataset to detect malignant lesions. At 4 false-positives per normal case, the sensitivity for the detection of cancer lesions that were visible or minimally visible in retrospect in prior-negative examinations was 0.71 (95% CI=0.38-1.00) and 0.31 (0.07-0.59), respectively. A substantial proportion of cancers that were misinterpreted or overlooked in an MRI screening program was detected by a CAD system in prior-negative examinations. It has to be clarified with further studies if such a CAD system has an influence on the number of misinterpreted and overlooked cancers in clinical practice when results are given to a radiologist. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.
Effectiveness of computer aided detection for solitary pulmonary nodules
NASA Astrophysics Data System (ADS)
Yan, Jiayong; Li, Wenjie; Du, Xiangying; Lu, Huihai; Xu, Jianrong; Xu, Mantao; Rong, Dongdong
2009-02-01
This study is to investigate the incremental effect of using a high performance computer-aided detection (CAD) system in detection of solitary pulmonary nodules in chest radiographs. The Kodak Chest CAD system was evaluated by a panel of six radiologists at different levels of experience. The observer study consisted of two independent phases: readings without CAD and readings with assistance of CAD. The study was conducted over a set of chest radiographs comprising 150 cancer cases and 150 cancer-free cases. The actual sensitivity of the CAD system is 72% with 3.7 false positives per case. Receiver operating characteristic (ROC) analysis was used to assess the overall observer performance. The AUZ (area under ROC curve) showed a significantly improvement (P=0.0001) from 0.844 to 0.884 after using CAD. The ROC analysis was also applied for observer performances on nodules in different sizes and visibilities. The average AUZs are improved from 0.798 to 0.835 (P=0.0003) for 5-10mm nodules, 0.853 to 0.907 (P=0.001) for 10-15mm nodules, 0.864 to 0.897 (P=0.051) for 15-20 mm nodules and 0.859 to 0.896 (P=0.0342) for 20-30mm nodules, respectively. For different visibilities, the average AUZs are improved from 0.886 to 0.915 (P=0.0337), 0.803 to 0.840 (P=0.063), 0.830 to 0.893 (P=0.0001), and 0.813 to 0.847 (P=0.152), for nodules clearly visible, hidden by ribs, partially overlap with ribs, and overlap with other structures, respectively. These results showed that observer performance could be greatly improved when the CAD system is employed as a second reader, especially for small nodules and nodules occluded by ribs.
Automatic rectum limit detection by anatomical markers correlation.
Namías, R; D'Amato, J P; del Fresno, M; Vénere, M
2014-06-01
Several diseases take place at the end of the digestive system. Many of them can be diagnosed by means of different medical imaging modalities together with computer aided detection (CAD) systems. These CAD systems mainly focus on the complete segmentation of the digestive tube. However, the detection of limits between different sections could provide important information to these systems. In this paper we present an automatic method for detecting the rectum and sigmoid colon limit using a novel global curvature analysis over the centerline of the segmented digestive tube in different imaging modalities. The results are compared with the gold standard rectum upper limit through a validation scheme comprising two different anatomical markers: the third sacral vertebra and the average rectum length. Experimental results in both magnetic resonance imaging (MRI) and computed tomography colonography (CTC) acquisitions show the efficacy of the proposed strategy in automatic detection of rectum limits. The method is intended for application to the rectum segmentation in MRI for geometrical modeling and as contextual information source in virtual colonoscopies and CAD systems. Copyright © 2014 Elsevier Ltd. All rights reserved.
Samala, Ravi K; Chan, Heang-Ping; Hadjiiski, Lubomir; Helvie, Mark A; Wei, Jun; Cha, Kenny
2016-12-01
Develop a computer-aided detection (CAD) system for masses in digital breast tomosynthesis (DBT) volume using a deep convolutional neural network (DCNN) with transfer learning from mammograms. A data set containing 2282 digitized film and digital mammograms and 324 DBT volumes were collected with IRB approval. The mass of interest on the images was marked by an experienced breast radiologist as reference standard. The data set was partitioned into a training set (2282 mammograms with 2461 masses and 230 DBT views with 228 masses) and an independent test set (94 DBT views with 89 masses). For DCNN training, the region of interest (ROI) containing the mass (true positive) was extracted from each image. False positive (FP) ROIs were identified at prescreening by their previously developed CAD systems. After data augmentation, a total of 45 072 mammographic ROIs and 37 450 DBT ROIs were obtained. Data normalization and reduction of non-uniformity in the ROIs across heterogeneous data was achieved using a background correction method applied to each ROI. A DCNN with four convolutional layers and three fully connected (FC) layers was first trained on the mammography data. Jittering and dropout techniques were used to reduce overfitting. After training with the mammographic ROIs, all weights in the first three convolutional layers were frozen, and only the last convolution layer and the FC layers were randomly initialized again and trained using the DBT training ROIs. The authors compared the performances of two CAD systems for mass detection in DBT: one used the DCNN-based approach and the other used their previously developed feature-based approach for FP reduction. The prescreening stage was identical in both systems, passing the same set of mass candidates to the FP reduction stage. For the feature-based CAD system, 3D clustering and active contour method was used for segmentation; morphological, gray level, and texture features were extracted and merged with a linear discriminant classifier to score the detected masses. For the DCNN-based CAD system, ROIs from five consecutive slices centered at each candidate were passed through the trained DCNN and a mass likelihood score was generated. The performances of the CAD systems were evaluated using free-response ROC curves and the performance difference was analyzed using a non-parametric method. Before transfer learning, the DCNN trained only on mammograms with an AUC of 0.99 classified DBT masses with an AUC of 0.81 in the DBT training set. After transfer learning with DBT, the AUC improved to 0.90. For breast-based CAD detection in the test set, the sensitivity for the feature-based and the DCNN-based CAD systems was 83% and 91%, respectively, at 1 FP/DBT volume. The difference between the performances for the two systems was statistically significant (p-value < 0.05). The image patterns learned from the mammograms were transferred to the mass detection on DBT slices through the DCNN. This study demonstrated that large data sets collected from mammography are useful for developing new CAD systems for DBT, alleviating the problem and effort of collecting entirely new large data sets for the new modality.
A new screening pathway for identifying asymptomatic patients using dental panoramic radiographs
NASA Astrophysics Data System (ADS)
Hayashi, Tatsuro; Matsumoto, Takuya; Sawagashira, Tsuyoshi; Tagami, Motoki; Katsumata, Akitoshi; Hayashi, Yoshinori; Muramatsu, Chisako; Zhou, Xiangrong; Iida, Yukihiro; Matsuoka, Masato; Katagi, Kiyoji; Fujita, Hiroshi
2012-03-01
To identify asymptomatic patients is the challenging task and the essential first step in diagnosis. Findings of dental panoramic radiographs include not only dental conditions but also radiographic signs that are suggestive of possible systemic diseases such as osteoporosis, arteriosclerosis, and maxillary sinusitis. Detection of such signs on panoramic radiographs has a potential to provide supplemental benefits for patients. However, it is not easy for general dental practitioners to pay careful attention to such signs. We addressed the development of a computer-aided detection (CAD) system that detects radiographic signs of pathology on panoramic images, and the design of the framework of new screening pathway by cooperation of dentists and our CAD system. The performance evaluation of our CAD system showed the sensitivity and specificity in the identification of osteoporotic patients were 92.6 % and 100 %, respectively, and those of the maxillary sinus abnormality were 89.6 % and 73.6 %, respectively. The detection rate of carotid artery calcifications that suggests the need for further medical evaluation was approximately 93.6 % with 4.4 false-positives per image. To validate the utility of the new screening pathway, preliminary clinical trials by using our CAD system were conducted. To date, 223 panoramic images were processed and 4 asymptomatic patients with suspected osteoporosis, 7 asymptomatic patients with suspected calcifications, and 40 asymptomatic patients with suspected maxillary sinusitis were detected in our initial trial. It was suggested that our new screening pathway could be useful to identify asymptomatic patients with systemic diseases.
The clinical evaluation of the CADence device in the acoustic detection of coronary artery disease.
Thomas, Joseph L; Ridner, Michael; Cole, Jason H; Chambers, Jeffrey W; Bokhari, Sabahat; Yannopoulos, Demetris; Kern, Morton; Wilson, Robert F; Budoff, Matthew J
2018-06-23
The noninvasive detection of turbulent coronary flow may enable diagnosis of significant coronary artery disease (CAD) using novel sensor and analytic technology. Eligible patients (n = 1013) with chest pain and CAD risk factors undergoing nuclear stress testing were studied using the CADence (AUM Cardiovascular Inc., Northfield MN) acoustic detection (AD) system. The trial was designed to demonstrate non-inferiority of AD for diagnostic accuracy in detecting significant CAD as compared to an objective performance criteria (sensitivity 83% and specificity 80%, with 15% non-inferiority margins) for nuclear stress testing. AD analysis was blinded to clinical, core lab-adjudicated angiographic, and nuclear data. The presence of significant CAD was determined by computed tomographic (CCTA) or invasive angiography. A total of 1013 subjects without prior coronary revascularization or Q-wave myocardial infarction were enrolled. Primary analysis was performed on subjects with complete angiographic and AD data (n = 763) including 111 subjects (15%) with severe CAD based on CCTA (n = 34) and invasive angiography (n = 77). The sensitivity and specificity of AD were 78% (p = 0.012 for non-inferiority) and 35% (p < 0.001 for failure to demonstrate non-inferiority), respectively. AD results had a high 91% negative predictive value for the presence of significant CAD. AD testing failed to demonstrate non-inferior diagnostic accuracy as compared to the historical performance of a nuclear stress OPC due to low specificity. AD sensitivity was non-inferior in detecting significant CAD with a high negative predictive value supporting a potential value in excluding CAD.
WE-E-217A-02: Methodologies for Evaluation of Standalone CAD System Performance.
Sahiner, B
2012-06-01
Standalone performance evaluation of a CAD system provides information about the abnormality detection or classification performance of the computerized system alone. Although the performance of the reader with CAD is the final step in CAD system assessment, standalone performance evaluation is an important component for several reasons: First, standalone evaluation informs the reader about the performance level of the CAD system and may have an impact on how the reader uses the system. Second, it provides essential information to the system designer for algorithm optimization during system development. Third, standalone evaluation can provide a detailed description of algorithm performance (e.g., on subgroups of the population) because a larger data set with more samples from different subgroups can be included in standalone studies compared to reader studies. Proper standalone evaluation of a CAD system involves a number of key components, some of which are shared with the assessment of reader performance with CAD. These include (1) selection of a test data set that allows performance assessment with little or no bias and acceptable uncertainty; (2) a reference standard that indicates disease status as well as the location and extent of disease; (3) a clearly defined method for labeling each CAD mark as a true-positive or false-positive; and (4) a properly selected set of metrics to summarize the accuracy of the computer marks and their corresponding scores. In this lecture, we will discuss various approaches for the key components of standalone CAD performance evaluation listed above, and present some of the recommendations and opinions from the AAPM CAD subcommittee on these issues. Learning Objectives 1. Identify basic components and metrics in the assessment of standalone CAD systems 2. Understand how each component may affect the assessed performance 3. Learn about AAPM CAD subcommittee's opinions and recommendations on factors and metrics related to the evaluation of standalone CAD system performance. © 2012 American Association of Physicists in Medicine.
A survey on computer aided diagnosis for ocular diseases
2014-01-01
Background Computer Aided Diagnosis (CAD), which can automate the detection process for ocular diseases, has attracted extensive attention from clinicians and researchers alike. It not only alleviates the burden on the clinicians by providing objective opinion with valuable insights, but also offers early detection and easy access for patients. Method We review ocular CAD methodologies for various data types. For each data type, we investigate the databases and the algorithms to detect different ocular diseases. Their advantages and shortcomings are analyzed and discussed. Result We have studied three types of data (i.e., clinical, genetic and imaging) that have been commonly used in existing methods for CAD. The recent developments in methods used in CAD of ocular diseases (such as Diabetic Retinopathy, Glaucoma, Age-related Macular Degeneration and Pathological Myopia) are investigated and summarized comprehensively. Conclusion While CAD for ocular diseases has shown considerable progress over the past years, the clinical importance of fully automatic CAD systems which are able to embed clinical knowledge and integrate heterogeneous data sources still show great potential for future breakthrough. PMID:25175552
Paquerault, Sophie; Hardy, Paul T; Wersto, Nancy; Chen, John; Smith, Robert C
2010-09-01
The aim of this study was to explore different computerized models (the "machine") as a means to achieve optimal use of computer-aided detection (CAD) systems and to investigate whether these models can play a primary role in clinical decision making and possibly replace a clinician's subjective decision for combining his or her own assessment with that provided by a CAD system. Data previously collected from a fully crossed, multiple-reader, multiple-case observer study with and without CAD by seven observers asked to identify simulated small masses on two separate sets of 100 mammographic images (low-contrast and high-contrast sets; ie, low-contrast and high-contrast simulated masses added to random locations on normal mammograms) were used. This allowed testing two relative sensitivities between the observers and CAD. Seven models that combined detection assessments from CAD standalone, unaided read, and CAD-aided read (second read and concurrent read) were developed using the leave-one-out technique for training and testing. These models were personalized for each observer. Detection performance accuracies were analyzed using the area under a portion of the free-response receiver-operating characteristic curve (AUFC), sensitivity, and number of false-positives per image. For the low-contrast set, the use of computerized models resulted in significantly higher AUFCs compared to the unaided read mode for all readers, whereas the increased AUFCs between CAD-aided (second and concurrent reads; ie, decisions made by the readers) and unaided read modes were statistically significant for a majority, but not all, of the readers (four and five of the seven readers, respectively). For the high-contrast set, there were no significant trends in the AUFCs whether or not a model was used to combine the original reading modes. Similar results were observed when using sensitivity as the figure of merit. However, the average number of false-positives per image resulting from the computerized models remained the same as that obtained from the unaided read modes. Individual computerized models (the machine) that combine image assessments from CAD standalone, unaided read, and CAD-aided read can increase detection performance compared to the reading done by the observer. However, relative sensitivity (ie, the difference in sensitivity between CAD standalone and unaided read) was a critical factor that determined incremental improvement in decision making, whether made by the observer or using computerized models. Published by Elsevier Inc.
Deep neural network-based computer-assisted detection of cerebral aneurysms in MR angiography.
Nakao, Takahiro; Hanaoka, Shouhei; Nomura, Yukihiro; Sato, Issei; Nemoto, Mitsutaka; Miki, Soichiro; Maeda, Eriko; Yoshikawa, Takeharu; Hayashi, Naoto; Abe, Osamu
2018-04-01
The usefulness of computer-assisted detection (CAD) for detecting cerebral aneurysms has been reported; therefore, the improved performance of CAD will help to detect cerebral aneurysms. To develop a CAD system for intracranial aneurysms on unenhanced magnetic resonance angiography (MRA) images based on a deep convolutional neural network (CNN) and a maximum intensity projection (MIP) algorithm, and to demonstrate the usefulness of the system by training and evaluating it using a large dataset. Retrospective study. There were 450 cases with intracranial aneurysms. The diagnoses of brain aneurysms were made on the basis of MRA, which was performed as part of a brain screening program. Noncontrast-enhanced 3D time-of-flight (TOF) MRA on 3T MR scanners. In our CAD, we used a CNN classifier that predicts whether each voxel is inside or outside aneurysms by inputting MIP images generated from a volume of interest (VOI) around the voxel. The CNN was trained in advance using manually inputted labels. We evaluated our method using 450 cases with intracranial aneurysms, 300 of which were used for training, 50 for parameter tuning, and 100 for the final evaluation. Free-response receiver operating characteristic (FROC) analysis. Our CAD system detected 94.2% (98/104) of aneurysms with 2.9 false positives per case (FPs/case). At a sensitivity of 70%, the number of FPs/case was 0.26. We showed that the combination of a CNN and an MIP algorithm is useful for the detection of intracranial aneurysms. 4 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2018;47:948-953. © 2017 International Society for Magnetic Resonance in Medicine.
B-Spline Filtering for Automatic Detection of Calcification Lesions in Mammograms
NASA Astrophysics Data System (ADS)
Bueno, G.; Sánchez, S.; Ruiz, M.
2006-10-01
Breast cancer continues to be an important health problem between women population. Early detection is the only way to improve breast cancer prognosis and significantly reduce women mortality. It is by using CAD systems that radiologist can improve their ability to detect, and classify lesions in mammograms. In this study the usefulness of using B-spline based on a gradient scheme and compared to wavelet and adaptative filtering has been investigated for calcification lesion detection and as part of CAD systems. The technique has been applied to different density tissues. A qualitative validation shows the success of the method.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bueno, G.; Ruiz, M.; Sanchez, S
Breast cancer continues to be an important health problem between women population. Early detection is the only way to improve breast cancer prognosis and significantly reduce women mortality. It is by using CAD systems that radiologist can improve their ability to detect, and classify lesions in mammograms. In this study the usefulness of using B-spline based on a gradient scheme and compared to wavelet and adaptative filtering has been investigated for calcification lesion detection and as part of CAD systems. The technique has been applied to different density tissues. A qualitative validation shows the success of the method.
Chan, Heang-Ping; Hadjiiski, Lubomir; Helvie, Mark A.; Wei, Jun; Cha, Kenny
2016-01-01
Purpose: Develop a computer-aided detection (CAD) system for masses in digital breast tomosynthesis (DBT) volume using a deep convolutional neural network (DCNN) with transfer learning from mammograms. Methods: A data set containing 2282 digitized film and digital mammograms and 324 DBT volumes were collected with IRB approval. The mass of interest on the images was marked by an experienced breast radiologist as reference standard. The data set was partitioned into a training set (2282 mammograms with 2461 masses and 230 DBT views with 228 masses) and an independent test set (94 DBT views with 89 masses). For DCNN training, the region of interest (ROI) containing the mass (true positive) was extracted from each image. False positive (FP) ROIs were identified at prescreening by their previously developed CAD systems. After data augmentation, a total of 45 072 mammographic ROIs and 37 450 DBT ROIs were obtained. Data normalization and reduction of non-uniformity in the ROIs across heterogeneous data was achieved using a background correction method applied to each ROI. A DCNN with four convolutional layers and three fully connected (FC) layers was first trained on the mammography data. Jittering and dropout techniques were used to reduce overfitting. After training with the mammographic ROIs, all weights in the first three convolutional layers were frozen, and only the last convolution layer and the FC layers were randomly initialized again and trained using the DBT training ROIs. The authors compared the performances of two CAD systems for mass detection in DBT: one used the DCNN-based approach and the other used their previously developed feature-based approach for FP reduction. The prescreening stage was identical in both systems, passing the same set of mass candidates to the FP reduction stage. For the feature-based CAD system, 3D clustering and active contour method was used for segmentation; morphological, gray level, and texture features were extracted and merged with a linear discriminant classifier to score the detected masses. For the DCNN-based CAD system, ROIs from five consecutive slices centered at each candidate were passed through the trained DCNN and a mass likelihood score was generated. The performances of the CAD systems were evaluated using free-response ROC curves and the performance difference was analyzed using a non-parametric method. Results: Before transfer learning, the DCNN trained only on mammograms with an AUC of 0.99 classified DBT masses with an AUC of 0.81 in the DBT training set. After transfer learning with DBT, the AUC improved to 0.90. For breast-based CAD detection in the test set, the sensitivity for the feature-based and the DCNN-based CAD systems was 83% and 91%, respectively, at 1 FP/DBT volume. The difference between the performances for the two systems was statistically significant (p-value < 0.05). Conclusions: The image patterns learned from the mammograms were transferred to the mass detection on DBT slices through the DCNN. This study demonstrated that large data sets collected from mammography are useful for developing new CAD systems for DBT, alleviating the problem and effort of collecting entirely new large data sets for the new modality. PMID:27908154
Computer aided detection of clusters of microcalcifications on full field digital mammograms
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ge Jun; Sahiner, Berkman; Hadjiiski, Lubomir M.
2006-08-15
We are developing a computer-aided detection (CAD) system to identify microcalcification clusters (MCCs) automatically on full field digital mammograms (FFDMs). The CAD system includes six stages: preprocessing; image enhancement; segmentation of microcalcification candidates; false positive (FP) reduction for individual microcalcifications; regional clustering; and FP reduction for clustered microcalcifications. At the stage of FP reduction for individual microcalcifications, a truncated sum-of-squares error function was used to improve the efficiency and robustness of the training of an artificial neural network in our CAD system for FFDMs. At the stage of FP reduction for clustered microcalcifications, morphological features and features derived from themore » artificial neural network outputs were extracted from each cluster. Stepwise linear discriminant analysis (LDA) was used to select the features. An LDA classifier was then used to differentiate clustered microcalcifications from FPs. A data set of 96 cases with 192 images was collected at the University of Michigan. This data set contained 96 MCCs, of which 28 clusters were proven by biopsy to be malignant and 68 were proven to be benign. The data set was separated into two independent data sets for training and testing of the CAD system in a cross-validation scheme. When one data set was used to train and validate the convolution neural network (CNN) in our CAD system, the other data set was used to evaluate the detection performance. With the use of a truncated error metric, the training of CNN could be accelerated and the classification performance was improved. The CNN in combination with an LDA classifier could substantially reduce FPs with a small tradeoff in sensitivity. By using the free-response receiver operating characteristic methodology, it was found that our CAD system can achieve a cluster-based sensitivity of 70, 80, and 90 % at 0.21, 0.61, and 1.49 FPs/image, respectively. For case-based performance evaluation, a sensitivity of 70, 80, and 90 % can be achieved at 0.07, 0.17, and 0.65 FPs/image, respectively. We also used a data set of 216 mammograms negative for clustered microcalcifications to further estimate the FP rate of our CAD system. The corresponding FP rates were 0.15, 0.31, and 0.86 FPs/image for cluster-based detection when negative mammograms were used for estimation of FP rates.« less
NASA Astrophysics Data System (ADS)
Litjens, G. J. S.; Barentsz, J. O.; Karssemeijer, N.; Huisman, H. J.
2012-03-01
MRI has shown to have great potential in prostate cancer localization and grading, but interpreting those exams requires expertise that is not widely available. Therefore, CAD applications are being developed to aid radiologists in detecting prostate cancer. Existing CAD applications focus on the prostate as a whole. However, in clinical practice transition zone cancer and peripheral zone cancer are considered to have different appearances. In this paper we present zone-specific CAD, in addition to an atlas based segmentation technique which includes zonal segmentation. Our CAD system consists of a detection and a classification stage. Prior to the detection stage the prostate is segmented into two zones. After segmentation features are extracted. Subsequently a likelihood map is generated on which local maxima detection is performed. For each local maximum a region is segmented. In the classification stage additional shape features are calculated, after which the regions are classified. Validation was performed on 288 data sets with MR-guided biopsy results as ground truth. Freeresponse Receiver Operating Characteristic (FROC) analysis was used for statistical evaluation. The difference between whole-prostate and zone-specific CAD was assessed using the difference between the FROCs. Our results show that evaluating the two zones separately results in an increase in performance compared to whole-prostate CAD. The FROC curves at .1, 1 and 3 false positives have a sensitivity of 0.0, 0.55 and 0.72 for whole-prostate and 0.08, 0.57 and 0.80 for zone-specific CAD. The FROC curve of the zone-specific CAD also showed significantly better performance overall (p < 0.05).
DOE Office of Scientific and Technical Information (OSTI.GOV)
Setio, Arnaud A. A., E-mail: arnaud.arindraadiyoso@radboudumc.nl; Jacobs, Colin; Gelderblom, Jaap
Purpose: Current computer-aided detection (CAD) systems for pulmonary nodules in computed tomography (CT) scans have a good performance for relatively small nodules, but often fail to detect the much rarer larger nodules, which are more likely to be cancerous. We present a novel CAD system specifically designed to detect solid nodules larger than 10 mm. Methods: The proposed detection pipeline is initiated by a three-dimensional lung segmentation algorithm optimized to include large nodules attached to the pleural wall via morphological processing. An additional preprocessing is used to mask out structures outside the pleural space to ensure that pleural and parenchymalmore » nodules have a similar appearance. Next, nodule candidates are obtained via a multistage process of thresholding and morphological operations, to detect both larger and smaller candidates. After segmenting each candidate, a set of 24 features based on intensity, shape, blobness, and spatial context are computed. A radial basis support vector machine (SVM) classifier was used to classify nodule candidates, and performance was evaluated using ten-fold cross-validation on the full publicly available lung image database consortium database. Results: The proposed CAD system reaches a sensitivity of 98.3% (234/238) and 94.1% (224/238) large nodules at an average of 4.0 and 1.0 false positives/scan, respectively. Conclusions: The authors conclude that the proposed dedicated CAD system for large pulmonary nodules can identify the vast majority of highly suspicious lesions in thoracic CT scans with a small number of false positives.« less
NASA Astrophysics Data System (ADS)
Deshpande, Ruchi R.; Fernandez, James; Lee, Joon K.; Chan, Tao; Liu, Brent J.; Huang, H. K.
2010-03-01
Timely detection of Acute Intra-cranial Hemorrhage (AIH) in an emergency environment is essential for the triage of patients suffering from Traumatic Brain Injury. Moreover, the small size of lesions and lack of experience on the reader's part could lead to difficulties in the detection of AIH. A CT based CAD algorithm for the detection of AIH has been developed in order to improve upon the current standard of identification and treatment of AIH. A retrospective analysis of the algorithm has already been carried out with 135 AIH CT studies with 135 matched normal head CT studies from the Los Angeles County General Hospital/ University of Southern California Hospital System (LAC/USC). In the next step, AIH studies have been collected from Walter Reed Army Medical Center, and are currently being processed using the AIH CAD system as part of implementing a multi-site assessment and evaluation of the performance of the algorithm. The sensitivity and specificity numbers from the Walter Reed study will be compared with the numbers from the LAC/USC study to determine if there are differences in the presentation and detection due to the difference in the nature of trauma between the two sites. Simultaneously, a stand-alone system with a user friendly GUI has been developed to facilitate implementation in a clinical setting.
A deep-learning based automatic pulmonary nodule detection system
NASA Astrophysics Data System (ADS)
Zhao, Yiyuan; Zhao, Liang; Yan, Zhennan; Wolf, Matthias; Zhan, Yiqiang
2018-02-01
Lung cancer is the deadliest cancer worldwide. Early detection of lung cancer is a promising way to lower the risk of dying. Accurate pulmonary nodule detection in computed tomography (CT) images is crucial for early diagnosis of lung cancer. The development of computer-aided detection (CAD) system of pulmonary nodules contributes to making the CT analysis more accurate and with more efficiency. Recent studies from other groups have been focusing on lung cancer diagnosis CAD system by detecting medium to large nodules. However, to fully investigate the relevance between nodule features and cancer diagnosis, a CAD that is capable of detecting nodules with all sizes is needed. In this paper, we present a deep-learning based automatic all size pulmonary nodule detection system by cascading two artificial neural networks. We firstly use a U-net like 3D network to generate nodule candidates from CT images. Then, we use another 3D neural network to refine the locations of the nodule candidates generated from the previous subsystem. With the second sub-system, we bring the nodule candidates closer to the center of the ground truth nodule locations. We evaluate our system on a public CT dataset provided by the Lung Nodule Analysis (LUNA) 2016 grand challenge. The performance on the testing dataset shows that our system achieves 90% sensitivity with an average of 4 false positives per scan. This indicates that our system can be an aid for automatic nodule detection, which is beneficial for lung cancer diagnosis.
Tiouririne, Mohamed; Dixon, Adam J; Mauldin, F William; Scalzo, David; Krishnaraj, Arun
2017-08-01
The aim of this study was to evaluate the imaging performance of a handheld ultrasound system and the accuracy of an automated lumbar spine computer-aided detection (CAD) algorithm in the spines of human subjects. This study was approved by the institutional review board of the University of Virginia. The authors designed a handheld ultrasound system with enhanced bone image quality and fully automated CAD of lumbar spine anatomy. The imaging performance was evaluated by imaging the lumbar spines of 68 volunteers with body mass index between 18.5 and 48 kg/m. The accuracy, sensitivity, and specificity of the lumbar spine CAD algorithm were assessed by comparing the algorithm's results to ground-truth segmentations of neuraxial anatomy provided by radiologists. The lumbar spine CAD algorithm detected the epidural space with a sensitivity of 94.2% (95% confidence interval [CI], 85.1%-98.1%) and a specificity of 85.5% (95% CI, 81.7%-88.6%) and measured its depth with an error of approximately ±0.5 cm compared with measurements obtained manually from the 2-dimensional ultrasound images. The spine midline was detected with a sensitivity of 93.9% (95% CI, 85.8%-97.7%) and specificity of 91.3% (95% CI, 83.6%-96.9%), and its lateral position within the ultrasound image was measured with an error of approximately ±0.3 cm. The bone enhancement imaging mode produced images with 5.1- to 10-fold enhanced bone contrast when compared with a comparable handheld ultrasound imaging system. The results of this study demonstrate the feasibility of CAD for assisting with real-time interpretation of ultrasound images of the lumbar spine at the bedside.
Jiang, Yulei; Inciardi, Marc F; Edwards, Alexandra V; Papaioannou, John
2018-05-24
The purpose of this study was to compare diagnostic accuracy and interpretation time of screening automated breast ultrasound (ABUS) for women with dense breast tissue without and with use of a recently U.S. Food and Drug Administration-approved computer-aided detection (CAD) system for concurrent read. In a retrospective observer performance study, 18 radiologists interpreted a cancer-enriched set (i.e., cancer prevalence higher than in the original screening cohort) of 185 screening ABUS studies (52 with and 133 without breast cancer). These studies were from a large cohort of ABUS screened patients interpreted as BI-RADS density C or D. Each reader interpreted each case twice in a counterbalanced study, once without the CAD system and once with it, separated by 4 weeks. For each case, each reader identified abnormal findings and reported BI-RADS assessment category and level of suspicion for breast cancer. Interpretation time was recorded. Level of suspicion data were compared to evaluate diagnostic accuracy by means of the Dorfman-Berbaum-Metz method of jackknife with ANOVA ROC analysis. Interpretation times were compared by ANOVA. The ROC AUC was 0.848 with the CAD system, compared with 0.828 without it, for a difference of 0.020 (95% CI, -0.011 to 0.051) and was statistically noninferior to the AUC without the CAD system with respect to a margin of -0.05 (p = 0.000086). The mean interpretation time was 3 minutes 33 seconds per case without the CAD system and 2 minutes 24 seconds with it, for a difference of 1 minute 9 seconds saved (95% CI, 44-93 seconds; p = 0.000014), or a reduction in interpretation time to 67% of the time without the CAD system. Use of the concurrent-read CAD system for interpretation of screening ABUS studies of women with dense breast tissue who do not have symptoms is expected to make interpretation significantly faster and produce noninferior diagnostic accuracy compared with interpretation without the CAD system.
Acharya, U Rajendra; Sree, S Vinitha; Krishnan, M Muthu Rama; Molinari, Filippo; Zieleźnik, Witold; Bardales, Ricardo H; Witkowska, Agnieszka; Suri, Jasjit S
2014-02-01
Computer-aided diagnostic (CAD) techniques aid physicians in better diagnosis of diseases by extracting objective and accurate diagnostic information from medical data. Hashimoto thyroiditis is the most common type of inflammation of the thyroid gland. The inflammation changes the structure of the thyroid tissue, and these changes are reflected as echogenic changes on ultrasound images. In this work, we propose a novel CAD system (a class of systems called ThyroScan) that extracts textural features from a thyroid sonogram and uses them to aid in the detection of Hashimoto thyroiditis. In this paradigm, we extracted grayscale features based on stationary wavelet transform from 232 normal and 294 Hashimoto thyroiditis-affected thyroid ultrasound images obtained from a Polish population. Significant features were selected using a Student t test. The resulting feature vectors were used to build and evaluate the following 4 classifiers using a 10-fold stratified cross-validation technique: support vector machine, decision tree, fuzzy classifier, and K-nearest neighbor. Using 7 significant features that characterized the textural changes in the images, the fuzzy classifier had the highest classification accuracy of 84.6%, sensitivity of 82.8%, specificity of 87.0%, and a positive predictive value of 88.9%. The proposed ThyroScan CAD system uses novel features to noninvasively detect the presence of Hashimoto thyroiditis on ultrasound images. Compared to manual interpretations of ultrasound images, the CAD system offers a more objective interpretation of the nature of the thyroid. The preliminary results presented in this work indicate the possibility of using such a CAD system in a clinical setting after evaluating it with larger databases in multicenter clinical trials.
2011-01-01
Background Single reading with computer aided detection (CAD) is an alternative to double reading for detecting cancer in screening mammograms. The aim of this study is to investigate whether the use of a single reader with CAD is more cost-effective than double reading. Methods Based on data from the CADET II study, the cost-effectiveness of single reading with CAD versus double reading was measured in terms of cost per cancer detected. Cost (Pound (£), year 2007/08) of single reading with CAD versus double reading was estimated assuming a health and social service perspective and a 7 year time horizon. As the equipment cost varies according to the unit size a separate analysis was conducted for high, average and low volume screening units. One-way sensitivity analyses were performed by varying the reading time, equipment and assessment cost, recall rate and reader qualification. Results CAD is cost increasing for all sizes of screening unit. The introduction of CAD is cost-increasing compared to double reading because the cost of CAD equipment, staff training and the higher assessment cost associated with CAD are greater than the saving in reading costs. The introduction of single reading with CAD, in place of double reading, would produce an additional cost of £227 and £253 per 1,000 women screened in high and average volume units respectively. In low volume screening units, the high cost of purchasing the equipment will results in an additional cost of £590 per 1,000 women screened. One-way sensitivity analysis showed that the factors having the greatest effect on the cost-effectiveness of CAD with single reading compared with double reading were the reading time and the reader's professional qualification (radiologist versus advanced practitioner). Conclusions Without improvements in CAD effectiveness (e.g. a decrease in the recall rate) CAD is unlikely to be a cost effective alternative to double reading for mammography screening in UK. This study provides updated estimates of CAD costs in a full-field digital system and assessment cost for women who are re-called after initial screening. However, the model is highly sensitive to various parameters e.g. reading time, reader qualification, and equipment cost. PMID:21241473
An interactive system for computer-aided diagnosis of breast masses.
Wang, Xingwei; Li, Lihua; Liu, Wei; Xu, Weidong; Lederman, Dror; Zheng, Bin
2012-10-01
Although mammography is the only clinically accepted imaging modality for screening the general population to detect breast cancer, interpreting mammograms is difficult with lower sensitivity and specificity. To provide radiologists "a visual aid" in interpreting mammograms, we developed and tested an interactive system for computer-aided detection and diagnosis (CAD) of mass-like cancers. Using this system, an observer can view CAD-cued mass regions depicted on one image and then query any suspicious regions (either cued or not cued by CAD). CAD scheme automatically segments the suspicious region or accepts manually defined region and computes a set of image features. Using content-based image retrieval (CBIR) algorithm, CAD searches for a set of reference images depicting "abnormalities" similar to the queried region. Based on image retrieval results and a decision algorithm, a classification score is assigned to the queried region. In this study, a reference database with 1,800 malignant mass regions and 1,800 benign and CAD-generated false-positive regions was used. A modified CBIR algorithm with a new function of stretching the attributes in the multi-dimensional space and decision scheme was optimized using a genetic algorithm. Using a leave-one-out testing method to classify suspicious mass regions, we compared the classification performance using two CBIR algorithms with either equally weighted or optimally stretched attributes. Using the modified CBIR algorithm, the area under receiver operating characteristic curve was significantly increased from 0.865 ± 0.006 to 0.897 ± 0.005 (p < 0.001). This study demonstrated the feasibility of developing an interactive CAD system with a large reference database and achieving improved performance.
Colonic polyps: application value of computer-aided detection in computed tomographic colonography.
Zhang, Hui-Mao; Guo, Wei; Liu, Gui-Feng; An, Dong-Hong; Gao, Shuo-Hui; Sun, Li-Bo; Yang, Hai-Shan
2011-02-01
Colonic polyps are frequently encountered in clinics. Computed tomographic colonography (CTC), as a painless and quick detection, has high values in clinics. In this study, we evaluated the application value of computer-aided detection (CAD) in CTC detection of colonic polyps in the Chinese population. CTC was performed with a GE 64-row multidetector computed tomography (MDCT) scanner. Data of 50 CTC patients (39 patients positive for at least one polyp of ≥ 0.5 cm in size and the other 11 patients negative by endoscopic detection) were retrospectively reviewed first without computer-aided detection (CAD) and then with CAD by four radiologists (two were experienced and another two inexperienced) blinded to colonoscopy findings. The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of detected colonic polyps, as well as the areas under the ROC curves (Az value) with and without CAD were calculated. CAD increased the overall sensitivity, specificity, positive predictive value, negative predictive value and accuracy of the colonic polyps detected by experienced and inexperienced readers. The sensitivity in detecting small polyps (5 - 9 mm) with CAD in experienced and inexperienced readers increased from 82% and 44% to 93% and 82%, respectively (P > 0.05 and P < 0.001). With the use of CAD, the overall false positive rate and false negative rate for the detection of polyps by experienced and inexperienced readers decreased in different degrees. Among 13 sessile polyps not detected by CAD, two were ≥ 1.0 cm, eleven were 5 - 9 mm in diameter, and nine were flat-shaped lesions. The application of CAD in combination with CTC can increase the ability to detect colonic polyps, particularly for inexperienced readers. However, CAD is of limited value for the detection of flat polyps.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Linguraru, Marius George; Panjwani, Neil; Fletcher, Joel G.
2011-12-15
Purpose: To evaluate the performance of a computer-aided detection (CAD) system for detecting colonic polyps at noncathartic computed tomography colonography (CTC) in conjunction with an automated image-based colon cleansing algorithm. Methods: An automated colon cleansing algorithm was designed to detect and subtract tagged-stool, accounting for heterogeneity and poor tagging, to be used in conjunction with a colon CAD system. The method is locally adaptive and combines intensity, shape, and texture analysis with probabilistic optimization. CTC data from cathartic-free bowel preparation were acquired for testing and training the parameters. Patients underwent various colonic preparations with barium or Gastroview in divided dosesmore » over 48 h before scanning. No laxatives were administered and no dietary modifications were required. Cases were selected from a polyp-enriched cohort and included scans in which at least 90% of the solid stool was visually estimated to be tagged and each colonic segment was distended in either the prone or supine view. The CAD system was run comparatively with and without the stool subtraction algorithm. Results: The dataset comprised 38 CTC scans from prone and/or supine scans of 19 patients containing 44 polyps larger than 10 mm (22 unique polyps, if matched between prone and supine scans). The results are robust on fine details around folds, thin-stool linings on the colonic wall, near polyps and in large fluid/stool pools. The sensitivity of the CAD system is 70.5% per polyp at a rate of 5.75 false positives/scan without using the stool subtraction module. This detection improved significantly (p = 0.009) after automated colon cleansing on cathartic-free data to 86.4% true positive rate at 5.75 false positives/scan. Conclusions: An automated image-based colon cleansing algorithm designed to overcome the challenges of the noncathartic colon significantly improves the sensitivity of colon CAD by approximately 15%.« less
Henriksen, Emilie L; Carlsen, Jonathan F; Vejborg, Ilse Mm; Nielsen, Michael B; Lauridsen, Carsten A
2018-01-01
Background Early detection of breast cancer (BC) is crucial in lowering the mortality. Purpose To present an overview of studies concerning computer-aided detection (CAD) in screening mammography for early detection of BC and compare diagnostic accuracy and recall rates (RR) of single reading (SR) with SR + CAD and double reading (DR) with SR + CAD. Material and Methods PRISMA guidelines were used as a review protocol. Articles on clinical trials concerning CAD for detection of BC in a screening population were included. The literature search resulted in 1522 records. A total of 1491 records were excluded by abstract and 18 were excluded by full text reading. A total of 13 articles were included. Results All but two studies from the SR vs. SR + CAD group showed an increased sensitivity and/or cancer detection rate (CDR) when adding CAD. The DR vs. SR + CAD group showed no significant differences in sensitivity and CDR. Adding CAD to SR increased the RR and decreased the specificity in all but one study. For the DR vs. SR + CAD group only one study reported a significant difference in RR. Conclusion All but two studies showed an increase in RR, sensitivity and CDR when adding CAD to SR. Compared to DR no statistically significant differences in sensitivity or CDR were reported. Additional studies based on organized population-based screening programs, with longer follow-up time, high-volume readers, and digital mammography are needed to evaluate the efficacy of CAD.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Masotti, Matteo; Lanconelli, Nico; Campanini, Renato
In this work, gray-scale invariant ranklet texture features are proposed for false positive reduction (FPR) in computer-aided detection (CAD) of breast masses. Two main considerations are at the basis of this proposal. First, false positive (FP) marks surviving our previous CAD system seem to be characterized by specific texture properties that can be used to discriminate them from masses. Second, our previous CAD system achieves invariance to linear/nonlinear monotonic gray-scale transformations by encoding regions of interest into ranklet images through the ranklet transform, an image transformation similar to the wavelet transform, yet dealing with pixels' ranks rather than with theirmore » gray-scale values. Therefore, the new FPR approach proposed herein defines a set of texture features which are calculated directly from the ranklet images corresponding to the regions of interest surviving our previous CAD system, hence, ranklet texture features; then, a support vector machine (SVM) classifier is used for discrimination. As a result of this approach, texture-based information is used to discriminate FP marks surviving our previous CAD system; at the same time, invariance to linear/nonlinear monotonic gray-scale transformations of the new CAD system is guaranteed, as ranklet texture features are calculated from ranklet images that have this property themselves by construction. To emphasize the gray-scale invariance of both the previous and new CAD systems, training and testing are carried out without any in-between parameters' adjustment on mammograms having different gray-scale dynamics; in particular, training is carried out on analog digitized mammograms taken from a publicly available digital database, whereas testing is performed on full-field digital mammograms taken from an in-house database. Free-response receiver operating characteristic (FROC) curve analysis of the two CAD systems demonstrates that the new approach achieves a higher reduction of FP marks when compared to the previous one. Specifically, at 60%, 65%, and 70% per-mammogram sensitivity, the new CAD system achieves 0.50, 0.68, and 0.92 FP marks per mammogram, whereas at 70%, 75%, and 80% per-case sensitivity it achieves 0.37, 0.48, and 0.71 FP marks per mammogram, respectively. Conversely, at the same sensitivities, the previous CAD system reached 0.71, 0.87, and 1.15 FP marks per mammogram, and 0.57, 0.73, and 0.92 FPs per mammogram. Also, statistical significance of the difference between the two per-mammogram and per-case FROC curves is demonstrated by the p-value<0.001 returned by jackknife FROC analysis performed on the two CAD systems.« less
Diagnostic performance of an acoustic-based system for coronary artery disease risk stratification.
Winther, Simon; Nissen, Louise; Schmidt, Samuel Emil; Westra, Jelmer Sybren; Rasmussen, Laust Dupont; Knudsen, Lars Lyhne; Madsen, Lene Helleskov; Kirk Johansen, Jane; Larsen, Bjarke Skogstad; Struijk, Johannes Jan; Frost, Lars; Holm, Niels Ramsing; Christiansen, Evald Høj; Botker, Hans Erik; Bøttcher, Morten
2018-06-01
Diagnosing coronary artery disease (CAD) continues to require substantial healthcare resources. Acoustic analysis of transcutaneous heart sounds of cardiac movement and intracoronary turbulence due to obstructive coronary disease could potentially change this. The aim of this study was thus to test the diagnostic accuracy of a new portable acoustic device for detection of CAD. We included 1675 patients consecutively with low to intermediate likelihood of CAD who had been referred for cardiac CT angiography. If significant obstruction was suspected in any coronary segment, patients were referred to invasive angiography and fractional flow reserve (FFR) assessment. Heart sound analysis was performed in all patients. A predefined acoustic CAD-score algorithm was evaluated; subsequently, we developed and validated an updated CAD-score algorithm that included both acoustic features and clinical risk factors. Low risk is indicated by a CAD-score value ≤20. Haemodynamically significant CAD assessed from FFR was present in 145 (10.0%) patients. In the entire cohort, the predefined CAD-score had a sensitivity of 63% and a specificity of 44%. In total, 50% had an updated CAD-score value ≤20. At this cut-off, sensitivity was 81% (95% CI 73% to 87%), specificity 53% (95% CI 50% to 56%), positive predictive value 16% (95% CI 13% to 18%) and negative predictive value 96% (95% CI 95% to 98%) for diagnosing haemodynamically significant CAD. Sound-based detection of CAD enables risk stratification superior to clinical risk scores. With a negative predictive value of 96%, this new acoustic rule-out system could potentially supplement clinical assessment to guide decisions on the need for further diagnostic investigation. ClinicalTrials.gov identifier NCT02264717; Results. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.
Tartar, A; Akan, A; Kilic, N
2014-01-01
Computer-aided detection systems can help radiologists to detect pulmonary nodules at an early stage. In this paper, a novel Computer-Aided Diagnosis system (CAD) is proposed for the classification of pulmonary nodules as malignant and benign. The proposed CAD system using ensemble learning classifiers, provides an important support to radiologists at the diagnosis process of the disease, achieves high classification performance. The proposed approach with bagging classifier results in 94.7 %, 90.0 % and 77.8 % classification sensitivities for benign, malignant and undetermined classes (89.5 % accuracy), respectively.
Detection of benign prostatic hyperplasia nodules in T2W MR images using fuzzy decision forest
NASA Astrophysics Data System (ADS)
Lay, Nathan; Freeman, Sabrina; Turkbey, Baris; Summers, Ronald M.
2016-03-01
Prostate cancer is the second leading cause of cancer-related death in men MRI has proven useful for detecting prostate cancer, and CAD may further improve detection. One source of false positives in prostate computer-aided diagnosis (CAD) is the presence of benign prostatic hyperplasia (BPH) nodules. These nodules have a distinct appearance with a pseudo-capsule on T2 weighted MR images but can also resemble cancerous lesions in other sequences such as the ADC or high B-value images. Describing their appearance with hand-crafted heuristics (features) that also exclude the appearance of cancerous lesions is challenging. This work develops a method based on fuzzy decision forests to automatically learn discriminative features for the purpose of BPH nodule detection in T2 weighted images for the purpose of improving prostate CAD systems.
Detection of breast cancer with full-field digital mammography and computer-aided detection.
The, Juliette S; Schilling, Kathy J; Hoffmeister, Jeffrey W; Friedmann, Euvondia; McGinnis, Ryan; Holcomb, Richard G
2009-02-01
The purpose of this study was to evaluate computer-aided detection (CAD) performance with full-field digital mammography (FFDM). CAD (Second Look, version 7.2) was used to evaluate 123 cases of breast cancer detected with FFDM (Senographe DS). Retrospectively, CAD sensitivity was assessed using breast density, mammographic presentation, histopathology results, and lesion size. To determine the case-based false-positive rate, patients with four standard views per case were included in the study group. Eighteen unilateral mammography examinations with nonstandard views were excluded, resulting in a sample of 105 bilateral cases. CAD detected 115 (94%) of 123 cancer cases: six of six (100%) in fatty breasts, 63 of 66 (95%) in breasts containing scattered fibroglandular densities, 43 of 46 (93%) in heterogeneously dense breasts, and three of five (60%) in extremely dense breasts. CAD detected 93% (41/44) of cancers manifesting as calcifications, 92% (57/62) as masses, and 100% (17/17) as mixed masses and calcifications. CAD detected 94% of the invasive ductal carcinomas (n = 63), 100% of the invasive lobular carcinomas (n = 7), 91% of the other invasive carcinomas (n = 11), and 93% of the ductal carcinomas in situ (n = 42). CAD sensitivity for cancers 1-10 mm (n = 55) was 89%; 11-20 mm (n = 37), 97%; 21-30 mm (n = 16), 100%; and larger than 30 mm (n = 15), 93%. The CAD false-positive rate was 2.3 marks per four-image case. CAD with FFDM showed a high sensitivity in identifying cancers manifesting as calcifications and masses. Sensitivity was maintained in cancers with lower mammographic sensitivity, including invasive lobular carcinomas and small neoplasms (1-20 mm). CAD with FFDM should be effective in assisting radiologists with earlier detection of breast cancer. Future studies are needed to assess CAD accuracy in larger populations.
Balleyguier, Corinne; Arfi-Rouche, Julia; Levy, Laurent; Toubiana, Patrick R; Cohen-Scali, Franck; Toledano, Alicia Y; Boyer, Bruno
2017-12-01
Evaluate concurrent Computer-Aided Detection (CAD) with Digital Breast Tomosynthesis (DBT) to determine impact on radiologist performance and reading time. The CAD system detects and extracts suspicious masses, architectural distortions and asymmetries from DBT planes that are blended into corresponding synthetic images to form CAD-enhanced synthetic images. Review of CAD-enhanced images and navigation to corresponding planes to confirm or dismiss potential lesions allows radiologists to more quickly review DBT planes. A retrospective, crossover study with and without CAD was conducted with six radiologists who read an enriched sample of 80 DBT cases including 23 malignant lesions in 21 women. Area Under the Receiver Operating Characteristic (ROC) Curve (AUC) compared the readings with and without CAD to determine the effect of CAD on overall interpretation performance. Sensitivity, specificity, recall rate and reading time were also assessed. Multi-reader, multi-case (MRMC) methods accounting for correlation and requiring correct lesion localization were used to analyze all endpoints. AUCs were based on a 0-100% probability of malignancy (POM) score. Sensitivity and specificity were based on BI-RADS scores, where 3 or higher was positive. Average AUC across readers without CAD was 0.854 (range: 0.785-0.891, 95% confidence interval (CI): 0.769,0.939) and 0.850 (range: 0.746-0.905, 95% CI: 0.751,0.949) with CAD (95% CI for difference: -0.046,0.039), demonstrating non-inferiority of AUC. Average reduction in reading time with CAD was 23.5% (95% CI: 7.0-37.0% improvement), from an average 48.2 (95% CI: 39.1,59.6) seconds without CAD to 39.1 (95% CI: 26.2,54.5) seconds with CAD. Per-patient sensitivity was the same with and without CAD (0.865; 95% CI for difference: -0.070,0.070), and there was a small 0.022 improvement (95% CI for difference: -0.046,0.089) in per-lesion sensitivity from 0.790 without CAD to 0.812 with CAD. A slight reduction in specificity with a -0.014 difference (95% CI for difference: -0.079,0.050) and a small 0.025 increase (95% CI for difference: -0.036,0.087) in recall rate in non-cancer cases were observed with CAD. Concurrent CAD resulted in faster reading time with non-inferiority of radiologist interpretation performance. Radiologist sensitivity, specificity and recall rate were similar with and without CAD. Copyright © 2017 Elsevier B.V. All rights reserved.
Yousefi, Mina; Krzyżak, Adam; Suen, Ching Y
2018-05-01
Digital breast tomosynthesis (DBT) was developed in the field of breast cancer screening as a new tomographic technique to minimize the limitations of conventional digital mammography breast screening methods. A computer-aided detection (CAD) framework for mass detection in DBT has been developed and is described in this paper. The proposed framework operates on a set of two-dimensional (2D) slices. With plane-to-plane analysis on corresponding 2D slices from each DBT, it automatically learns complex patterns of 2D slices through a deep convolutional neural network (DCNN). It then applies multiple instance learning (MIL) with a randomized trees approach to classify DBT images based on extracted information from 2D slices. This CAD framework was developed and evaluated using 5040 2D image slices derived from 87 DBT volumes. The empirical results demonstrate that this proposed CAD framework achieves much better performance than CAD systems that use hand-crafted features and deep cardinality-restricted Bolzmann machines to detect masses in DBTs. Copyright © 2018 Elsevier Ltd. All rights reserved.
The interplay of attention economics and computer-aided detection marks in screening mammography
NASA Astrophysics Data System (ADS)
Schwartz, Tayler M.; Sridharan, Radhika; Wei, Wei; Lukyanchenko, Olga; Geiser, William; Whitman, Gary J.; Haygood, Tamara Miner
2016-03-01
Introduction: According to attention economists, overabundant information leads to decreased attention for individual pieces of information. Computer-aided detection (CAD) alerts radiologists to findings potentially associated with breast cancer but is notorious for creating an abundance of false-positive marks. We suspected that increased CAD marks do not lengthen mammogram interpretation time, as radiologists will selectively disregard these marks when present in larger numbers. We explore the relevance of attention economics in mammography by examining how the number of CAD marks affects interpretation time. Methods: We performed a retrospective review of bilateral digital screening mammograms obtained between January 1, 2011 and February 28, 2014, using only weekend interpretations to decrease distractions and the likelihood of trainee participation. We stratified data according to reader and used ANOVA to assess the relationship between number of CAD marks and interpretation time. Results: Ten radiologists, with median experience after residency of 12.5 years (range 6 to 24,) interpreted 1849 mammograms. When accounting for number of images, Breast Imaging Reporting and Data System category, and breast density, increasing numbers of CAD marks was correlated with longer interpretation time only for the three radiologists with the fewest years of experience (median 7 years.) Conclusion: For the 7 most experienced readers, increasing CAD marks did not lengthen interpretation time. We surmise that as CAD marks increase, the attention given to individual marks decreases. Experienced radiologists may rapidly dismiss larger numbers of CAD marks as false-positive, having learned that devoting extra attention to such marks does not improve clinical detection.
Observer training for computer-aided detection of pulmonary nodules in chest radiography.
De Boo, Diederick W; van Hoorn, François; van Schuppen, Joost; Schijf, Laura; Scheerder, Maeke J; Freling, Nicole J; Mets, Onno; Weber, Michael; Schaefer-Prokop, Cornelia M
2012-08-01
To assess whether short-term feedback helps readers to increase their performance using computer-aided detection (CAD) for nodule detection in chest radiography. The 140 CXRs (56 with a solitary CT-proven nodules and 84 negative controls) were divided into four subsets of 35; each were read in a different order by six readers. Lesion presence, location and diagnostic confidence were scored without and with CAD (IQQA-Chest, EDDA Technology) as second reader. Readers received individual feedback after each subset. Sensitivity, specificity and area under the receiver-operating characteristics curve (AUC) were calculated for readings with and without CAD with respect to change over time and impact of CAD. CAD stand-alone sensitivity was 59 % with 1.9 false-positives per image. Mean AUC slightly increased over time with and without CAD (0.78 vs. 0.84 with and 0.76 vs. 0.82 without CAD) but differences did not reach significance. The sensitivity increased (65 % vs. 70 % and 66 % vs. 70 %) and specificity decreased over time (79 % vs. 74 % and 80 % vs. 77 %) but no significant impact of CAD was found. Short-term feedback does not increase the ability of readers to differentiate true- from false-positive candidate lesions and to use CAD more effectively. • Computer-aided detection (CAD) is increasingly used as an adjunct for many radiological techniques. • Short-term feedback does not improve reader performance with CAD in chest radiography. • Differentiation between true- and false-positive CAD for low conspicious possible lesions proves difficult. • CAD can potentially increase reader performance for nodule detection in chest radiography.
Increasing CAD system efficacy for lung texture analysis using a convolutional network
NASA Astrophysics Data System (ADS)
Tarando, Sebastian Roberto; Fetita, Catalin; Faccinetto, Alex; Brillet, Pierre-Yves
2016-03-01
The infiltrative lung diseases are a class of irreversible, non-neoplastic lung pathologies requiring regular follow-up with CT imaging. Quantifying the evolution of the patient status imposes the development of automated classification tools for lung texture. For the large majority of CAD systems, such classification relies on a two-dimensional analysis of axial CT images. In a previously developed CAD system, we proposed a fully-3D approach exploiting a multi-scale morphological analysis which showed good performance in detecting diseased areas, but with a major drawback consisting of sometimes overestimating the pathological areas and mixing different type of lung patterns. This paper proposes a combination of the existing CAD system with the classification outcome provided by a convolutional network, specifically tuned-up, in order to increase the specificity of the classification and the confidence to diagnosis. The advantage of using a deep learning approach is a better regularization of the classification output (because of a deeper insight into a given pathological class over a large series of samples) where the previous system is extra-sensitive due to the multi-scale response on patient-specific, localized patterns. In a preliminary evaluation, the combined approach was tested on a 10 patient database of various lung pathologies, showing a sharp increase of true detections.
Optimizing computer-aided colonic polyp detection for CT colonography by evolving the Pareto front1
Li, Jiang; Huang, Adam; Yao, Jack; Liu, Jiamin; Van Uitert, Robert L.; Petrick, Nicholas; Summers, Ronald M.
2009-01-01
A multiobjective genetic algorithm is designed to optimize a computer-aided detection (CAD) system for identifying colonic polyps. Colonic polyps appear as elliptical protrusions on the inner surface of the colon. Curvature-based features for colonic polyp detection have proved to be successful in several CT colonography (CTC) CAD systems. Our CTC CAD program uses a sequential classifier to form initial polyp detections on the colon surface. The classifier utilizes a set of thresholds on curvature-based features to cluster suspicious colon surface regions into polyp candidates. The thresholds were previously chosen experimentally by using feature histograms. The chosen thresholds were effective for detecting polyps sized 10 mm or larger in diameter. However, many medium-sized polyps, 6–9 mm in diameter, were missed in the initial detection procedure. In this paper, the task of finding optimal thresholds as a multiobjective optimization problem was formulated, and a genetic algorithm to solve it was utilized by evolving the Pareto front of the Pareto optimal set. The new CTC CAD system was tested on 792 patients. The sensitivities of the optimized system improved significantly, from 61.68% to 74.71% with an increase of 13.03% (95% CI [6.57%, 19.5%], p=7.78×10−5) for the size category of 6–9 mm polyps, from 65.02% to 77.4% with an increase of 12.38% (95% CI [6.23%, 18.53%], p=7.95×10−5) for polyps 6 mm or larger, and from 82.2% to 90.58% with an increase of 8.38% (95%CI [0.75%, 16%], p=0.03) for polyps 8 mm or larger at comparable false positive rates. The sensitivities of the optimized system are nearly equivalent to those of expert radiologists. PMID:19235388
Region-growing approach to detect microcalcifications in digital mammograms
NASA Astrophysics Data System (ADS)
Shin, Jin-Wook; Chae, Soo-Ik; Sook, Yoon M.; Park, Dong-Sun
2001-09-01
Detecting early symptoms of breast cancer is very important to enhance the possibility of cure. There have been active researches to develop computer-aided diagnosis(CAD) systems detecting early symptoms of breast cancer in digital mammograms. An expert or a CAD system can recognize the early symptoms based on microcalcifications appeared in digital mammographic images. Microcalcifications have higher gray value than surrounding regions, so these can be detected by expanding a region from a local maximum. However the resultant image contains unnecessary elements such as noise, holes and valleys. Mathematical morphology is a good solution to delete regions that are affected by the unnecessary elements. In this paper, we present a method that effectively detects microcalcifications in digital mammograms using a combination of local maximum operation and the region-growing operation.
NASA Astrophysics Data System (ADS)
Meijs, M.; Debats, O.; Huisman, H.
2015-03-01
In prostate cancer, the detection of metastatic lymph nodes indicates progression from localized disease to metastasized cancer. The detection of positive lymph nodes is, however, a complex and time consuming task for experienced radiologists. Assistance of a two-stage Computer-Aided Detection (CAD) system in MR Lymphography (MRL) is not yet feasible due to the large number of false positives in the first stage of the system. By introducing a multi-structure, multi-atlas segmentation, using an affine transformation followed by a B-spline transformation for registration, the organ location is given by a mean density probability map. The atlas segmentation is semi-automatically drawn with ITK-SNAP, using Active Contour Segmentation. Each anatomic structure is identified by a label number. Registration is performed using Elastix, using Mutual Information and an Adaptive Stochastic Gradient optimization. The dataset consists of the MRL scans of ten patients, with lymph nodes manually annotated in consensus by two expert readers. The feature map of the CAD system consists of the Multi-Atlas and various other features (e.g. Normalized Intensity and multi-scale Blobness). The voxel-based Gentleboost classifier is evaluated using ROC analysis with cross validation. We show in a set of 10 studies that adding multi-structure, multi-atlas anatomical structure likelihood features improves the quality of the lymph node voxel likelihood map. Multiple structure anatomy maps may thus make MRL CAD more feasible.
A ROC-based feature selection method for computer-aided detection and diagnosis
NASA Astrophysics Data System (ADS)
Wang, Songyuan; Zhang, Guopeng; Liao, Qimei; Zhang, Junying; Jiao, Chun; Lu, Hongbing
2014-03-01
Image-based computer-aided detection and diagnosis (CAD) has been a very active research topic aiming to assist physicians to detect lesions and distinguish them from benign to malignant. However, the datasets fed into a classifier usually suffer from small number of samples, as well as significantly less samples available in one class (have a disease) than the other, resulting in the classifier's suboptimal performance. How to identifying the most characterizing features of the observed data for lesion detection is critical to improve the sensitivity and minimize false positives of a CAD system. In this study, we propose a novel feature selection method mR-FAST that combines the minimal-redundancymaximal relevance (mRMR) framework with a selection metric FAST (feature assessment by sliding thresholds) based on the area under a ROC curve (AUC) generated on optimal simple linear discriminants. With three feature datasets extracted from CAD systems for colon polyps and bladder cancer, we show that the space of candidate features selected by mR-FAST is more characterizing for lesion detection with higher AUC, enabling to find a compact subset of superior features at low cost.
Giger, Maryellen L.; Chan, Heang-Ping; Boone, John
2008-01-01
The roles of physicists in medical imaging have expanded over the years, from the study of imaging systems (sources and detectors) and dose to the assessment of image quality and perception, the development of image processing techniques, and the development of image analysis methods to assist in detection and diagnosis. The latter is a natural extension of medical physicists’ goals in developing imaging techniques to help physicians acquire diagnostic information and improve clinical decisions. Studies indicate that radiologists do not detect all abnormalities on images that are visible on retrospective review, and they do not always correctly characterize abnormalities that are found. Since the 1950s, the potential use of computers had been considered for analysis of radiographic abnormalities. In the mid-1980s, however, medical physicists and radiologists began major research efforts for computer-aided detection or computer-aided diagnosis (CAD), that is, using the computer output as an aid to radiologists—as opposed to a completely automatic computer interpretation—focusing initially on methods for the detection of lesions on chest radiographs and mammograms. Since then, extensive investigations of computerized image analysis for detection or diagnosis of abnormalities in a variety of 2D and 3D medical images have been conducted. The growth of CAD over the past 20 years has been tremendous—from the early days of time-consuming film digitization and CPU-intensive computations on a limited number of cases to its current status in which developed CAD approaches are evaluated rigorously on large clinically relevant databases. CAD research by medical physicists includes many aspects—collecting relevant normal and pathological cases; developing computer algorithms appropriate for the medical interpretation task including those for segmentation, feature extraction, and classifier design; developing methodology for assessing CAD performance; validating the algorithms using appropriate cases to measure performance and robustness; conducting observer studies with which to evaluate radiologists in the diagnostic task without and with the use of the computer aid; and ultimately assessing performance with a clinical trial. Medical physicists also have an important role in quantitative imaging, by validating the quantitative integrity of scanners and developing imaging techniques, and image analysis tools that extract quantitative data in a more accurate and automated fashion. As imaging systems become more complex and the need for better quantitative information from images grows, the future includes the combined research efforts from physicists working in CAD with those working on quantitative imaging systems to readily yield information on morphology, function, molecular structure, and more—from animal imaging research to clinical patient care. A historical review of CAD and a discussion of challenges for the future are presented here, along with the extension to quantitative image analysis. PMID:19175137
DOE Office of Scientific and Technical Information (OSTI.GOV)
Giger, Maryellen L.; Chan, Heang-Ping; Boone, John
2008-12-15
The roles of physicists in medical imaging have expanded over the years, from the study of imaging systems (sources and detectors) and dose to the assessment of image quality and perception, the development of image processing techniques, and the development of image analysis methods to assist in detection and diagnosis. The latter is a natural extension of medical physicists' goals in developing imaging techniques to help physicians acquire diagnostic information and improve clinical decisions. Studies indicate that radiologists do not detect all abnormalities on images that are visible on retrospective review, and they do not always correctly characterize abnormalities thatmore » are found. Since the 1950s, the potential use of computers had been considered for analysis of radiographic abnormalities. In the mid-1980s, however, medical physicists and radiologists began major research efforts for computer-aided detection or computer-aided diagnosis (CAD), that is, using the computer output as an aid to radiologists--as opposed to a completely automatic computer interpretation--focusing initially on methods for the detection of lesions on chest radiographs and mammograms. Since then, extensive investigations of computerized image analysis for detection or diagnosis of abnormalities in a variety of 2D and 3D medical images have been conducted. The growth of CAD over the past 20 years has been tremendous--from the early days of time-consuming film digitization and CPU-intensive computations on a limited number of cases to its current status in which developed CAD approaches are evaluated rigorously on large clinically relevant databases. CAD research by medical physicists includes many aspects--collecting relevant normal and pathological cases; developing computer algorithms appropriate for the medical interpretation task including those for segmentation, feature extraction, and classifier design; developing methodology for assessing CAD performance; validating the algorithms using appropriate cases to measure performance and robustness; conducting observer studies with which to evaluate radiologists in the diagnostic task without and with the use of the computer aid; and ultimately assessing performance with a clinical trial. Medical physicists also have an important role in quantitative imaging, by validating the quantitative integrity of scanners and developing imaging techniques, and image analysis tools that extract quantitative data in a more accurate and automated fashion. As imaging systems become more complex and the need for better quantitative information from images grows, the future includes the combined research efforts from physicists working in CAD with those working on quantitative imaging systems to readily yield information on morphology, function, molecular structure, and more--from animal imaging research to clinical patient care. A historical review of CAD and a discussion of challenges for the future are presented here, along with the extension to quantitative image analysis.« less
Computer-aided diagnosis in radiological imaging: current status and future challenges
NASA Astrophysics Data System (ADS)
Doi, Kunio
2009-10-01
Computer-aided diagnosis (CAD) has become one of the major research subjects in medical imaging and diagnostic radiology. Many different types of CAD schemes are being developed for detection and/or characterization of various lesions in medical imaging, including conventional projection radiography, CT, MRI, and ultrasound imaging. Commercial systems for detection of breast lesions on mammograms have been developed and have received FDA approval for clinical use. CAD may be defined as a diagnosis made by a physician who takes into account the computer output as a "second opinion". The purpose of CAD is to improve the quality and productivity of physicians in their interpretation of radiologic images. The quality of their work can be improved in terms of the accuracy and consistency of their radiologic diagnoses. In addition, the productivity of radiologists is expected to be improved by a reduction in the time required for their image readings. The computer output is derived from quantitative analysis of radiologic images by use of various methods and techniques in computer vision, artificial intelligence, and artificial neural networks (ANNs). The computer output may indicate a number of important parameters, for example, the locations of potential lesions such as lung cancer and breast cancer, the likelihood of malignancy of detected lesions, and the likelihood of various diseases based on differential diagnosis in a given image and clinical parameters. In this review article, the basic concept of CAD is first defined, and the current status of CAD research is then described. In addition, the potential of CAD in the future is discussed and predicted.
Wavelet method for CT colonography computer-aided polyp detection.
Li, Jiang; Van Uitert, Robert; Yao, Jianhua; Petrick, Nicholas; Franaszek, Marek; Huang, Adam; Summers, Ronald M
2008-08-01
Computed tomographic colonography (CTC) computer aided detection (CAD) is a new method to detect colon polyps. Colonic polyps are abnormal growths that may become cancerous. Detection and removal of colonic polyps, particularly larger ones, has been shown to reduce the incidence of colorectal cancer. While high sensitivities and low false positive rates are consistently achieved for the detection of polyps sized 1 cm or larger, lower sensitivities and higher false positive rates occur when the goal of CAD is to identify "medium"-sized polyps, 6-9 mm in diameter. Such medium-sized polyps may be important for clinical patient management. We have developed a wavelet-based postprocessor to reduce false positives for this polyp size range. We applied the wavelet-based postprocessor to CTC CAD findings from 44 patients in whom 45 polyps with sizes of 6-9 mm were found at segmentally unblinded optical colonoscopy and visible on retrospective review of the CT colonography images. Prior to the application of the wavelet-based postprocessor, the CTC CAD system detected 33 of the polyps (sensitivity 73.33%) with 12.4 false positives per patient, a sensitivity comparable to that of expert radiologists. Fourfold cross validation with 5000 bootstraps showed that the wavelet-based postprocessor could reduce the false positives by 56.61% (p <0.001), to 5.38 per patient (95% confidence interval [4.41, 6.34]), without significant sensitivity degradation (32/45, 71.11%, 95% confidence interval [66.39%, 75.74%], p=0.1713). We conclude that this wavelet-based postprocessor can substantially reduce the false positive rate of our CTC CAD for this important polyp size range.
Dewailly, Marion; Rémy-Jardin, Martine; Duhamel, Alain; Faivre, Jean-Baptiste; Pontana, François; Deken, Valérie; Bakai, Anne-Marie; Remy, Jacques
2010-01-01
To evaluate the performance of a computer-aided detection (CAD) system for diagnosing peripheral acute pulmonary embolism (PE) with a 64-slice multi-detector row computed tomography (CT). Two radiologists investigated the accuracy of a software aimed at detecting peripheral clots (PECAD prototype, version 7; Siemens Medical Systems, Forchheim, Germany) by applying this tool for the analysis of the pulmonary arterial bed of 74 CT angiograms obtained with 64-slice dual-source CT (Definition; Siemens Medical Systems). These cases were retrospectively selected from a database of CT studies performed on the same CT unit, with a similar collimation (64 x 0.6 mm) and similar injection protocols. Patient selection was based on a variety of (1) scanning conditions, namely, nongated (n = 30), electrocardiography-gated (n = 30), and dual-energy CT angiograms (n = 14), and (2) image quality (IQ), namely, scans of excellent IQ (n = 53) and lower IQ due to lower levels of arterial enhancement and/or presence of noise (n = 21). The standard of truth was based on the 2 radiologists' consensus reading and the results of CAD. The software detected 80 of 93 peripheral clots present in the 21 patients (42 segmental and 38 subsegmental clots). The overall sensitivity (95% confidence interval) of the CAD tool was 86% (77%-92%) for detecting peripheral clots, 78% (64.5%-88%) at the segmental level and 97% (85.5%-99.9%) at the subsegmental level. Assuming normal vascular anatomy with 20 segmental and 40 subsegmental arteries, overall specificity and positive and negative predictive values (95% confidence interval) of the software were 91.8% (91%-92.6%), 18.4% (15%-22.4%), and 99.7% (99.5%-99.8%), respectively. A mean of 5.4 false positives was found per patient (total, 354 false positives), mainly linked to the presence of perivascular connective tissue (n = 119; 34%) and perivascular airspace consolidation (n = 97; 27%). The sensitivities (95% confidence interval) for the CAD tool were 91% (69.8%-99.3%) for dual-energy, 87% (59.3%-93.2%) for electrocardiography-gated, and 87% (73.5%-95.3%) for nongated scans (P > 0.05). No significant difference was found in the sensitivity of the CAD software when comparing the scans according to the scanning conditions and image quality. The evaluated CAD software has a good sensitivity in detecting peripheral PE, which is not influenced by the scanning conditions or the overall image quality.
Correlation coefficient based supervised locally linear embedding for pulmonary nodule recognition.
Wu, Panpan; Xia, Kewen; Yu, Hengyong
2016-11-01
Dimensionality reduction techniques are developed to suppress the negative effects of high dimensional feature space of lung CT images on classification performance in computer aided detection (CAD) systems for pulmonary nodule detection. An improved supervised locally linear embedding (SLLE) algorithm is proposed based on the concept of correlation coefficient. The Spearman's rank correlation coefficient is introduced to adjust the distance metric in the SLLE algorithm to ensure that more suitable neighborhood points could be identified, and thus to enhance the discriminating power of embedded data. The proposed Spearman's rank correlation coefficient based SLLE (SC(2)SLLE) is implemented and validated in our pilot CAD system using a clinical dataset collected from the publicly available lung image database consortium and image database resource initiative (LICD-IDRI). Particularly, a representative CAD system for solitary pulmonary nodule detection is designed and implemented. After a sequential medical image processing steps, 64 nodules and 140 non-nodules are extracted, and 34 representative features are calculated. The SC(2)SLLE, as well as SLLE and LLE algorithm, are applied to reduce the dimensionality. Several quantitative measurements are also used to evaluate and compare the performances. Using a 5-fold cross-validation methodology, the proposed algorithm achieves 87.65% accuracy, 79.23% sensitivity, 91.43% specificity, and 8.57% false positive rate, on average. Experimental results indicate that the proposed algorithm outperforms the original locally linear embedding and SLLE coupled with the support vector machine (SVM) classifier. Based on the preliminary results from a limited number of nodules in our dataset, this study demonstrates the great potential to improve the performance of a CAD system for nodule detection using the proposed SC(2)SLLE. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
Girod, Sabine; Schvartzman, Sara C; Gaudilliere, Dyani; Salisbury, Kenneth; Silva, Rebeka
2016-01-01
Computer-assisted surgical (CAS) planning tools are available for craniofacial surgery, but are usually based on computer-aided design (CAD) tools that lack the ability to detect the collision of virtual objects (i.e., fractured bone segments). We developed a CAS system featuring a sense of touch (haptic) that enables surgeons to physically interact with individual, patient-specific anatomy and immerse in a three-dimensional virtual environment. In this study, we evaluated initial user experience with our novel system compared to an existing CAD system. Ten surgery resident trainees received a brief verbal introduction to both the haptic and CAD systems. Users simulated mandibular fracture reduction in three clinical cases within a 15 min time limit for each system and completed a questionnaire to assess their subjective experience. We compared standard landmarks and linear and angular measurements between the simulated results and the actual surgical outcome and found that haptic simulation results were not significantly different from actual postoperative outcomes. In contrast, CAD results significantly differed from both the haptic simulation and actual postoperative results. In addition to enabling a more accurate fracture repair, the haptic system provided a better user experience than the CAD system in terms of intuitiveness and self-reported quality of repair.
A completely automated CAD system for mass detection in a large mammographic database.
Bellotti, R; De Carlo, F; Tangaro, S; Gargano, G; Maggipinto, G; Castellano, M; Massafra, R; Cascio, D; Fauci, F; Magro, R; Raso, G; Lauria, A; Forni, G; Bagnasco, S; Cerello, P; Zanon, E; Cheran, S C; Lopez Torres, E; Bottigli, U; Masala, G L; Oliva, P; Retico, A; Fantacci, M E; Cataldo, R; De Mitri, I; De Nunzio, G
2006-08-01
Mass localization plays a crucial role in computer-aided detection (CAD) systems for the classification of suspicious regions in mammograms. In this article we present a completely automated classification system for the detection of masses in digitized mammographic images. The tool system we discuss consists in three processing levels: (a) Image segmentation for the localization of regions of interest (ROIs). This step relies on an iterative dynamical threshold algorithm able to select iso-intensity closed contours around gray level maxima of the mammogram. (b) ROI characterization by means of textural features computed from the gray tone spatial dependence matrix (GTSDM), containing second-order spatial statistics information on the pixel gray level intensity. As the images under study were recorded in different centers and with different machine settings, eight GTSDM features were selected so as to be invariant under monotonic transformation. In this way, the images do not need to be normalized, as the adopted features depend on the texture only, rather than on the gray tone levels, too. (c) ROI classification by means of a neural network, with supervision provided by the radiologist's diagnosis. The CAD system was evaluated on a large database of 3369 mammographic images [2307 negative, 1062 pathological (or positive), containing at least one confirmed mass, as diagnosed by an expert radiologist]. To assess the performance of the system, receiver operating characteristic (ROC) and free-response ROC analysis were employed. The area under the ROC curve was found to be Az = 0.783 +/- 0.008 for the ROI-based classification. When evaluating the accuracy of the CAD against the radiologist-drawn boundaries, 4.23 false positives per image are found at 80% of mass sensitivity.
NASA Astrophysics Data System (ADS)
Ma, Kevin; Wong, Jonathan; Zhong, Mark; Zhang, Jeff; Liu, Brent
2014-03-01
In the past, we have presented an imaging-informatics based eFolder system for managing and analyzing imaging and lesion data of multiple sclerosis (MS) patients, which allows for data storage, data analysis, and data mining in clinical and research settings. The system integrates the patient's clinical data with imaging studies and a computer-aided detection (CAD) algorithm for quantifying MS lesion volume, lesion contour, locations, and sizes in brain MRI studies. For compliance with IHE integration protocols, long-term storage in PACS, and data query and display in a DICOM compliant clinical setting, CAD results need to be converted into DICOM-Structured Report (SR) format. Open-source dcmtk and customized XML templates are used to convert quantitative MS CAD results from MATLAB to DICOM-SR format. A web-based GUI based on our existing web-accessible DICOM object (WADO) image viewer has been designed to display the CAD results from generated SR files. The GUI is able to parse DICOM-SR files and extract SR document data, then display lesion volume, location, and brain matter volume along with the referenced DICOM imaging study. In addition, the GUI supports lesion contour overlay, which matches a detected MS lesion with its corresponding DICOM-SR data when a user selects either the lesion or the data. The methodology of converting CAD data in native MATLAB format to DICOM-SR and displaying the tabulated DICOM-SR along with the patient's clinical information, and relevant study images in the GUI will be demonstrated. The developed SR conversion model and GUI support aim to further demonstrate how to incorporate CAD post-processing components in a PACS and imaging informatics-based environment.
Skaane, Per; Kshirsagar, Ashwini; Hofvind, Solveig; Jahr, Gunnar; Castellino, Ronald A
2012-04-01
Double reading improves the cancer detection rate in mammography screening. Single reading with computer-aided detection (CAD) has been considered to be an alternative to double reading. Little is known about the potential benefit of CAD in breast cancer screening with double reading. To compare prospective independent double reading of screen-film (SFM) and full-field digital (FFDM) mammography in population-based screening with retrospective standalone CAD performance on the baseline mammograms of the screen-detected cancers and subsequent cancers diagnosed during the follow-up period. The study had ethics committee approval. A 5-point rating scale for probability of cancer was used for 23,923 (SFM = 16,983; FFDM = 6940) screening mammograms. Of 208 evaluable cancers, 104 were screen-detected and 104 were subsequent (44 interval and 60 next screening round) cancers. Baseline mammograms of subsequent cancers were retrospectively classified in consensus without information about cancer location, histology, or CAD prompting as normal, non-specific minimal signs, significant minimal signs, and false-negatives. The baseline mammograms of the screen-detected cancers and subsequent cancers were evaluated by CAD. Significant minimal signs and false-negatives were considered 'actionable' and potentially diagnosable if correctly prompted by CAD. CAD correctly marked 94% (98/104) of the baseline mammograms of the screen-detected cancers (SFM = 95% [61/64]; FFDM = 93% [37/40]), including 96% (23/24) of those with discordant interpretations. Considering only those baseline examinations of subsequent cancers prospectively interpreted as normal and retrospectively categorized as 'actionable', CAD input at baseline screening had the potential to increase the cancer detection rate from 0.43% to 0.51% (P = 0.13); and to increase cancer detection by 16% ([104 + 17]/104) and decrease interval cancers by 20% (from 44 to 35). CAD may have the potential to increase cancer detection by up to 16%, and to reduce the number of interval cancers by up to 20% in SFM and FFDM screening programs using independent double reading with consensus review. The influence of true- and false-positive CAD marks on decision-making can, however, only be evaluated in a prospective clinical study.
Melendez, Jaime; Sánchez, Clara I; van Ginneken, Bram; Karssemeijer, Nico
2014-08-01
Mass candidate detection is a crucial component of multistep computer-aided detection (CAD) systems. It is usually performed by combining several local features by means of a classifier. When these features are processed on a per-image-location basis (e.g., for each pixel), mismatching problems may arise while constructing feature vectors for classification, which is especially true when the behavior expected from the evaluated features is a peaked response due to the presence of a mass. In this study, two of these problems, consisting of maxima misalignment and differences of maxima spread, are identified and two solutions are proposed. The first proposed method, feature maxima propagation, reproduces feature maxima through their neighboring locations. The second method, local feature selection, combines different subsets of features for different feature vectors associated with image locations. Both methods are applied independently and together. The proposed methods are included in a mammogram-based CAD system intended for mass detection in screening. Experiments are carried out with a database of 382 digital cases. Sensitivity is assessed at two sets of operating points. The first one is the interval of 3.5-15 false positives per image (FPs/image), which is typical for mass candidate detection. The second one is 1 FP/image, which allows to estimate the quality of the mass candidate detector's output for use in subsequent steps of the CAD system. The best results are obtained when the proposed methods are applied together. In that case, the mean sensitivity in the interval of 3.5-15 FPs/image significantly increases from 0.926 to 0.958 (p < 0.0002). At the lower rate of 1 FP/image, the mean sensitivity improves from 0.628 to 0.734 (p < 0.0002). Given the improved detection performance, the authors believe that the strategies proposed in this paper can render mass candidate detection approaches based on image location classification more robust to feature discrepancies and prove advantageous not only at the candidate detection level, but also at subsequent steps of a CAD system.
Vallejo, Enrique
2009-01-01
Coronary artery disease (CAD) remains the leading cause of death in the Western world, and early detection of CAD allows optimal therapeutic management. The gold standard has always been invasive coronary angiography, but over the years various non-invasive techniques have been developed to detect CAD, including cardiac SPECT and cardiac computed tomography (Cardiac CT). Cardiac SPECT permitted visualization of myocardial perfusion and have focused on the assessment of the hemodynamic consequences of obstructive coronary lesions as a marker of CAD. Cardiac CT focuses on the detection of atherosclerosis rather than ischemia, and permit detection of CAD at an earlier stage. Objectives of this manuscript are to discuss the clinical experience with both modalities and to provide a critical review of the strengths and limitations of Cardiac SPECT and Cardiac CT for the diagnostic and management of patients with suspected CAD or cardiac ischemic disease.
Dachman, Abraham H.; Wroblewski, Kristen; Vannier, Michael W.; Horne, John M.
2014-01-01
Computed tomography (CT) colonography is a screening modality used to detect colonic polyps before they progress to colorectal cancer. Computer-aided detection (CAD) is designed to decrease errors of detection by finding and displaying polyp candidates for evaluation by the reader. CT colonography CAD false-positive results are common and have numerous causes. The relative frequency of CAD false-positive results and their effect on reader performance on the basis of a 19-reader, 100-case trial shows that the vast majority of CAD false-positive results were dismissed by readers. Many CAD false-positive results are easily disregarded, including those that result from coarse mucosa, reconstruction, peristalsis, motion, streak artifacts, diverticulum, rectal tubes, and lipomas. CAD false-positive results caused by haustral folds, extracolonic candidates, diminutive lesions (<6 mm), anal papillae, internal hemorrhoids, varices, extrinsic compression, and flexural pseudotumors are almost always recognized and disregarded. The ileocecal valve and tagged stool are common sources of CAD false-positive results associated with reader false-positive results. Nondismissable CAD soft-tissue polyp candidates larger than 6 mm are another common cause of reader false-positive results that may lead to further evaluation with follow-up CT colonography or optical colonoscopy. Strategies for correctly evaluating CAD polyp candidates are important to avoid pitfalls from common sources of CAD false-positive results. ©RSNA, 2014 PMID:25384290
Vertebral degenerative disc disease severity evaluation using random forest classification
NASA Astrophysics Data System (ADS)
Munoz, Hector E.; Yao, Jianhua; Burns, Joseph E.; Pham, Yasuyuki; Stieger, James; Summers, Ronald M.
2014-03-01
Degenerative disc disease (DDD) develops in the spine as vertebral discs degenerate and osseous excrescences or outgrowths naturally form to restabilize unstable segments of the spine. These osseous excrescences, or osteophytes, may progress or stabilize in size as the spine reaches a new equilibrium point. We have previously created a CAD system that detects DDD. This paper presents a new system to determine the severity of DDD of individual vertebral levels. This will be useful to monitor the progress of developing DDD, as rapid growth may indicate that there is a greater stabilization problem that should be addressed. The existing DDD CAD system extracts the spine from CT images and segments the cortical shell of individual levels with a dual-surface model. The cortical shell is unwrapped, and is analyzed to detect the hyperdense regions of DDD. Three radiologists scored the severity of DDD of each disc space of 46 CT scans. Radiologists' scores and features generated from CAD detections were used to train a random forest classifier. The classifier then assessed the severity of DDD at each vertebral disc level. The agreement between the computer severity score and the average radiologist's score had a quadratic weighted Cohen's kappa of 0.64.
Shear Bond Strength of Repair Systems to New CAD/CAM Restorative Materials.
Üstün, Özlem; Büyükhatipoğlu, Işıl Keçik; Seçilmiş, Aslı
2016-11-23
To evaluate the bond strength of repair systems (Ceramic Repair, Clearfil Repair) to computer-aided design/computer-assisted machining (CAD/CAM) restorative materials (IPS e.max CAD, Vita Suprinity, Vita Enamic, Lava Ultimate). Thermally aged CAD/CAM restorative material specimens (5000 cycles between 5°C and 55°C) were randomly divided into two groups according to the repair system: Ceramic Repair (37% phosphoric acid + Monobond-S + Heliobond + Tetric N Ceram) or Clearfil Repair (40% phosphoric acid + mixture of Clearfil Porcelain Bond Activator and Clearfil SE Bond Primer + Clearfil SE Bond + Filtek Z250). The resin composite was light-cured on conditioned specimens. All specimens were stored in distilled water at 37°C for 24 hours and then additionally aged for 5000 thermal cycles. The shear bond strength test was performed using a universal testing machine (0.5 mm/min). Two-way ANOVA was used to detect significance differences according to the CAD/CAM material and composite repair system factors. Subgroup analyses were conducted using the least significant difference post-hoc test. The results of two-way ANOVA indicated that bond strength values varied according to the restorative materials (p < 0.05). No significant differences were observed between the CAD/CAM restorative materials (p > 0.05), except in the Vita Suprinity group (p < 0.05). Moreover, no differences were observed between the repair systems. Both the Clearfil and Ceramic repair systems used in the study allow for successful repairs. © 2016 by the American College of Prosthodontists.
Path length entropy analysis of diastolic heart sounds.
Griffel, Benjamin; Zia, Mohammad K; Fridman, Vladamir; Saponieri, Cesare; Semmlow, John L
2013-09-01
Early detection of coronary artery disease (CAD) using the acoustic approach, a noninvasive and cost-effective method, would greatly improve the outcome of CAD patients. To detect CAD, we analyze diastolic sounds for possible CAD murmurs. We observed diastolic sounds to exhibit 1/f structure and developed a new method, path length entropy (PLE) and a scaled version (SPLE), to characterize this structure to improve CAD detection. We compare SPLE results to Hurst exponent, Sample entropy and Multiscale entropy for distinguishing between normal and CAD patients. SPLE achieved a sensitivity-specificity of 80%-81%, the best of the tested methods. However, PLE and SPLE are not sufficient to prove nonlinearity, and evaluation using surrogate data suggests that our cardiovascular sound recordings do not contain significant nonlinear properties. Copyright © 2013 Elsevier Ltd. All rights reserved.
Path Length Entropy Analysis of Diastolic Heart Sounds
Griffel, B.; Zia, M. K.; Fridman, V.; Saponieri, C.; Semmlow, J. L.
2013-01-01
Early detection of coronary artery disease (CAD) using the acoustic approach, a noninvasive and cost-effective method, would greatly improve the outcome of CAD patients. To detect CAD, we analyze diastolic sounds for possible CAD murmurs. We observed diastolic sounds to exhibit 1/f structure and developed a new method, path length entropy (PLE) and a scaled version (SPLE), to characterize this structure to improve CAD detection. We compare SPLE results to Hurst exponent, Sample entropy and Multi-scale entropy for distinguishing between normal and CAD patients. SPLE achieved a sensitivity-specificity of 80%–81%, the best of the tested methods. However, PLE and SPLE are not sufficient to prove nonlinearity, and evaluation using surrogate data suggests that our cardiovascular sound recordings do not contain significant nonlinear properties. PMID:23930808
Godoy, Myrna C B; Kim, Tae Jung; White, Charles S; Bogoni, Luca; de Groot, Patricia; Florin, Charles; Obuchowski, Nancy; Babb, James S; Salganicoff, Marcos; Naidich, David P; Anand, Vikram; Park, Sangmin; Vlahos, Ioannis; Ko, Jane P
2013-01-01
The objective of our study was to evaluate the impact of computer-aided detection (CAD) on the identification of subsolid and solid lung nodules on thin- and thick-section CT. For 46 chest CT examinations with ground-glass opacity (GGO) nodules, CAD marks computed using thin data were evaluated in two phases. First, four chest radiologists reviewed thin sections (reader(thin)) for nodules and subsequently CAD marks (reader(thin) + CAD(thin)). After 4 months, the same cases were reviewed on thick sections (reader(thick)) and subsequently with CAD marks (reader(thick) + CAD(thick)). Sensitivities were evaluated. Additionally, reader(thick) sensitivity with assessment of CAD marks on thin sections was estimated (reader(thick) + CAD(thin)). For 155 nodules (mean, 5.5 mm; range, 4.0-27.5 mm)-74 solid nodules, 22 part-solid (part-solid nodules), and 59 GGO nodules-CAD stand-alone sensitivity was 80%, 95%, and 71%, respectively, with three false-positives on average (0-12) per CT study. Reader(thin) + CAD(thin) sensitivities were higher than reader(thin) for solid nodules (82% vs 57%, p < 0.001), part-solid nodules (97% vs 81%, p = 0.0027), and GGO nodules (82% vs 69%, p < 0.001) for all readers (p < 0.001). Respective sensitivities for reader(thick), reader(thick) + CAD(thick), reader(thick) + CAD(thin) were 40%, 58% (p < 0.001), and 77% (p < 0.001) for solid nodules; 72%, 73% (p = 0.322), and 94% (p < 0.001) for part-solid nodules; and 53%, 58% (p = 0.008), and 79% (p < 0.001) for GGO nodules. For reader(thin), false-positives increased from 0.64 per case to 0.90 with CAD(thin) (p < 0.001) but not for reader(thick); false-positive rates were 1.17, 1.19, and 1.26 per case for reader(thick), reader(thick) + CAD(thick), and reader(thick) + CAD(thin), respectively. Detection of GGO nodules and solid nodules is significantly improved with CAD. When interpretation is performed on thick sections, the benefit is greater when CAD marks are reviewed on thin rather than thick sections.
NASA Astrophysics Data System (ADS)
Park, Sang Cheol; Zheng, Bin; Wang, Xiao-Hui; Gur, David
2008-03-01
Digital breast tomosynthesis (DBT) has emerged as a promising imaging modality for screening mammography. However, visually detecting micro-calcification clusters depicted on DBT images is a difficult task. Computer-aided detection (CAD) schemes for detecting micro-calcification clusters depicted on mammograms can achieve high performance and the use of CAD results can assist radiologists in detecting subtle micro-calcification clusters. In this study, we compared the performance of an available 2D based CAD scheme with one that includes a new grouping and scoring method when applied to both projection and reconstructed DBT images. We selected a dataset involving 96 DBT examinations acquired on 45 women. Each DBT image set included 11 low dose projection images and a varying number of reconstructed image slices ranging from 18 to 87. In this dataset 20 true-positive micro-calcification clusters were visually detected on the projection images and 40 were visually detected on the reconstructed images, respectively. We first applied the CAD scheme that was previously developed in our laboratory to the DBT dataset. We then tested a new grouping method that defines an independent cluster by grouping the same cluster detected on different projection or reconstructed images. We then compared four scoring methods to assess the CAD performance. The maximum sensitivity level observed for the different grouping and scoring methods were 70% and 88% for the projection and reconstructed images with a maximum false-positive rate of 4.0 and 15.9 per examination, respectively. This preliminary study demonstrates that (1) among the maximum, the minimum or the average CAD generated scores, using the maximum score of the grouped cluster regions achieved the highest performance level, (2) the histogram based scoring method is reasonably effective in reducing false-positive detections on the projection images but the overall CAD sensitivity is lower due to lower signal-to-noise ratio, and (3) CAD achieved higher sensitivity and higher false-positive rate (per examination) on the reconstructed images. We concluded that without changing the detection threshold or performing pre-filtering to possibly increase detection sensitivity, current CAD schemes developed and optimized for 2D mammograms perform relatively poorly and need to be re-optimized using DBT datasets and new grouping and scoring methods need to be incorporated into the schemes if these are to be used on the DBT examinations.
Wolfger, Barbara; Manns, Braden J; Barkema, Herman W; Schwartzkopf-Genswein, Karen S; Dorin, Craig; Orsel, Karin
2015-03-01
New technologies to identify diseased feedlot cattle in early stages of illness have been developed to reduce costs and welfare impacts associated with bovine respiratory disease (BRD). However, the economic value of early BRD detection has never been assessed. The objective was to simulate cost differences between two BRD detection methods during the first 61 d on feed (DOF) applied in moderate- to large-sized feedlots using an automated recording system (ARS) for feeding behavior and the current industry standard, pen-checking (visual appraisal confirmed by rectal temperature). Economic impact was assessed with a cost analysis in a simple decision model. Scenarios for Canadian and US feedlots with high- and low-risk cattle were modeled, and uncertainty was estimated using extensive sensitivity analyses. Input costs and probabilities were mainly extracted from publicly accessible market observations and a large-scale US feedlot study. In the baseline scenario, we modeled high-risk cattle with a treatment rate of 20% within the first 61 DOF in a feedlot of >8000 cattle in Canada. Early BRD detection was estimated to result in a relative risk of 0.60 in retreatment and 0.66 in mortality compared to pen-checking (based on previously published estimates). The additional cost of monitoring health with ARS in Canadian dollar (CAD) was 13.68 per steer. Scenario analysis for similar sized US feedlots and low-risk cattle with a treatment rate of 8% were included to account for variability in costs and probabilities in various cattle populations. Considering the cost of monitoring, all relevant treatment costs and sale price, ARS was more costly than visual appraisal during the first 61 DOF by CAD 9.61 and CAD 9.69 per steer in Canada and the US, respectively. This cost difference increased in low-risk cattle in Canada to CAD 12.45. Early BRD detection with ARS became less expensive if the costs for the system decreased to less than CAD 4.06/steer, or if the underlying true BRD incidence (not treatment rate) within the first 61 DOF exceeded 47%. The model was robust to variability in the remaining input variables. Some of the assumptions in the baseline analyses were conservative and may have underestimated the real value of early BRD detection. Systems such as ARS may reduce treatment costs in some scenarios, but the investment costs are currently too high to be cost-effective when used solely for BRD detection compared to pen-checking. Copyright © 2014 Elsevier B.V. All rights reserved.
van Zelst, J C M; Tan, T; Platel, B; de Jong, M; Steenbakkers, A; Mourits, M; Grivegnee, A; Borelli, C; Karssemeijer, N; Mann, R M
2017-04-01
To investigate the effect of dedicated Computer Aided Detection (CAD) software for automated breast ultrasound (ABUS) on the performance of radiologists screening for breast cancer. 90 ABUS views of 90 patients were randomly selected from a multi-institutional archive of cases collected between 2010 and 2013. This dataset included normal cases (n=40) with >1year of follow up, benign (n=30) lesions that were either biopsied or remained stable, and malignant lesions (n=20). Six readers evaluated all cases with and without CAD in two sessions. CAD-software included conventional CAD-marks and an intelligent minimum intensity projection of the breast tissue. Readers reported using a likelihood-of-malignancy scale from 0 to 100. Alternative free-response ROC analysis was used to measure the performance. Without CAD, the average area-under-the-curve (AUC) of the readers was 0.77 and significantly improved with CAD to 0.84 (p=0.001). Sensitivity of all readers improved (range 5.2-10.6%) by using CAD but specificity decreased in four out of six readers (range 1.4-5.7%). No significant difference was observed in the AUC between experienced radiologists and residents both with and without CAD. Dedicated CAD-software for ABUS has the potential to improve the cancer detection rates of radiologists screening for breast cancer. Copyright © 2017 Elsevier B.V. All rights reserved.
Moschetti, Karine; Muzzarelli, Stefano; Pinget, Christophe; Wagner, Anja; Pilz, Günther; Wasserfallen, Jean-Blaise; Schulz-Menger, Jeanette; Nothnagel, Detle; Dill, Torsten; Frank, Herbert; Lombardi, Massimo; Bruder, Oliver; Mahrholdt, Heiko; Schwitter, Jürg
2012-06-14
Cardiovascular magnetic resonance (CMR) has favorable characteristics for diagnostic evaluation and risk stratification of patients with known or suspected CAD. CMR utilization in CAD detection is growing fast. However, data on its cost-effectiveness are scarce. The goal of this study is to compare the costs of two strategies for detection of significant coronary artery stenoses in patients with suspected coronary artery disease (CAD): 1) Performing CMR first to assess myocardial ischemia and/or infarct scar before referring positive patients (defined as presence of ischemia and/or infarct scar to coronary angiography (CXA) versus 2) a hypothetical CXA performed in all patients as a single test to detect CAD. A subgroup of the European CMR pilot registry was used including 2,717 consecutive patients who underwent stress-CMR. From these patients, 21% were positive for CAD (ischemia and/or infarct scar), 73% negative, and 6% uncertain and underwent additional testing. The diagnostic costs were evaluated using invoicing costs of each test performed. Costs analysis was performed from a health care payer perspective in German, United Kingdom, Swiss, and United States health care settings. In the public sectors of the German, United Kingdom, and Swiss health care systems, cost savings from the CMR-driven strategy were 50%, 25% and 23%, respectively, versus outpatient CXA. If CXA was carried out as an inpatient procedure, cost savings were 46%, 50% and 48%, respectively. In the United States context, cost savings were 51% when compared with inpatient CXA, but higher for CMR by 8% versus outpatient CXA. This analysis suggests that from an economic perspective, the use of CMR should be encouraged as a management option for patients with suspected CAD.
Toneff, M J; Sreekumar, A; Tinnirello, A; Hollander, P Den; Habib, S; Li, S; Ellis, M J; Xin, L; Mani, S A; Rosen, J M
2016-06-17
The epithelial to mesenchymal transition (EMT) has been implicated in metastasis and therapy resistance of carcinomas and can endow cancer cells with cancer stem cell (CSC) properties. The ability to detect cancer cells that are undergoing or have completed EMT has typically relied on the expression of cell surface antigens that correlate with an EMT/CSC phenotype. Alternatively these cells may be permanently marked through Cre-mediated recombination or through immunostaining of fixed cells. The EMT process is dynamic, and these existing methods cannot reveal such changes within live cells. The development of fluorescent sensors that mirror the dynamic EMT state by following the expression of bona fide EMT regulators in live cells would provide a valuable new tool for characterizing EMT. In addition, these sensors will allow direct observation of cellular plasticity with respect to the epithelial/mesenchymal state to enable more effective studies of EMT in cancer and development. We generated a lentiviral-based, dual fluorescent reporter system, designated as the Z-cad dual sensor, comprising destabilized green fluorescent protein containing the ZEB1 3' UTR and red fluorescent protein driven by the E-cadherin (CDH1) promoter. Using this sensor, we robustly detected EMT and mesenchymal to epithelial transition (MET) in breast cancer cells by flow cytometry and fluorescence microscopy. Importantly, we observed dynamic changes in cellular populations undergoing MET. Additionally, we used the Z-cad sensor to identify and isolate minor subpopulations of cells displaying mesenchymal properties within a population comprising predominately epithelial-like cells. The Z-cad dual sensor identified cells with CSC-like properties more effectively than either the ZEB1 3' UTR or E-cadherin sensor alone. The Z-cad dual sensor effectively reports the activities of two factors critical in determining the epithelial/mesenchymal state of carcinoma cells. The ability of this stably integrating dual sensor system to detect dynamic fluctuations between these two states through live cell imaging offers a significant improvement over existing methods and helps facilitate the study of EMT/MET plasticity in response to different stimuli and in cancer pathogenesis. Finally, the versatile Z-cad sensor can be adapted to a variety of in vitro or in vivo systems to elucidate whether EMT/MET contributes to normal and disease phenotypes.
Bell, L T O; Gandhi, S
2018-06-01
To directly compare the accuracy and speed of analysis of two commercially available computer-assisted detection (CAD) programs in detecting colorectal polyps. In this retrospective single-centre study, patients who had colorectal polyps identified on computed tomography colonography (CTC) and subsequent lower gastrointestinal endoscopy, were analysed using two commercially available CAD programs (CAD1 and CAD2). Results were compared against endoscopy to ascertain sensitivity and positive predictive value (PPV) for colorectal polyps. Time taken for CAD analysis was also calculated. CAD1 demonstrated a sensitivity of 89.8%, PPV of 17.6% and mean analysis time of 125.8 seconds. CAD2 demonstrated a sensitivity of 75.5%, PPV of 44.0% and mean analysis time of 84.6 seconds. The sensitivity and PPV for colorectal polyps and CAD analysis times can vary widely between current commercially available CAD programs. There is still room for improvement. Generally, there is a trade-off between sensitivity and PPV, and so further developments should aim to optimise both. Information on these factors should be made routinely available, so that an informed choice on their use can be made. This information could also potentially influence the radiologist's use of CAD results. Copyright © 2018 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.
Park, Sang Cheol; Chapman, Brian E; Zheng, Bin
2011-06-01
This study developed a computer-aided detection (CAD) scheme for pulmonary embolism (PE) detection and investigated several approaches to improve CAD performance. In the study, 20 computed tomography examinations with various lung diseases were selected, which include 44 verified PE lesions. The proposed CAD scheme consists of five basic steps: 1) lung segmentation; 2) PE candidate extraction using an intensity mask and tobogganing region growing; 3) PE candidate feature extraction; 4) false-positive (FP) reduction using an artificial neural network (ANN); and 5) a multifeature-based k-nearest neighbor for positive/negative classification. In this study, we also investigated the following additional methods to improve CAD performance: 1) grouping 2-D detected features into a single 3-D object; 2) selecting features with a genetic algorithm (GA); and 3) limiting the number of allowed suspicious lesions to be cued in one examination. The results showed that 1) CAD scheme using tobogganing, an ANN, and grouping method achieved the maximum detection sensitivity of 79.2%; 2) the maximum scoring method achieved the superior performance over other scoring fusion methods; 3) GA was able to delete "redundant" features and further improve CAD performance; and 4) limiting the maximum number of cued lesions in an examination reduced FP rate by 5.3 times. Combining these approaches, CAD scheme achieved 63.2% detection sensitivity with 18.4 FP lesions per examination. The study suggested that performance of CAD schemes for PE detection depends on many factors that include 1) optimizing the 2-D region grouping and scoring methods; 2) selecting the optimal feature set; and 3) limiting the number of allowed cueing lesions per examination.
Luo, Tingting; Yan, Aifen; Liu, Lian; Jiang, Hong; Feng, Cuilan; Liu, Guannan; Liu, Fang; Tang, Dongsheng; Zhou, Tianhong
2018-03-28
To explore the effect of intervention of E-cadherin (E-cad) and B-lymphoma Moloney murine leukemia virus insertion region-1 (Bmi-1) mediated by transcription activator-like effector nuclease (TALEN) on the biological behaviors of nasopharyngeal carcinoma cells. Methods: Multi-locus gene targeting vectors pUC-DS1-CMV-E-cad-2A-Neo-DS2 and pUC-DS1-Bmi-1 shRNA-Zeo-DS2 were constructed, and the E-cad and Bmi-1 targeting vectors were transferred with TALEN plasmids to CNE-2 cells individually or simultaneously. The integration of target genes were detected by PCR, the expressions of E-cad and Bmi-1 were detected by Western blot. The changes of cell proliferation were detected by cell counting kit-8 (CCK-8) assay. The cell cycle and apoptosis were detected by flow cytometry. The cell migration and invasion were detected by Transwell assay. Results: The E-cad and Bmi-1 shRNA expression elements were successfully integrated into the genome of CNE-2 cells, the protein expression level of E-cad was up-regulated, and the protein expression level of Bmi-1 was down-regulated. The intervention of E-cad and Bmi-1 didn't affect the proliferation, cell cycle and apoptosis of CNE-2 cells, but it significantly inhibited the migration and invasion ability of CNE-2 cells. Furthermore, the intervention of E-cad and Bmi-1 together significantly inhibited the migration ability of nasopharyngeal carcinoma cells compared with the intervention of E-cad or Bmi-1 alone (all P<0.01). Conclusion: The joint intervention of E-cad and Bmi-1 mediated by TALEN can effectively inhibit the migration and invasion of nasopharyngeal carcinoma cells in vitro, which may lay the preliminary experimental basis for gene therapy of human cancer.
Computer Aided Detection of Breast Masses in Digital Tomosynthesis
2008-06-01
the suspicious CAD location were extracted. For the second set, 256x256 ROIs representing the - 8 - summed slab of 5 slices (5 mm) were extracted...region hotelling observer, digital tomosynthesis, multi-slice CAD algorithms, biopsy 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT 18...developing computer-aided detection ( CAD ) tools for mammography. Although these tools have shown promise in identifying calcifications, detecting
Moore, William; Ripton-Snyder, Jennifer; Wu, George; Hendler, Craig
2011-06-01
The objective of this research was to determine the sensitivity and specificity of a commercially available computer-aided detection (CAD) system for detection of lung nodule on posterior-anterior (PA) chest radiograph in a varied patient population who are referred to computed tomographic angiogram (CTA) of the chest as a reference standard. Patients who had a PA chest radiograph with concomitant CTA of the chest were included in this retrospective study. The PA chest radiograph was analyzed by a CAD device, and results were recorded. A qualitative assessment of the CAD results was performed using a 5-point Likert scale. The CTA was then reviewed to determine if there were correlative nodules. The presence of a correlative nodule between 0.5 cm and 1.5 cm was considered a positive result. The baseline sensitivity of the system was determined to be 0.707 (95% CI = 0.52-0.86), with a specificity of 0.50 (95% CI = 0.38-0.76). Positive predictive value was 0.30 (95% CI = 0.24-0.49), with a negative predictive value of 0.858 (95% CI = 0.82-0.95), and accuracy of 0.555 (95% CI = 0.40-0.66). When excluding nodules that were qualitatively determined by a thoracic radiologist to be false positives, the specificity was 0.781 (95% CI = 0.764-0.839), the positive predictive value was 0.564 (95% CI = 0.491-0.654), the negative predictive value was 0.829 (95% CI = 0.819-0.878), and the accuracy was 0.737 (95% CI = 0.721-0.801). The use of CAD for lung nodule detection on chest radiograph, when used in conjunction with an experienced radiologist, has a very good sensitivity, specificity, and accuracy.
Hole Feature on Conical Face Recognition for Turning Part Model
NASA Astrophysics Data System (ADS)
Zubair, A. F.; Abu Mansor, M. S.
2018-03-01
Computer Aided Process Planning (CAPP) is the bridge between CAD and CAM and pre-processing of the CAD data in the CAPP system is essential. For CNC turning part, conical faces of part model is inevitable to be recognised beside cylindrical and planar faces. As the sinus cosines of the cone radius structure differ according to different models, face identification in automatic feature recognition of the part model need special intention. This paper intends to focus hole on feature on conical faces that can be detected by CAD solid modeller ACIS via. SAT file. Detection algorithm of face topology were generated and compared. The study shows different faces setup for similar conical part models with different hole type features. Three types of holes were compared and different between merge faces and unmerge faces were studied.
NASA Astrophysics Data System (ADS)
Lee, Joon K.; Chan, Tao; Liu, Brent J.; Huang, H. K.
2009-02-01
Detection of acute intracranial hemorrhage (AIH) is a primary task in the interpretation of computed tomography (CT) brain scans of patients suffering from acute neurological disturbances or after head trauma. Interpretation can be difficult especially when the lesion is inconspicuous or the reader is inexperienced. We have previously developed a computeraided detection (CAD) algorithm to detect small AIH. One hundred and thirty five small AIH CT studies from the Los Angeles County (LAC) + USC Hospital were identified and matched by age and sex with one hundred and thirty five normal studies. These cases were then processed using our AIH CAD system to evaluate the efficacy and constraints of the algorithm.
Boone, Darren; Mallett, Susan; McQuillan, Justine; Taylor, Stuart A.; Altman, Douglas G.; Halligan, Steve
2015-01-01
Objectives To quantify the incremental benefit of computer-assisted-detection (CAD) for polyps, for inexperienced readers versus experienced readers of CT colonography. Methods 10 inexperienced and 16 experienced radiologists interpreted 102 colonography studies unassisted and with CAD utilised in a concurrent paradigm. They indicated any polyps detected on a study sheet. Readers’ interpretations were compared against a ground-truth reference standard: 46 studies were normal and 56 had at least one polyp (132 polyps in total). The primary study outcome was the difference in CAD net benefit (a combination of change in sensitivity and change in specificity with CAD, weighted towards sensitivity) for detection of patients with polyps. Results Inexperienced readers’ per-patient sensitivity rose from 39.1% to 53.2% with CAD and specificity fell from 94.1% to 88.0%, both statistically significant. Experienced readers’ sensitivity rose from 57.5% to 62.1% and specificity fell from 91.0% to 88.3%, both non-significant. Net benefit with CAD assistance was significant for inexperienced readers but not for experienced readers: 11.2% (95%CI 3.1% to 18.9%) versus 3.2% (95%CI -1.9% to 8.3%) respectively. Conclusions Concurrent CAD resulted in a significant net benefit when used by inexperienced readers to identify patients with polyps by CT colonography. The net benefit was nearly four times the magnitude of that observed for experienced readers. Experienced readers did not benefit significantly from concurrent CAD. PMID:26355745
Depeursinge, Adrien; Vargas, Alejandro; Gaillard, Frédéric; Platon, Alexandra; Geissbuhler, Antoine; Poletti, Pierre-Alexandre; Müller, Henning
2012-01-01
Clinical workflows and user interfaces of image-based computer-aided diagnosis (CAD) for interstitial lung diseases in high-resolution computed tomography are introduced and discussed. Three use cases are implemented to assist students, radiologists, and physicians in the diagnosis workup of interstitial lung diseases. In a first step, the proposed system shows a three-dimensional map of categorized lung tissue patterns with quantification of the diseases based on texture analysis of the lung parenchyma. Then, based on the proportions of abnormal and normal lung tissue as well as clinical data of the patients, retrieval of similar cases is enabled using a multimodal distance aggregating content-based image retrieval (CBIR) and text-based information search. The global system leads to a hybrid detection-CBIR-based CAD, where detection-based and CBIR-based CAD show to be complementary both on the user's side and on the algorithmic side. The proposed approach is in accordance with the classical workflow of clinicians searching for similar cases in textbooks and personal collections. The developed system enables objective and customizable inter-case similarity assessment, and the performance measures obtained with a leave-one-patient-out cross-validation (LOPO CV) are representative of a clinical usage of the system.
A computerized scheme for lung nodule detection in multiprojection chest radiography
DOE Office of Scientific and Technical Information (OSTI.GOV)
Guo Wei; Li Qiang; Boyce, Sarah J.
2012-04-15
Purpose: Our previous study indicated that multiprojection chest radiography could significantly improve radiologists' performance for lung nodule detection in clinical practice. In this study, the authors further verify that multiprojection chest radiography can greatly improve the performance of a computer-aided diagnostic (CAD) scheme. Methods: Our database consisted of 59 subjects, including 43 subjects with 45 nodules and 16 subjects without nodules. The 45 nodules included 7 real and 38 simulated ones. The authors developed a conventional CAD scheme and a new fusion CAD scheme to detect lung nodules. The conventional CAD scheme consisted of four steps for (1) identification ofmore » initial nodule candidates inside lungs, (2) nodule candidate segmentation based on dynamic programming, (3) extraction of 33 features from nodule candidates, and (4) false positive reduction using a piecewise linear classifier. The conventional CAD scheme processed each of the three projection images of a subject independently and discarded the correlation information between the three images. The fusion CAD scheme included the four steps in the conventional CAD scheme and two additional steps for (5) registration of all candidates in the three images of a subject, and (6) integration of correlation information between the registered candidates in the three images. The integration step retained all candidates detected at least twice in the three images of a subject and removed those detected only once in the three images as false positives. A leave-one-subject-out testing method was used for evaluation of the performance levels of the two CAD schemes. Results: At the sensitivities of 70%, 65%, and 60%, our conventional CAD scheme reported 14.7, 11.3, and 8.6 false positives per image, respectively, whereas our fusion CAD scheme reported 3.9, 1.9, and 1.2 false positives per image, and 5.5, 2.8, and 1.7 false positives per patient, respectively. The low performance of the conventional CAD scheme may be attributed to the high noise level in chest radiography, and the small size and low contrast of most nodules. Conclusions: This study indicated that the fusion of correlation information in multiprojection chest radiography can markedly improve the performance of CAD scheme for lung nodule detection.« less
Computer-Assisted Classification Patterns in Autoimmune Diagnostics: The AIDA Project
Benammar Elgaaied, Amel; Cascio, Donato; Bruno, Salvatore; Ciaccio, Maria Cristina; Cipolla, Marco; Fauci, Alessandro; Morgante, Rossella; Taormina, Vincenzo; Gorgi, Yousr; Marrakchi Triki, Raja; Ben Ahmed, Melika; Louzir, Hechmi; Yalaoui, Sadok; Imene, Sfar; Issaoui, Yassine; Abidi, Ahmed; Ammar, Myriam; Bedhiafi, Walid; Ben Fraj, Oussama; Bouhaha, Rym; Hamdi, Khouloud; Soumaya, Koudhi; Neili, Bilel; Asma, Gati; Lucchese, Mariano; Catanzaro, Maria; Barbara, Vincenza; Brusca, Ignazio; Fregapane, Maria; Amato, Gaetano; Friscia, Giuseppe; Neila, Trai; Turkia, Souayeh; Youssra, Haouami; Rekik, Raja; Bouokez, Hayet; Vasile Simone, Maria; Fauci, Francesco; Raso, Giuseppe
2016-01-01
Antinuclear antibodies (ANAs) are significant biomarkers in the diagnosis of autoimmune diseases in humans, done by mean of Indirect ImmunoFluorescence (IIF) method, and performed by analyzing patterns and fluorescence intensity. This paper introduces the AIDA Project (autoimmunity: diagnosis assisted by computer) developed in the framework of an Italy-Tunisia cross-border cooperation and its preliminary results. A database of interpreted IIF images is being collected through the exchange of images and double reporting and a Gold Standard database, containing around 1000 double reported images, has been settled. The Gold Standard database is used for optimization of a CAD (Computer Aided Detection) solution and for the assessment of its added value, in order to be applied along with an Immunologist as a second Reader in detection of autoantibodies. This CAD system is able to identify on IIF images the fluorescence intensity and the fluorescence pattern. Preliminary results show that CAD, used as second Reader, appeared to perform better than Junior Immunologists and hence may significantly improve their efficacy; compared with two Junior Immunologists, the CAD system showed higher Intensity Accuracy (85,5% versus 66,0% and 66,0%), higher Patterns Accuracy (79,3% versus 48,0% and 66,2%), and higher Mean Class Accuracy (79,4% versus 56,7% and 64.2%). PMID:27042658
Blackmon, Kevin N; Florin, Charles; Bogoni, Luca; McCain, Joshua W; Koonce, James D; Lee, Heon; Bastarrika, Gorka; Thilo, Christian; Costello, Philip; Salganicoff, Marcos; Joseph Schoepf, U
2011-06-01
To evaluate the effect of a computer-aided detection (CAD) algorithm on the performance of novice readers for detection of pulmonary embolism (PE) at CT pulmonary angiography (CTPA). We included CTPA examinations of 79 patients (50 female, 52 ± 18 years). Studies were evaluated by two independent inexperienced readers who marked all vessels containing PE. After 3 months all studies were reevaluated by the same two readers, this time aided by CAD prototype. A consensus read by three expert radiologists served as the reference standard. Statistical analysis used χ(2) and McNemar testing. Expert consensus revealed 119 PEs in 32 studies. For PE detection, the sensitivity of CAD alone was 78%. Inexperienced readers' initial interpretations had an average per-PE sensitivity of 50%, which improved to 71% (p < 0.001) with CAD as a second reader. False positives increased from 0.18 to 0.25 per study (p = 0.03). Per-study, the readers initially detected 27/32 positive studies (84%); with CAD this number increased to 29.5 studies (92%; p = 0.125). Our results suggest that CAD significantly improves the sensitivity of PE detection for inexperienced readers with a small but appreciable increase in the rate of false positives.
Zuo, Houjuan; Yan, Jiangtao; Zeng, Hesong; Li, Wenyu; Li, Pengcheng; Liu, Zhengxiang; Cui, Guanglin; Lv, Jiagao; Wang, Daowen; Wang, Hong
2015-01-01
Global longitudinal strain (GLS) measured by 2-D speckle-tracking echocardiography (2-D STE) at rest has been recognized as a sensitive parameter in the detection of significant coronary artery disease (CAD). However, the diagnostic power of 2-D STE in the detection of significant CAD in patients with diabetes mellitus is unknown. Two-dimensional STE features were studied in total of 143 consecutive patients who underwent echocardiography and coronary angiography. Left ventricular global and segmental peak systolic longitudinal strains (PSLSs) were quantified by speckle-tracking imaging. In the presence of obstructive CAD (defined as stenosis ≥75%), global PSLS was significantly lower in patients with diabetes mellitus than in patients without (16.65 ± 2.29% vs. 17.32 ± 2.27%, p < 0.05). Receiver operating characteristic analysis revealed that global PSLS could effectively detect obstructive CAD in patients without diabetes mellitus (cutoff value: -18.35%, sensitivity: 78.8%, specificity: 77.5%). However, global PSLS could detect obstructive CAD in diabetic patients at a lower cutoff value with inadequate sensitivity and specificity (cutoff value: -17.15%; sensitivity: 61.1%, specificity: 52.9%). In addition, the results for segmental PSLS were similar to those for global PSLS. In conclusion, global and segmental PSLSs at rest were significantly lower in patients with both obstructive CAD and diabetes mellitus than in patients with obstructive CAD only; thus, PSLSs at rest might not be a useful parameter in the detection of obstructive CAD in patients with diabetes mellitus. Copyright © 2015 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.
NASA Astrophysics Data System (ADS)
Lieberman, Robert; Kwong, Heston; Liu, Brent; Huang, H. K.
2009-02-01
The chest x-ray radiological features of tuberculosis patients are well documented, and the radiological features that change in response to successful pharmaceutical therapy can be followed with longitudinal studies over time. The patients can also be classified as either responsive or resistant to pharmaceutical therapy based on clinical improvement. We have retrospectively collected time series chest x-ray images of 200 patients diagnosed with tuberculosis receiving the standard pharmaceutical treatment. Computer algorithms can be created to utilize image texture features to assess the temporal changes in the chest x-rays of the tuberculosis patients. This methodology provides a framework for a computer-assisted detection (CAD) system that may provide physicians with the ability to detect poor treatment response earlier in pharmaceutical therapy. Early detection allows physicians to respond with more timely treatment alternatives and improved outcomes. Such a system has the potential to increase treatment efficacy for millions of patients each year.
Excretion of anti-angiogenic proteins in patients with chronic allograft dysfunction.
Moskowitz-Kassai, Eliza; Mackelaite, Lina; Chen, Jun; Patel, Kaushal; Dadhania, Darshana M; Gross, Steven S; Chander, Praveen; Delaney, Vera; Deng, Luqin; Chen, Ligong; Cui, Xiangqin; Suthanthiran, Manikkam; Goligorsky, Michael S
2012-02-01
We have recently documented the appearance of an anti-angiogenic peptide, endorepellin, in the urine of patients with chronic allograft dysfunction (CAD). Here, we analyzed using enzyme-linked immunosorbent assay the excretion of anti-angiogenic peptides endostatin, pigment epithelium-derived factor (PEDF) and Kruppel-like factor-2 (KLF-2), in healthy individuals, patients with stable graft function and patients with various degrees of CAD. In healthy subjects and patients with CAD-0, endostatin, PEDF and KLF-2 excretions were at the level of detection. In contrast, there were significant differences between the patients with CAD-3 and CAD-0, CAD-1 and healthy controls for endostatin and CAD-0 versus CAD-3 for PEDF, but no differences in KLF-2 excretion. Receiver operating characteristic (ROC) curve analyses demonstrated a highly discriminative profile for all three biomarkers: the combination of these parameters offered 83% sensitivity and 90% specificity in distinguishing CAD-0 from CAD-1-3. The quality of these potential biomarkers of CAD was, however, highest in discriminating CAD status in biopsy-proven cases and dropped when CAD-0 was diagnosed based on clinical criteria. In conclusion, these findings indicate the diagnostic potential of urinary detection of endostatin, PEDF and to lesser degree KLF-2 and suggest a mechanistic role played by anti-angiogenic substances in the developing vasculopathy and vascular rarefaction in patients with CAD.
Effectiveness of Computer-Aided Detection in Community Mammography Practice
Abraham, Linn; Taplin, Stephen H.; Geller, Berta M.; Carney, Patricia A.; D’Orsi, Carl; Elmore, Joann G.; Barlow, William E.
2011-01-01
Background Computer-aided detection (CAD) is applied during screening mammography for millions of US women annually, although it is uncertain whether CAD improves breast cancer detection when used by community radiologists. Methods We investigated the association between CAD use during film-screen screening mammography and specificity, sensitivity, positive predictive value, cancer detection rates, and prognostic characteristics of breast cancers (stage, size, and node involvement). Records from 684 956 women who received more than 1.6 million film-screen mammograms at Breast Cancer Surveillance Consortium facilities in seven states in the United States from 1998 to 2006 were analyzed. We used random-effects logistic regression to estimate associations between CAD and specificity (true-negative examinations among women without breast cancer), sensitivity (true-positive examinations among women with breast cancer diagnosed within 1 year of mammography), and positive predictive value (breast cancer diagnosed after positive mammograms) while adjusting for mammography registry, patient age, time since previous mammography, breast density, use of hormone replacement therapy, and year of examination (1998–2002 vs 2003–2006). All statistical tests were two-sided. Results Of 90 total facilities, 25 (27.8%) adopted CAD and used it for an average of 27.5 study months. In adjusted analyses, CAD use was associated with statistically significantly lower specificity (OR = 0.87, 95% confidence interval [CI] = 0.85 to 0.89, P < .001) and positive predictive value (OR = 0.89, 95% CI = 0.80 to 0.99, P = .03). A non-statistically significant increase in overall sensitivity with CAD (OR = 1.06, 95% CI = 0.84 to 1.33, P = .62) was attributed to increased sensitivity for ductal carcinoma in situ (OR = 1.55, 95% CI = 0.83 to 2.91; P = .17), although sensitivity for invasive cancer was similar with or without CAD (OR = 0.96, 95% CI = 0.75 to 1.24; P = .77). CAD was not associated with higher breast cancer detection rates or more favorable stage, size, or lymph node status of invasive breast cancer. Conclusion CAD use during film-screen screening mammography in the United States is associated with decreased specificity but not with improvement in the detection rate or prognostic characteristics of invasive breast cancer. PMID:21795668
NASA Astrophysics Data System (ADS)
Mazzetti, S.; Giannini, V.; Russo, F.; Regge, D.
2018-05-01
Computer-aided diagnosis (CAD) systems are increasingly being used in clinical settings to report multi-parametric magnetic resonance imaging (mp-MRI) of the prostate. Usually, CAD systems automatically highlight cancer-suspicious regions to the radiologist, reducing reader variability and interpretation errors. Nevertheless, implementing this software requires the selection of which mp-MRI parameters can best discriminate between malignant and non-malignant regions. To exploit functional information, some parameters are derived from dynamic contrast-enhanced (DCE) acquisitions. In particular, much CAD software employs pharmacokinetic features, such as K trans and k ep, derived from the Tofts model, to estimate a likelihood map of malignancy. However, non-pharmacokinetic models can be also used to describe DCE-MRI curves, without any requirement for prior knowledge or measurement of the arterial input function, which could potentially lead to large errors in parameter estimation. In this work, we implemented an empirical function derived from the phenomenological universalities (PUN) class to fit DCE-MRI. The parameters of the PUN model are used in combination with T2-weighted and diffusion-weighted acquisitions to feed a support vector machine classifier to produce a voxel-wise malignancy likelihood map of the prostate. The results were all compared to those for a CAD system based on Tofts pharmacokinetic features to describe DCE-MRI curves, using different quality aspects of image segmentation, while also evaluating the number and size of false positive (FP) candidate regions. This study included 61 patients with 70 biopsy-proven prostate cancers (PCa). The metrics used to evaluate segmentation quality between the two CAD systems were not statistically different, although the PUN-based CAD reported a lower number of FP, with reduced size compared to the Tofts-based CAD. In conclusion, the CAD software based on PUN parameters is a feasible means with which to detect PCa, without affecting segmentation quality, and hence it could be successfully applied in clinical settings, improving the automated diagnosis process and reducing computational complexity.
Mazurowski, Maciej A; Zurada, Jacek M; Tourassi, Georgia D
2009-07-01
Ensemble classifiers have been shown efficient in multiple applications. In this article, the authors explore the effectiveness of ensemble classifiers in a case-based computer-aided diagnosis system for detection of masses in mammograms. They evaluate two general ways of constructing subclassifiers by resampling of the available development dataset: Random division and random selection. Furthermore, they discuss the problem of selecting the ensemble size and propose two adaptive incremental techniques that automatically select the size for the problem at hand. All the techniques are evaluated with respect to a previously proposed information-theoretic CAD system (IT-CAD). The experimental results show that the examined ensemble techniques provide a statistically significant improvement (AUC = 0.905 +/- 0.024) in performance as compared to the original IT-CAD system (AUC = 0.865 +/- 0.029). Some of the techniques allow for a notable reduction in the total number of examples stored in the case base (to 1.3% of the original size), which, in turn, results in lower storage requirements and a shorter response time of the system. Among the methods examined in this article, the two proposed adaptive techniques are by far the most effective for this purpose. Furthermore, the authors provide some discussion and guidance for choosing the ensemble parameters.
Quantitative Digital Tomosynthesis Mammography for Improved Breast Cancer Detection and Diagnosis
2008-04-01
include breast-shape slabs consisted of breast- tissue-equivalent materials, i.e. heterogeneous mixture of fibroglandular-tissue- mimicking material. We...collected previ- ously in the Department of Radiology at the University of Michigan for our CAD study.46 The resulting mean effi- ciency ratio for 96 CC...may obscure the characteristics of mass margins. Development of CAD systems for DBT is still at an early stage. In this preliminary study, we compared
Gadolinium Enhanced MR Coronary Vessel Wall Imaging at 3.0 Tesla.
Kelle, Sebastian; Schlendorf, Kelly; Hirsch, Glenn A; Gerstenblith, Gary; Fleck, Eckart; Weiss, Robert G; Stuber, Matthias
2010-10-11
Purpose. We evaluated the influence of the time between low-dose gadolinium (Gd) contrast administration and coronary vessel wall enhancement (LGE) detected by 3T magnetic resonance imaging (MRI) in healthy subjects and patients with coronary artery disease (CAD). Materials and Methods. Four healthy subjects (4 men, mean age 29 ± 3 years and eleven CAD patients (6 women, mean age 61 ± 10 years) were studied on a commercial 3.0 Tesla (T) whole-body MR imaging system (Achieva 3.0 T; Philips, Best, The Netherlands). T1-weighted inversion-recovery coronary magnetic resonance imaging (MRI) was repeated up to 75 minutes after administration of low-dose Gadolinium (Gd) (0.1 mmol/kg Gd-DTPA). Results. LGE was seen in none of the healthy subjects, however in all of the CAD patients. In CAD patients, fifty-six of 62 (90.3%) segments showed LGE of the coronary artery vessel wall at time-interval 1 after contrast. At time-interval 2, 34 of 42 (81.0%) and at time-interval 3, 29 of 39 evaluable segments (74.4%) were enhanced. Conclusion. In this work, we demonstrate LGE of the coronary artery vessel wall using 3.0 T MRI after a single, low-dose Gd contrast injection in CAD patients but not in healthy subjects. In the majority of the evaluated coronary segments in CAD patients, LGE of the coronary vessel wall was already detectable 30-45 minutes after administration of the contrast agent.
Yassin, Nisreen I R; Omran, Shaimaa; El Houby, Enas M F; Allam, Hemat
2018-03-01
The high incidence of breast cancer in women has increased significantly in the recent years. Physician experience of diagnosing and detecting breast cancer can be assisted by using some computerized features extraction and classification algorithms. This paper presents the conduction and results of a systematic review (SR) that aims to investigate the state of the art regarding the computer aided diagnosis/detection (CAD) systems for breast cancer. The SR was conducted using a comprehensive selection of scientific databases as reference sources, allowing access to diverse publications in the field. The scientific databases used are Springer Link (SL), Science Direct (SD), IEEE Xplore Digital Library, and PubMed. Inclusion and exclusion criteria were defined and applied to each retrieved work to select those of interest. From 320 studies retrieved, 154 studies were included. However, the scope of this research is limited to scientific and academic works and excludes commercial interests. This survey provides a general analysis of the current status of CAD systems according to the used image modalities and the machine learning based classifiers. Potential research studies have been discussed to create a more objective and efficient CAD systems. Copyright © 2017 Elsevier B.V. All rights reserved.
Cymerman, Rachel M; Skolnick, Adam H; Cole, William J; Nabati, Camellia; Curcio, Christine A; Smith, R Theodore
2016-11-01
Reticular macular disease (RMD) is the highest risk form of early age-related macular degeneration and also specifically confers decreased longevity. However, because RMD requires advanced retinal imaging for adequate detection of its characteristic subretinal drusenoid deposits (SDD), it has not yet been completely studied with respect to coronary artery disease (CAD), the leading cause of death in the developed world. Because CAD appears in middle age, our purpose was to screen patients aged 45-80 years, documented either with or without CAD, to determine if CAD is associated with RMD. A prospective cohort study of patients with documented CAD status and no known retinal disease in a clinical practice setting at one institution. Subjects and Controls: A number of 76 eyes from 38 consecutive patients (23 with documented CAD, 15 controls documented without CAD; 47.4% female; mean age 66.7 years). Patients were imaged with near-infrared reflectance/spectral domain optical coherence tomography and assessed in masked fashion by two graders for the presence of SDD lesions of RMD and soft drusen. Presence or absence of RMD/SDD and soft drusen. RMD was more frequent in patients with CAD versus those without (Relative Risk [RR] = 2.1, CI = 1.08-3.95, P = 0.03). There was no association of CAD with soft drusen. A specific relationship between CAD and RMD suggests common systemic causes for both and warrants further study.
NASA Astrophysics Data System (ADS)
de Oliveira, Helder C. R.; Mencattini, Arianna; Casti, Paola; Martinelli, Eugenio; di Natale, Corrado; Catani, Juliana H.; de Barros, Nestor; Melo, Carlos F. E.; Gonzaga, Adilson; Vieira, Marcelo A. C.
2018-02-01
This paper proposes a method to reduce the number of false-positives (FP) in a computer-aided detection (CAD) scheme for automated detection of architectural distortion (AD) in digital mammography. AD is a subtle contraction of breast parenchyma that may represent an early sign of breast cancer. Due to its subtlety and variability, AD is more difficult to detect compared to microcalcifications and masses, and is commonly found in retrospective evaluations of false-negative mammograms. Several computer-based systems have been proposed for automated detection of AD in breast images. The usual approach is automatically detect possible sites of AD in a mammographic image (segmentation step) and then use a classifier to eliminate the false-positives and identify the suspicious regions (classification step). This paper focus on the optimization of the segmentation step to reduce the number of FPs that is used as input to the classifier. The proposal is to use statistical measurements to score the segmented regions and then apply a threshold to select a small quantity of regions that should be submitted to the classification step, improving the detection performance of a CAD scheme. We evaluated 12 image features to score and select suspicious regions of 74 clinical Full-Field Digital Mammography (FFDM). All images in this dataset contained at least one region with AD previously marked by an expert radiologist. The results showed that the proposed method can reduce the false positives of the segmentation step of the CAD scheme from 43.4 false positives (FP) per image to 34.5 FP per image, without increasing the number of false negatives.
Lesion classification using clinical and visual data fusion by multiple kernel learning
NASA Astrophysics Data System (ADS)
Kisilev, Pavel; Hashoul, Sharbell; Walach, Eugene; Tzadok, Asaf
2014-03-01
To overcome operator dependency and to increase diagnosis accuracy in breast ultrasound (US), a lot of effort has been devoted to developing computer-aided diagnosis (CAD) systems for breast cancer detection and classification. Unfortunately, the efficacy of such CAD systems is limited since they rely on correct automatic lesions detection and localization, and on robustness of features computed based on the detected areas. In this paper we propose a new approach to boost the performance of a Machine Learning based CAD system, by combining visual and clinical data from patient files. We compute a set of visual features from breast ultrasound images, and construct the textual descriptor of patients by extracting relevant keywords from patients' clinical data files. We then use the Multiple Kernel Learning (MKL) framework to train SVM based classifier to discriminate between benign and malignant cases. We investigate different types of data fusion methods, namely, early, late, and intermediate (MKL-based) fusion. Our database consists of 408 patient cases, each containing US images, textual description of complaints and symptoms filled by physicians, and confirmed diagnoses. We show experimentally that the proposed MKL-based approach is superior to other classification methods. Even though the clinical data is very sparse and noisy, its MKL-based fusion with visual features yields significant improvement of the classification accuracy, as compared to the image features only based classifier.
The Handbook of Medical Image Perception and Techniques
NASA Astrophysics Data System (ADS)
Samei, Ehsan; Krupinski, Elizabeth
2014-07-01
1. Medical image perception Ehsan Samei and Elizabeth Krupinski; Part I. Historical Reflections and Theoretical Foundations: 2. A short history of image perception in medical radiology Harold Kundel and Calvin Nodine; 3. Spatial vision research without noise Arthur Burgess; 4. Signal detection theory, a brief history Arthur Burgess; 5. Signal detection in radiology Arthur Burgess; 6. Lessons from dinners with the giants of modern image science Robert Wagner; Part II. Science of Image Perception: 7. Perceptual factors in reading medical images Elizabeth Krupinski; 8. Cognitive factors in reading medical images David Manning; 9. Satisfaction of search in traditional radiographic imaging Kevin Berbaum, Edmund Franken, Robert Caldwell and Kevin Schartz; 10. The role of expertise in radiologic image interpretation Calvin Nodine and Claudia Mello-Thoms; 11. A primer of image quality and its perceptual relevance Robert Saunders and Ehsan Samei; 12. Beyond the limitations of human vision Maria Petrou; Part III. Perception Metrology: 13. Logistical issues in designing perception experiments Ehsan Samei and Xiang Li; 14. ROC analysis: basic concepts and practical applications Georgia Tourassi; 15. Multi-reader ROC Steve Hillis; 16. Recent developments in FROC methodology Dev Chakraborty; 17. Observer models as a surrogate to perception experiments Craig Abbey and Miguel Eckstein; 18. Implementation of observer models Matthew Kupinski; Part IV. Decision Support and Computer Aided Detection: 19. CAD: an image perception perspective Maryellen Giger and Weijie Chen; 20. Common designs of CAD studies Yulei Jiang; 21. Perceptual effect of CAD in reading chest images Matthew Freedman and Teresa Osicka; 22. Perceptual issues in mammography and CAD Michael Ulissey; 23. How perceptual factors affect the use and accuracy of CAD for interpretation of CT images Ronald Summers; 24. CAD: risks and benefits for radiologists' decisions Eugenio Alberdi, Andrey Povyakalo, Lorenzo Strigini and Peter Ayton; Part V. Optimization and Practical Issues: 25. Optimization of 2D and 3D radiographic systems Jeff Siewerdson; 26. Applications of AFC methodology in optimization of CT imaging systems Kent Ogden and Walter Huda; 27. Perceptual issues in reading mammograms Margarita Zuley; 28. Perceptual optimization of display processing techniques Richard Van Metter; 29. Optimization of display systems Elizabeth Krupinski and Hans Roehrig; 30. Ergonomic radiologist workplaces in the PACS environment Carl Zylack; Part VI. Epilogue: 31. Future prospects of medical image perception Ehsan Samei and Elizabeth Krupinski; Index.
The Handbook of Medical Image Perception and Techniques
NASA Astrophysics Data System (ADS)
Samei, Ehsan; Krupinski, Elizabeth
2009-12-01
1. Medical image perception Ehsan Samei and Elizabeth Krupinski; Part I. Historical Reflections and Theoretical Foundations: 2. A short history of image perception in medical radiology Harold Kundel and Calvin Nodine; 3. Spatial vision research without noise Arthur Burgess; 4. Signal detection theory, a brief history Arthur Burgess; 5. Signal detection in radiology Arthur Burgess; 6. Lessons from dinners with the giants of modern image science Robert Wagner; Part II. Science of Image Perception: 7. Perceptual factors in reading medical images Elizabeth Krupinski; 8. Cognitive factors in reading medical images David Manning; 9. Satisfaction of search in traditional radiographic imaging Kevin Berbaum, Edmund Franken, Robert Caldwell and Kevin Schartz; 10. The role of expertise in radiologic image interpretation Calvin Nodine and Claudia Mello-Thoms; 11. A primer of image quality and its perceptual relevance Robert Saunders and Ehsan Samei; 12. Beyond the limitations of human vision Maria Petrou; Part III. Perception Metrology: 13. Logistical issues in designing perception experiments Ehsan Samei and Xiang Li; 14. ROC analysis: basic concepts and practical applications Georgia Tourassi; 15. Multi-reader ROC Steve Hillis; 16. Recent developments in FROC methodology Dev Chakraborty; 17. Observer models as a surrogate to perception experiments Craig Abbey and Miguel Eckstein; 18. Implementation of observer models Matthew Kupinski; Part IV. Decision Support and Computer Aided Detection: 19. CAD: an image perception perspective Maryellen Giger and Weijie Chen; 20. Common designs of CAD studies Yulei Jiang; 21. Perceptual effect of CAD in reading chest images Matthew Freedman and Teresa Osicka; 22. Perceptual issues in mammography and CAD Michael Ulissey; 23. How perceptual factors affect the use and accuracy of CAD for interpretation of CT images Ronald Summers; 24. CAD: risks and benefits for radiologists' decisions Eugenio Alberdi, Andrey Povyakalo, Lorenzo Strigini and Peter Ayton; Part V. Optimization and Practical Issues: 25. Optimization of 2D and 3D radiographic systems Jeff Siewerdson; 26. Applications of AFC methodology in optimization of CT imaging systems Kent Ogden and Walter Huda; 27. Perceptual issues in reading mammograms Margarita Zuley; 28. Perceptual optimization of display processing techniques Richard Van Metter; 29. Optimization of display systems Elizabeth Krupinski and Hans Roehrig; 30. Ergonomic radiologist workplaces in the PACS environment Carl Zylack; Part VI. Epilogue: 31. Future prospects of medical image perception Ehsan Samei and Elizabeth Krupinski; Index.
Paraskevaidis, Ioannis A; Tsougos, Elias; Panou, Fotios; Dagres, Nikolaos; Karatzas, Dimitrios; Boutati, Eleni; Varounis, Christos; Kremastinos, Dimitrios Th
2010-03-01
Diabetes mellitus is considered as an equivalent of coronary artery disease (CAD). Aim of the study was to investigate whether in asymptomatic patients with type II diabetes, diastolic stress echocardiography may represent an alternative tool for the detection of CAD. The study population consisted of 105 patients with diabetes mellitus (age 61+/-9 years, 26% female, duration of diabetes 37+/-14 months). We performed an exercise stress test, followed by an echo-study and a single-positron emission tomography. Coronary angiography was performed within 1 month. Coronary angiography revealed a coronary artery stenosis of at least 70% in 72 patients (69%, CAD group), while the remaining formed the non-CAD group. Exercise induced an increase of both E/E' lateral and septal ratios as well as their average in the CAD group and on the contrary a decrease of these ratios in the non-CAD group. Receiver operating curve analysis for discrimination between patients with and without obstructive CAD showed an optimal cut-off value of -0.0708 for the exercise-induced change of E/E' average (area under curve 0.892, P<0.001). Sensitivities of scintigraphy and of diastolic stress echocardiography for detection of CAD were 75.0 and 93.1%, respectively; specificity was 78.8% for both methods. In asymptomatic patients, sensitivities of scintigraphy and diastolic stress echocardiography were 76.9 and 92.3%; specificity of both was 80%. In patients with type II diabetes, diastolic stress echocardiography, by means of E/E' ratio exercise-induced changes, can be used for the diagnosis and severity of CAD and for the detection of occult myocardial ischemia.
Baker, Mark E; Bogoni, Luca; Obuchowski, Nancy A; Dass, Chandra; Kendzierski, Renee M; Remer, Erick M; Einstein, David M; Cathier, Pascal; Jerebko, Anna; Lakare, Sarang; Blum, Andrew; Caroline, Dina F; Macari, Michael
2007-10-01
To determine whether computer-aided detection (CAD) applied to computed tomographic (CT) colonography can help improve sensitivity of polyp detection by less-experienced radiologist readers, with colonoscopy or consensus used as the reference standard. The release of the CT colonographic studies was approved by the individual institutional review boards of each institution. Institutions from the United States were HIPAA compliant. Written informed consent was waived at all institutions. The CT colonographic studies in 30 patients from six institutions were collected; 24 images depicted at least one confirmed polyp 6 mm or larger (39 total polyps) and six depicted no polyps. By using an investigational software package, seven less-experienced readers from two institutions evaluated the CT colonographic images and marked or scored polyps by using a five-point scale before and after CAD. The time needed to interpret the CT colonographic findings without CAD and then to re-evaluate them with CAD was recorded. For each reader, the McNemar test, adjusted for clustered data, was used to compare sensitivities for readers without and with CAD; a Wilcoxon signed-rank test was used to analyze the number of false-positive results per patient. The average sensitivity of the seven readers for polyp detection was significantly improved with CAD-from 0.810 to 0.908 (P=.0152). The number of false-positive results per patient without and with CAD increased from 0.70 to 0.96 (95% confidence interval for the increase: -0.39, 0.91). The mean total time for the readings was 17 minutes 54 seconds; for interpretation of CT colonographic findings alone, the mean time was 14 minutes 16 seconds; and for review of CAD findings, the mean time was 3 minutes 38 seconds. Results of this feasibility study suggest that CAD for CT colonography significantly improves per-polyp detection for less-experienced readers. Copyright (c) RSNA, 2007.
NASA Astrophysics Data System (ADS)
Traverso, A.; Lopez Torres, E.; Fantacci, M. E.; Cerello, P.
2017-05-01
Lung cancer is one of the most lethal types of cancer, because its early diagnosis is not good enough. In fact, the detection of pulmonary nodule, potential lung cancers, in Computed Tomography scans is a very challenging and time-consuming task for radiologists. To support radiologists, researchers have developed Computer-Aided Diagnosis (CAD) systems for the automated detection of pulmonary nodules in chest Computed Tomography scans. Despite the high level of technological developments and the proved benefits on the overall detection performance, the usage of Computer-Aided Diagnosis in clinical practice is far from being a common procedure. In this paper we investigate the causes underlying this discrepancy and present a solution to tackle it: the M5L WEB- and Cloud-based on-demand Computer-Aided Diagnosis. In addition, we prove how the combination of traditional imaging processing techniques with state-of-art advanced classification algorithms allows to build a system whose performance could be much larger than any Computer-Aided Diagnosis developed so far. This outcome opens the possibility to use the CAD as clinical decision support for radiologists.
A combined system for 3D printing cybersecurity
NASA Astrophysics Data System (ADS)
Straub, Jeremy
2017-06-01
Previous work has discussed the impact of cybersecurity breaches on 3D printed objects. Multiple attack types that could weaken objects, make them unsuitable for certain applications and even create safety hazards have been presented. This paper considers a visible light sensing-based verification system's efficacy as a means of thwarting cybersecurity threats to 3D printing. This system detects discrepancies between expected and actual printed objects (based on an independent pristine CAD model). Whether reliance on an independent CAD model is appropriate is also considered. The future of 3D printing is projected and the importance of cybersecurity in this future is discussed.
Neural networks: Application to medical imaging
NASA Technical Reports Server (NTRS)
Clarke, Laurence P.
1994-01-01
The research mission is the development of computer assisted diagnostic (CAD) methods for improved diagnosis of medical images including digital x-ray sensors and tomographic imaging modalities. The CAD algorithms include advanced methods for adaptive nonlinear filters for image noise suppression, hybrid wavelet methods for feature segmentation and enhancement, and high convergence neural networks for feature detection and VLSI implementation of neural networks for real time analysis. Other missions include (1) implementation of CAD methods on hospital based picture archiving computer systems (PACS) and information networks for central and remote diagnosis and (2) collaboration with defense and medical industry, NASA, and federal laboratories in the area of dual use technology conversion from defense or aerospace to medicine.
Eom, Han Young; Park, So-Young; Kim, Min Kyung; Suh, Joon Hyuk; Yeom, Hyesun; Min, Jung Won; Kim, Unyong; Lee, Jeongmi; Youm, Jeong-Rok; Han, Sang Beom
2010-06-25
Saikosaponins are triterpene saponins derived from the roots of Bupleurum falcatum L. (Umbelliferae), which has been traditionally used to treat fever, inflammation, liver diseases, and nephritis. It is difficult to analyze saikosaponins using HPLC-UV due to the lack of chromophores. Therefore, evaporative light scattering detection (ELSD) is used as a valuable alternative to UV detection. More recently, a charged aerosol detection (CAD) method has been developed to improve the sensitivity and reproducibility of ELSD. In this study, we compared CAD and ELSD methods in the simultaneous analysis of 10 saikosaponins, including saikosaponins-A, -B(1), -B(2), -B(3), -B(4), -C, -D, -G, -H and -I. A mixture of the 10 saikosaponins was injected into the Ascentis Express C18 column (100 mm x 4.6 mm, 2.7 microm) with gradient elution and detection with CAD and ELSD by splitting. We examined various factors that could affect the sensitivity of the detectors including various concentrations of additives, pH and flow rate of the mobile phase, purity of nitrogen gas and the CAD range. The sensitivity was determined based on the signal-to-noise ratio. The best sensitivity for CAD was achieved with 0.1 mM ammonium acetate at pH 4.0 in the mobile phase with a flow rate of 1.0 mL/min, and the CAD range at 100 pA, whereas that for ELSD was achieved with 0.01% acetic acid in the mobile phase with a flow rate at 0.8 mL/min. The purity of the nitrogen gas had only minor effects on the sensitivities of both detectors. Finally, the sensitivity for CAD was two to six times better than that of ELSD. Taken together, these results suggest that CAD provides a more sensitive analysis of the 10 saikosaponins than does ELSD. Copyright 2010 Elsevier B.V. All rights reserved.
Hirose, Tomohiro; Nitta, Norihisa; Shiraishi, Junji; Nagatani, Yukihiro; Takahashi, Masashi; Murata, Kiyoshi
2008-12-01
The aim of this study was to evaluate the usefulness of computer-aided diagnosis (CAD) software for the detection of lung nodules on multidetector-row computed tomography (MDCT) in terms of improvement in radiologists' diagnostic accuracy in detecting lung nodules, using jackknife free-response receiver-operating characteristic (JAFROC) analysis. Twenty-one patients (6 without and 15 with lung nodules) were selected randomly from 120 consecutive thoracic computed tomographic examinations. The gold standard for the presence or absence of nodules in the observer study was determined by consensus of two radiologists. Six expert radiologists participated in a free-response receiver operating characteristic study for the detection of lung nodules on MDCT, in which cases were interpreted first without and then with the output of CAD software. Radiologists were asked to indicate the locations of lung nodule candidates on the monitor with their confidence ratings for the presence of lung nodules. The performance of the CAD software indicated that the sensitivity in detecting lung nodules was 71.4%, with 0.95 false-positive results per case. When radiologists used the CAD software, the average sensitivity improved from 39.5% to 81.0%, with an increase in the average number of false-positive results from 0.14 to 0.89 per case. The average figure-of-merit values for the six radiologists were 0.390 without and 0.845 with the output of the CAD software, and there was a statistically significant difference (P < .0001) using the JAFROC analysis. The CAD software for the detection of lung nodules on MDCT has the potential to assist radiologists by increasing their accuracy.
Use of CAD systems in design of Space Station and space robots
NASA Technical Reports Server (NTRS)
Dwivedi, Suren N.; Yadav, P.; Jones, Gary; Travis, Elmer W.
1988-01-01
The evolution of CAD systems is traced. State-of-the-art CAD systems are reviewed and various advanced CAD facilities and supplementing systems being used at NASA-Goddard are described. CAD hardware, computer software, and protocols are detailed.
Computer-aided diagnosis (CAD) for colonoscopy
NASA Astrophysics Data System (ADS)
Gu, Jia; Poirson, Allen
2007-03-01
Colorectal cancer is the second leading cause of cancer deaths, and ranks third for new cancer cases and cancer mortality for both men and women. However, its death rate can be dramatically reduced by appropriate treatment when early detection is available. The purpose of colonoscopy is to identify and assess the severity of lesions, which may be flat or protruding. Due to the subjective nature of the examination, colonoscopic proficiency is highly variable and dependent upon the colonoscopist's knowledge and experience. An automated image processing system providing an objective, rapid, and inexpensive analysis of video from a standard colonoscope could provide a valuable tool for screening and diagnosis. In this paper, we present the design, functionality and preliminary results of its Computer-Aided-Diagnosis (CAD) system for colonoscopy - ColonoCAD TM. ColonoCAD is a complex multi-sensor, multi-data and multi-algorithm image processing system, incorporating data management and visualization, video quality assessment and enhancement, calibration, multiple view based reconstruction, feature extraction and classification. As this is a new field in medical image processing, our hope is that this paper will provide the framework to encourage and facilitate collaboration and discussion between industry, academia, and medical practitioners.
Mazurowski, Maciej A.; Zurada, Jacek M.; Tourassi, Georgia D.
2009-01-01
Ensemble classifiers have been shown efficient in multiple applications. In this article, the authors explore the effectiveness of ensemble classifiers in a case-based computer-aided diagnosis system for detection of masses in mammograms. They evaluate two general ways of constructing subclassifiers by resampling of the available development dataset: Random division and random selection. Furthermore, they discuss the problem of selecting the ensemble size and propose two adaptive incremental techniques that automatically select the size for the problem at hand. All the techniques are evaluated with respect to a previously proposed information-theoretic CAD system (IT-CAD). The experimental results show that the examined ensemble techniques provide a statistically significant improvement (AUC=0.905±0.024) in performance as compared to the original IT-CAD system (AUC=0.865±0.029). Some of the techniques allow for a notable reduction in the total number of examples stored in the case base (to 1.3% of the original size), which, in turn, results in lower storage requirements and a shorter response time of the system. Among the methods examined in this article, the two proposed adaptive techniques are by far the most effective for this purpose. Furthermore, the authors provide some discussion and guidance for choosing the ensemble parameters. PMID:19673196
Taylor, Stuart A; Charman, Susan C; Lefere, Philippe; McFarland, Elizabeth G; Paulson, Erik K; Yee, Judy; Aslam, Rizwan; Barlow, John M; Gupta, Arun; Kim, David H; Miller, Chad M; Halligan, Steve
2008-02-01
To prospectively compare the diagnostic performance and time efficiency of both second and concurrent computer-aided detection (CAD) reading paradigms for retrospectively obtained computed tomographic (CT) colonography data sets by using consensus reading (three radiologists) of colonoscopic findings as a reference standard. Ethical permission, HIPAA compliance (for U.S. institutions), and patient consent were obtained from all institutions for use of CT colonography data sets in this study. Ten radiologists each read 25 CT colonography data sets (12 men, 13 women; mean age, 61 years) containing 69 polyps (28 were 1-5 mm, 41 were >or=6 mm) by using workstations integrated with CAD software. Reading was randomized to either "second read" CAD (applied only after initial unassisted assessment) or "concurrent read" CAD (applied at the start of assessment). Data sets were reread 6 weeks later by using the opposing paradigm. Polyp sensitivity and reading times were compared by using multilevel logistic and linear regression, respectively. Receiver operating characteristic (ROC) curves were generated. Compared with the unassisted read, odds of improved polyp (>or=6 mm) detection were 1.5 (95% confidence interval [CI]: 1.0, 2.2) and 1.3 (95% CI: 0.9, 1.9) by using CAD as second and concurrent reader, respectively. Detection odds by using CAD concurrently were 0.87 (95% CI: 0.59, 1.3) and 0.76 (95% CI: 0.57, 1.01) those of second read CAD, excluding and including polyps 1-5 mm, respectively. The concurrent read took 2.9 minutes (95% CI: -3.8, -1.9) less than did second read. The mean areas under the ROC curve (95% CI) for the unassisted read, second read CAD, and concurrent read CAD were 0.83 (95% CI: 0.78, 0.87), 0.86 (95% CI: 0.82, 0.90), and 0.88 (95% CI: 0.83, 0.92), respectively. CAD is more time efficient when used concurrently than when used as a second reader, with similar sensitivity for polyps 6 mm or larger. However, use of second read CAD maximizes sensitivity, particularly for smaller lesions. (c) RSNA, 2007.
A new CAD approach for improving efficacy of cancer screening
NASA Astrophysics Data System (ADS)
Zheng, Bin; Qian, Wei; Li, Lihua; Pu, Jiantao; Kang, Yan; Lure, Fleming; Tan, Maxine; Qiu, Yuchen
2015-03-01
Since performance and clinical utility of current computer-aided detection (CAD) schemes of detecting and classifying soft tissue lesions (e.g., breast masses and lung nodules) is not satisfactory, many researchers in CAD field call for new CAD research ideas and approaches. The purpose of presenting this opinion paper is to share our vision and stimulate more discussions of how to overcome or compensate the limitation of current lesion-detection based CAD schemes in the CAD research community. Since based on our observation that analyzing global image information plays an important role in radiologists' decision making, we hypothesized that using the targeted quantitative image features computed from global images could also provide highly discriminatory power, which are supplementary to the lesion-based information. To test our hypothesis, we recently performed a number of independent studies. Based on our published preliminary study results, we demonstrated that global mammographic image features and background parenchymal enhancement of breast MR images carried useful information to (1) predict near-term breast cancer risk based on negative screening mammograms, (2) distinguish between true- and false-positive recalls in mammography screening examinations, and (3) classify between malignant and benign breast MR examinations. The global case-based CAD scheme only warns a risk level of the cases without cueing a large number of false-positive lesions. It can also be applied to guide lesion-based CAD cueing to reduce false-positives but enhance clinically relevant true-positive cueing. However, before such a new CAD approach is clinically acceptable, more work is needed to optimize not only the scheme performance but also how to integrate with lesion-based CAD schemes in the clinical practice.
An intercomparison of five ammonia measurement techniques
NASA Technical Reports Server (NTRS)
Williams, E. J.; Sandholm, S. T.; Bradshaw, J. D.; Schendel, J. S.; Langford, A. O.; Quinn, P. K.; Lebel, P. J.; Vay, S. A.; Roberts, P. D.; Norton, R. B.
1992-01-01
Results obtained from five techniques for measuring gas-phase ammonia at low concentration in the atmosphere are compared. These methods are: (1) a photofragmentation/laser-induced fluorescence (PF/LIF) instrument; (2) a molybdenum oxide annular denuder sampling/chemiluminescence detection technique; (3) a tungsten oxide denuder sampling/chemiluminescence detection system; (4) a citric-acid-coated denuder sampling/ion chromatographic analysis (CAD/IC) method; and (5) an oxalic-acid-coated filter pack sampling/colorimetric analysis method. It was found that two of the techniques, the PF/LIF and the CAD/IC methods, measured approximately 90 percent of the calculated ammonia added in the spiking tests and agreed very well with each other in the ambient measurements.
Utilizing optical coherence tomography for CAD/CAM of indirect dental restorations
NASA Astrophysics Data System (ADS)
Chityala, Ravishankar; Vidal, Carola; Jones, Robert
Optical Coherence Tomography (OCT) has seen broad application in dentistry including early carious lesion detection and imaging defects in resin composite restorations. This study investigates expanding the clinical usefulness by investigating methods to use OCT for obtaining three-dimensional (3D) digital impressions, which can be integrated to CAD/CAM manufacturing of indirect restorations. 3D surface topography `before' and `after' a cavity preparation was acquired by an intraoral cross polarization swept source OCT (CP-OCT) system with a Micro-Electro-Mechanical System (MEMS) scanning mirror. Image registration and segmentation methods were used to digitally construct a replacement restoration that modeled the original surface morphology of a hydroxyapatite sample. After high resolution additive manufacturing (e.g. polymer 3D printing) of the replacement restoration, micro-CT imaging was performed to examine the marginal adaptation. This study establishes the protocol for further investigation of integrating OCT with CAD/CAM of indirect dental restorations.
NASA Astrophysics Data System (ADS)
Beyer, F.; Zierott, L.; Fallenberg, E. M.; Juergens, K.; Stoeckel, J.; Heindel, W.; Wormanns, D.
2006-03-01
Purpose: To compare sensitivity and reading time when using CAD as second reader resp. concurrent reader. Materials and Methods: Fifty chest MDCT scans due to clinical indication were analysed independently by four radiologists two times: First with CAD as concurrent reader (display of CAD results simultaneously to the primary reading by the radiologist); then after a median of 14 weeks with CAD as second reader (CAD results were shown after completion of a reading session without CAD). A prototype version of Siemens LungCAD (Siemens,Malvern,USA) was used. Sensitivities and reading times for detecting nodules >=4mm of concurrent reading, reading without CAD and second reading were recorded. In a consensus conference false positive findings were eliminated. Student's T-Test was used to compare sensitivities and reading times. Results: 108 true positive nodules were found. Mean sensitivity was .68 for reading without CAD, .68 for concurrent reading and .75 for second reading. Differences of sensitivities were significant between concurrent and second reading (p<.001) resp. reading without CAD and second reading (p=.001). Mean reading time for concurrent reading was significant shorter (274s) compared to reading without CAD (294s;p=.04) and second reading (337sp<.001). New work to be presented: To our knowledge this is the first study that compares sensitivities and reading times between use of CAD as concurrent resp. second reader. Conclusion: CAD can either be used to speed up reading of chest CT cases for pulmonary nodules without loss of sensitivity as concurrent reader -OR (and not AND) to increase sensitivity and reading time as second reader.
Initial versus final fracture of metal-free crowns, analyzed via acoustic emission.
Ereifej, Nadia; Silikas, Nick; Watts, David C
2008-09-01
To discriminate between initial and final fracture failure loads of four metal-free crown systems by the conjoint detection of acoustic emission signals during compressive loading. Teeth were prepared and used for crown construction with four crown systems; Vita Mark II (VM II) (Vita Zahnfabrik), IPS e.max Ceram/CAD (CAD) (Ivoclar-Vivadent), IPS e.max Ceram/ZirCAD (ZirCAD) (Ivoclar-Vivadent) and BelleGlass/EverStick (BGES) (Kerr/Stick Tech Ltd.). All samples were loaded in compression via a Co/Cr maxillary first molar tooth at 0.2mm/min and released acoustic signals were collected and analyzed. A minimum number of 15 crowns per group were loaded to final failure and values of loading at initial and final fracture were compared. Additional four samples per group were loaded till fracture initiation and were fractographically examined under the optical microscope. A lower threshold of 50dB was selected to exclude spurious background signals. Initial fracture forces were significantly lower than those of final fracture (p<0.05) in all groups and initial failure AE amplitudes were lower than those of final fracture. Mean initial fracture force of ZirCAD samples (1029.1N) was higher than those of VMII (744.4N), CAD (808.8 N) and BGES (979.7 N). Final fracture of ZirCAD also occurred at significantly higher force values (2091.7 N) than the rest of the groups; VMII (1120.9 N), CAD (1468.9 N) and BGES (1576.6 N). Significantly higher values of initial failure AE amplitude were found in VMII than CAD and BGES while those of final fracture were similar. All crowns observed under the microscope at initial fracture had signs of failure. Whereas the metal-free crowns examined showed significant variations in final failure loads, acoustic emission data showed that they all manifested initial failures at significantly lower load values.
Computerized breast cancer analysis system using three stage semi-supervised learning method.
Sun, Wenqing; Tseng, Tzu-Liang Bill; Zhang, Jianying; Qian, Wei
2016-10-01
A large number of labeled medical image data is usually a requirement to train a well-performed computer-aided detection (CAD) system. But the process of data labeling is time consuming, and potential ethical and logistical problems may also present complications. As a result, incorporating unlabeled data into CAD system can be a feasible way to combat these obstacles. In this study we developed a three stage semi-supervised learning (SSL) scheme that combines a small amount of labeled data and larger amount of unlabeled data. The scheme was modified on our existing CAD system using the following three stages: data weighing, feature selection, and newly proposed dividing co-training data labeling algorithm. Global density asymmetry features were incorporated to the feature pool to reduce the false positive rate. Area under the curve (AUC) and accuracy were computed using 10 fold cross validation method to evaluate the performance of our CAD system. The image dataset includes mammograms from 400 women who underwent routine screening examinations, and each pair contains either two cranio-caudal (CC) or two mediolateral-oblique (MLO) view mammograms from the right and the left breasts. From these mammograms 512 regions were extracted and used in this study, and among them 90 regions were treated as labeled while the rest were treated as unlabeled. Using our proposed scheme, the highest AUC observed in our research was 0.841, which included the 90 labeled data and all the unlabeled data. It was 7.4% higher than using labeled data only. With the increasing amount of labeled data, AUC difference between using mixed data and using labeled data only reached its peak when the amount of labeled data was around 60. This study demonstrated that our proposed three stage semi-supervised learning can improve the CAD performance by incorporating unlabeled data. Using unlabeled data is promising in computerized cancer research and may have a significant impact for future CAD system applications. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
McKenna, Matthew T.; Wang, Shijun; Nguyen, Tan B.; Burns, Joseph E.; Petrick, Nicholas; Summers, Ronald M.
2012-01-01
Computer-aided detection (CAD) systems have been shown to improve the diagnostic performance of CT colonography (CTC) in the detection of premalignant colorectal polyps. Despite the improvement, the overall system is not optimal. CAD annotations on true lesions are incorrectly dismissed, and false positives are misinterpreted as true polyps. Here, we conduct an observer performance study utilizing distributed human intelligence in the form of anonymous knowledge workers (KWs) to investigate human performance in classifying polyp candidates under different presentation strategies. We evaluated 600 polyp candidates from 50 patients, each case having at least one polyp • 6 mm, from a large database of CTC studies. Each polyp candidate was labeled independently as a true or false polyp by 20 KWs and an expert radiologist. We asked each labeler to determine whether the candidate was a true polyp after looking at a single 3D-rendered image of the candidate and after watching a video fly-around of the candidate. We found that distributed human intelligence improved significantly when presented with the additional information in the video fly-around. We noted that performance degraded with increasing interpretation time and increasing difficulty, but distributed human intelligence performed better than our CAD classifier for “easy” and “moderate” polyp candidates. Further, we observed numerous parallels between the expert radiologist and the KWs. Both showed similar improvement in classification moving from single-image to video interpretation. Additionally, difficulty estimates obtained from the KWs using an expectation maximization algorithm correlated well with the difficulty rating assigned by the expert radiologist. Our results suggest that distributed human intelligence is a powerful tool that will aid in the development of CAD for CTC. PMID:22705287
McKenna, Matthew T; Wang, Shijun; Nguyen, Tan B; Burns, Joseph E; Petrick, Nicholas; Summers, Ronald M
2012-08-01
Computer-aided detection (CAD) systems have been shown to improve the diagnostic performance of CT colonography (CTC) in the detection of premalignant colorectal polyps. Despite the improvement, the overall system is not optimal. CAD annotations on true lesions are incorrectly dismissed, and false positives are misinterpreted as true polyps. Here, we conduct an observer performance study utilizing distributed human intelligence in the form of anonymous knowledge workers (KWs) to investigate human performance in classifying polyp candidates under different presentation strategies. We evaluated 600 polyp candidates from 50 patients, each case having at least one polyp ≥6 mm, from a large database of CTC studies. Each polyp candidate was labeled independently as a true or false polyp by 20 KWs and an expert radiologist. We asked each labeler to determine whether the candidate was a true polyp after looking at a single 3D-rendered image of the candidate and after watching a video fly-around of the candidate. We found that distributed human intelligence improved significantly when presented with the additional information in the video fly-around. We noted that performance degraded with increasing interpretation time and increasing difficulty, but distributed human intelligence performed better than our CAD classifier for "easy" and "moderate" polyp candidates. Further, we observed numerous parallels between the expert radiologist and the KWs. Both showed similar improvement in classification moving from single-image to video interpretation. Additionally, difficulty estimates obtained from the KWs using an expectation maximization algorithm correlated well with the difficulty rating assigned by the expert radiologist. Our results suggest that distributed human intelligence is a powerful tool that will aid in the development of CAD for CTC. Copyright © 2012. Published by Elsevier B.V.
Miszalski-Jamka, Tomasz; Kuntz-Hehner, Stefanie; Schmidt, Harald; Hammerstingl, Christoph; Tiemann, Klaus; Ghanem, Alexander; Troatz, Clemens; Lüderitz, Berndt; Omran, Heyder
2007-07-01
Myocardial contrast echocardiography (MCE) is a new imaging modality for diagnosing coronary artery disease (CAD). The aim of our study was to evaluate feasibility of qualitative myocardial contrast replenishment (RP) assessment during supine bicycle stress MCE and find out cutoff values for such analysis, which could allow accurate detection of CAD. Forty-four consecutive patients, scheduled for coronary angiography (CA) underwent supine bicycle stress two-dimensional echocardiography (2DE). During the same session, MCE was performed at peak stress and post stress. Ultrasound contrast agent (SonoVue) was administered in continuous mode using an infusion pump (BR-INF 100, Bracco Research). Seventeen-segment model of left ventricle was used in analysis. MCE was assessed off-line in terms of myocardial contrast opacification and RP. RP was evaluated on the basis of the number of cardiac cycles required to refill the segment with contrast after its prior destruction with high-power frames. Determination of cutoff values for RP assessment was performed by means of reference intervals and receiver operating characteristic analysis. Quantitative CA was carried out using CAAS system. MCE could be assessed in 42 patients. CA revealed CAD in 25 patients. Calculated cutoff values for RP-analysis (peak-stress RP >3 cardiac cycles and difference between peak stress and post stress RP >0 cardiac cycles) provided sensitive (88%) and accurate (88%) detection of CAD. Sensitivity and accuracy of 2DE were 76% and 79%, respectively. Qualitative RP-analysis based on the number of cardiac cycles required to refill myocardium with contrast is feasible during supine bicycle stress MCE and enables accurate detection of CAD.
Husser, Oliver; Bodí, Vicente; Sanchís, Juan; Mainar, Luis; Núñez, Julio; López-Lereu, María P; Monmeneu, José V; Ruiz, Vicente; Rumiz, Eva; Moratal, David; Chorro, Francisco J; Llácer, Angel
2009-04-01
Dipyridamole stress perfusion cardiovascular magnetic resonance (CMR) is used to detect coronary artery disease (CAD). However, few data are available on the diagnostic value of the systolic dysfunction induced by dipyridamole. This study investigated whether the induction of systolic dysfunction supplements the diagnostic information provided by perfusion imaging in the detection of CAD. Overall, 166 patients underwent dipyridamole CMR and quantitative coronary angiography, with CAD being defined as a stenosis > or =70%. Systolic dysfunction at rest, systolic dysfunction with dipyridamole, induced systolic dysfunction, and stress first-pass perfussion deficit (PD) and delayed enhancement were quantified. In the multivariate analysis, PD (hazard ratio [HR]=1.6; 95% confidence interval [CI], 1.33-1.91;P< .0001) and induced systolic dysfunction (OR=1.8; 95% CI, 1.18-2.28; P< .007) were independently associated with CAD and had a sensitivity and specificity of 92% and 62% and 43% and 96%, respectively. Patients were categorized as having no ischemia (Group 1), PD but no induced systolic dysfunction (Group 2), or induced systolic dysfunction irrespective of PD (Group 3). In Group 3, the prevalence of CAD was higher than in Group 1 or 2 (96% vs. 22% and 79%, respectively; P=.001) and the risk of CAD was two-fold higher than in Group 2 (OR=2.34; 95% CI, 1.07-5.13; P=.034). Compared with Group 2, more hypoperfused segments were observed in Group 3 (6.2+/-2.6 vs. 7.4+/-3.4; P=.044), and more diseased vessels (1.4+/-1.0 vs. 1.8+/-0.9; P=.036). Adding induced systolic dysfunction to perfusion and clinical data improved the multivariate model's C-statistic for predicting CAD (0.81 vs. 0.87; P=.02). Combining induced systolic dysfunction with perfusion imaging increases the diagnostic accuracy of detecting CAD and enables patients with severe ischemia and a high probability of CAD to be identified.
Byars, Sean G; Huang, Qin Qin; Gray, Lesley-Ann; Bakshi, Andrew; Ripatti, Samuli; Abraham, Gad; Stearns, Stephen C; Inouye, Michael
2017-06-01
Traditional genome-wide scans for positive selection have mainly uncovered selective sweeps associated with monogenic traits. While selection on quantitative traits is much more common, very few signals have been detected because of their polygenic nature. We searched for positive selection signals underlying coronary artery disease (CAD) in worldwide populations, using novel approaches to quantify relationships between polygenic selection signals and CAD genetic risk. We identified new candidate adaptive loci that appear to have been directly modified by disease pressures given their significant associations with CAD genetic risk. These candidates were all uniquely and consistently associated with many different male and female reproductive traits suggesting selection may have also targeted these because of their direct effects on fitness. We found that CAD loci are significantly enriched for lifetime reproductive success relative to the rest of the human genome, with evidence that the relationship between CAD and lifetime reproductive success is antagonistic. This supports the presence of antagonistic-pleiotropic tradeoffs on CAD loci and provides a novel explanation for the maintenance and high prevalence of CAD in modern humans. Lastly, we found that positive selection more often targeted CAD gene regulatory variants using HapMap3 lymphoblastoid cell lines, which further highlights the unique biological significance of candidate adaptive loci underlying CAD. Our study provides a novel approach for detecting selection on polygenic traits and evidence that modern human genomes have evolved in response to CAD-induced selection pressures and other early-life traits sharing pleiotropic links with CAD.
NASA Technical Reports Server (NTRS)
Schlegel, Todd T.; Delgado, Reynolds; Poulin, Greg; Starc, Vito; Arenare, Brian; Rahman, M. A.
2006-01-01
Resting conventional ECG is notoriously insensitive for detecting coronary artery disease (CAD) and only nominally useful in screening for cardiomyopathy (CM). Similarly, conventional exercise stress test ECG is both time- and labor-consuming and its accuracy in identifying CAD is suboptimal for use in population screening. We retrospectively investigated the accuracy of several advanced resting electrocardiographic (ECG) parameters, both alone and in combination, for detecting CAD and cardiomyopathy (CM).
NASA Astrophysics Data System (ADS)
Jiang, Guodong; Fan, Ming; Li, Lihua
2016-03-01
Mammography is the gold standard for breast cancer screening, reducing mortality by about 30%. The application of a computer-aided detection (CAD) system to assist a single radiologist is important to further improve mammographic sensitivity for breast cancer detection. In this study, a design and realization of the prototype for remote diagnosis system in mammography based on cloud platform were proposed. To build this system, technologies were utilized including medical image information construction, cloud infrastructure and human-machine diagnosis model. Specifically, on one hand, web platform for remote diagnosis was established by J2EE web technology. Moreover, background design was realized through Hadoop open-source framework. On the other hand, storage system was built up with Hadoop distributed file system (HDFS) technology which enables users to easily develop and run on massive data application, and give full play to the advantages of cloud computing which is characterized by high efficiency, scalability and low cost. In addition, the CAD system was realized through MapReduce frame. The diagnosis module in this system implemented the algorithms of fusion of machine and human intelligence. Specifically, we combined results of diagnoses from doctors' experience and traditional CAD by using the man-machine intelligent fusion model based on Alpha-Integration and multi-agent algorithm. Finally, the applications on different levels of this system in the platform were also discussed. This diagnosis system will have great importance for the balanced health resource, lower medical expense and improvement of accuracy of diagnosis in basic medical institutes.
Application of the LDM algorithm to identify small lung nodules on low-dose MSCT scans
NASA Astrophysics Data System (ADS)
Zhao, Binsheng; Ginsberg, Michelle S.; Lefkowitz, Robert A.; Jiang, Li; Cooper, Cathleen; Schwartz, Lawrence H.
2004-05-01
In this work, we present a computer-aided detection (CAD) algorithm for small lung nodules on low-dose MSCT images. With this technique, identification of potential lung nodules is carried out with a local density maximum (LDM) algorithm, followed by reduction of false positives from the nodule candidates using task-specific 2-D/3-D features along with a knowledge-based nodule inclusion/exclusion strategy. Twenty-eight MSCT scans (40/80mAs, 120kVp, 5mm collimation/2.5mm reconstruction) from our lung cancer screening program that included at least one lung nodule were selected for this study. Two radiologists independently interpreted these cases. Subsequently, a consensus reading by both radiologists and CAD was generated to define a "gold standard". In total, 165 nodules were considered as the "gold standard" (average: 5.9 nodules/case; range: 1-22 nodules/case). The two radiologists detected 146 nodules (88.5%) and CAD detected 100 nodules (60.6%) with 8.7 false-positives/case. CAD detected an additional 19 nodules (6 nodules > 3mm and 13 nodules < 3mm) that had been missed by both radiologists. Preliminary results show that the CAD is capable of detecting small lung nodules with acceptable number of false-positives on low-dose MSCT scans and it can detect nodules that are otherwise missed by radiologists, though a majority are small nodules (< 3mm).
Kumar, K R V; Ranganath, V; Naik, R; Banu, S; Nichani, A S
2014-12-01
Various epidemiological studies have implied that local infection may increase the levels of systemic inflammatory mediators and lipid mediators, thereby promoting atherosclerosis. The aim of this study was to assess high-sensitivity C-reactive protein (HsCRP) and lipid levels in healthy adults and patients with coronary artery disease (CAD), with and without periodontitis. A total of 100 subjects were included in the study and categorized into four groups of 25 subjects each, as follows: subjects with chronic periodontitis with angiographically proven CAD; nonperiodontitis subjects with angiographically proven CAD; otherwise healthy subjects with only chronic periodontitis; and systemically and orally healthy individuals. The periodontal parameters measured included plaque index, gingival index, probing pocket depth, clinical attachment level and marginal alveolar bone loss (which was recorded radiographically). Serum samples were collected for estimation of HsCRP, low-density lipoprotein (LDL), high-density lipoprotein (HDL) and triglycerides (TGs). The serum HsCRP levels in subjects with either CAD or chronic periodontitis were elevated two-fold compared with those of healthy individuals, whereas in subjects with both diseases (CAD plus chronic periodontitis) the levels were elevated three-fold. The serum LDL level was higher, and the serum HDL level was lower, in all the test groups compared with the healthy group. No significant difference among the groups was detected in the TG levels. A persistent infection, such as chronic periodontitis, may influence changes in the systemic levels of HsCRP, LDL and HDL, which potentially have an impact on inflammation-associated atherosclerotic processes, such as CAD. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
Increasing cancer detection yield of breast MRI using a new CAD scheme of mammograms
NASA Astrophysics Data System (ADS)
Tan, Maxine; Aghaei, Faranak; Hollingsworth, Alan B.; Stough, Rebecca G.; Liu, Hong; Zheng, Bin
2016-03-01
Although breast MRI is the most sensitive imaging modality to detect early breast cancer, its cancer detection yield in breast cancer screening is quite low (< 3 to 4% even for the small group of high-risk women) to date. The purpose of this preliminary study is to test the potential of developing and applying a new computer-aided detection (CAD) scheme of digital mammograms to identify women at high risk of harboring mammography-occult breast cancers, which can be detected by breast MRI. For this purpose, we retrospectively assembled a dataset involving 30 women who had both mammography and breast MRI screening examinations. All mammograms were interpreted as negative, while 5 cancers were detected using breast MRI. We developed a CAD scheme of mammograms, which include a new quantitative mammographic image feature analysis based risk model, to stratify women into two groups with high and low risk of harboring mammography-occult cancer. Among 30 women, 9 were classified into the high risk group by CAD scheme, which included all 5 women who had cancer detected by breast MRI. All 21 low risk women remained negative on the breast MRI examinations. The cancer detection yield of breast MRI applying to this dataset substantially increased from 16.7% (5/30) to 55.6% (5/9), while eliminating 84% (21/25) unnecessary breast MRI screenings. The study demonstrated the potential of applying a new CAD scheme to significantly increase cancer detection yield of breast MRI, while simultaneously reducing the number of negative MRIs in breast cancer screening.
Management of coronary artery disease
NASA Astrophysics Data System (ADS)
Safri, Z.
2018-03-01
Coronary Artery Disease (CAD) is associated with significant morbidity and mortality, therefore it’s important to early and accurate detection and appropriate management. Diagnosis of CAD include clinical examination, noninvasive techniques such as biochemical testing, a resting ECG, possibly ambulatory ECG monitoring, resting echocardiography, chest X-ray in selected patients; and catheterization. Managements of CAD patients include lifestyle modification, control of CAD risk factors, pharmacologic therapy, and patient education. Revascularization consists of percutaneous coronary angioplasty and coronary artery bypass grafting. Cardiac rehabilitation should be considered in all patients with CAD. This comprehensive review highlights strategies of management in patients with CAD.
NASA Astrophysics Data System (ADS)
Gendron, Marlin Lee
During Mine Warfare (MIW) operations, MIW analysts perform change detection by visually comparing historical sidescan sonar imagery (SSI) collected by a sidescan sonar with recently collected SSI in an attempt to identify objects (which might be explosive mines) placed at sea since the last time the area was surveyed. This dissertation presents a data structure and three algorithms, developed by the author, that are part of an automated change detection and classification (ACDC) system. MIW analysts at the Naval Oceanographic Office, to reduce the amount of time to perform change detection, are currently using ACDC. The dissertation introductory chapter gives background information on change detection, ACDC, and describes how SSI is produced from raw sonar data. Chapter 2 presents the author's Geospatial Bitmap (GB) data structure, which is capable of storing information geographically and is utilized by the three algorithms. This chapter shows that a GB data structure used in a polygon-smoothing algorithm ran between 1.3--48.4x faster than a sparse matrix data structure. Chapter 3 describes the GB clustering algorithm, which is the author's repeatable, order-independent method for clustering. Results from tests performed in this chapter show that the time to cluster a set of points is not affected by the distribution or the order of the points. In Chapter 4, the author presents his real-time computer-aided detection (CAD) algorithm that automatically detects mine-like objects on the seafloor in SSI. The author ran his GB-based CAD algorithm on real SSI data, and results of these tests indicate that his real-time CAD algorithm performs comparably to or better than other non-real-time CAD algorithms. The author presents his computer-aided search (CAS) algorithm in Chapter 5. CAS helps MIW analysts locate mine-like features that are geospatially close to previously detected features. A comparison between the CAS and a great circle distance algorithm shows that the CAS performs geospatial searching 1.75x faster on large data sets. Finally, the concluding chapter of this dissertation gives important details on how the completed ACDC system will function, and discusses the author's future research to develop additional algorithms and data structures for ACDC.
Greulich, Simon; Steubing, Hannah; Birkmeier, Stefan; Grün, Stefan; Bentz, Kerstin; Sechtem, Udo; Mahrholdt, Heiko
2015-11-05
The diagnostic performance of adenosine stress cardiovascular magnetic resonance (CMR) in patients with arrhythmias presenting for work-up of suspected or known CAD is largely unknown, since most CMR studies currently available exclude arrhythmic patients from analysis fearing gating problems, or other artifacts will impair image quality. The primary aim of our study was to evaluate the diagnostic performance of adenosine stress CMR for detection of significant coronary stenosis in patients with arrhythmia presenting for 1) work-up of suspected coronary artery disease (CAD), or 2) work-up of ischemia in known CAD. Patients with arrhythmia referred for work-up of suspected CAD or work-up of ischemia in known CAD undergoing adenosine stress CMR were included if they had coronary angiography within four weeks of CMR. One hundred fifty-nine patients were included (n = 64 atrial fibrillation, n = 87 frequent ventricular extrasystoles, n = 8 frequent supraventricular extrasystoles). Of these, n = 72 had suspected CAD, and n = 87 had known CAD. Diagnostic accuracy of the adenosine stress CMR for detection of significant CAD was 73 % for the entire population (sensitivity 72 %, specificity 76 %). Diagnostic accuracy was 75 % (sensitivity 80 %, specificity 74 %) in patients with suspected CAD, and 74 % (sensitivity 71 %, specificity 79 %) in the group with known CAD. For different types of arrhythmia, diagnostic accuracy of CMR was 70 % in the atrial fibrillation group, and 79 % in patients with ventricular extrasystoles. On a per coronary territory analysis, diagnostic accuracy of CMR was 77 % for stenosis of the left and 82 % for stenosis of the right coronary artery. The present data demonstrates good diagnostic performance of adenosine stress CMR for detection of significant coronary stenosis in patients with arrhythmia presenting for work-up of suspected CAD, or work-up of ischemia in known CAD. This holds true for a per patient, as well as for a per coronary territory analysis.
Chang, Yongjun; Paul, Anjan Kumar; Kim, Namkug; Baek, Jung Hwan; Choi, Young Jun; Ha, Eun Ju; Lee, Kang Dae; Lee, Hyoung Shin; Shin, DaeSeock; Kim, Nakyoung
2016-01-01
To develop a semiautomated computer-aided diagnosis (cad) system for thyroid cancer using two-dimensional ultrasound images that can be used to yield a second opinion in the clinic to differentiate malignant and benign lesions. A total of 118 ultrasound images that included axial and longitudinal images from patients with biopsy-confirmed malignant (n = 30) and benign (n = 29) nodules were collected. Thyroid cad software was developed to extract quantitative features from these images based on thyroid nodule segmentation in which adaptive diffusion flow for active contours was used. Various features, including histogram, intensity differences, elliptical fit, gray-level co-occurrence matrixes, and gray-level run-length matrixes, were evaluated for each region imaged. Based on these imaging features, a support vector machine (SVM) classifier was used to differentiate benign and malignant nodules. Leave-one-out cross-validation with sequential forward feature selection was performed to evaluate the overall accuracy of this method. Additionally, analyses with contingency tables and receiver operating characteristic (ROC) curves were performed to compare the performance of cad with visual inspection by expert radiologists based on established gold standards. Most univariate features for this proposed cad system attained accuracies that ranged from 78.0% to 83.1%. When optimal SVM parameters that were established using a grid search method with features that radiologists use for visual inspection were employed, the authors could attain rates of accuracy that ranged from 72.9% to 84.7%. Using leave-one-out cross-validation results in a multivariate analysis of various features, the highest accuracy achieved using the proposed cad system was 98.3%, whereas visual inspection by radiologists reached 94.9% accuracy. To obtain the highest accuracies, "axial ratio" and "max probability" in axial images were most frequently included in the optimal feature sets for the authors' proposed cad system, while "shape" and "calcification" in longitudinal images were most frequently included in the optimal feature sets for visual inspection by radiologists. The computed areas under curves in the ROC analysis were 0.986 and 0.979 for the proposed cad system and visual inspection by radiologists, respectively; no significant difference was detected between these groups. The use of thyroid cad to differentiate malignant from benign lesions shows accuracy similar to that obtained via visual inspection by radiologists. Thyroid cad might be considered a viable way to generate a second opinion for radiologists in clinical practice.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Chang, Yongjun; Paul, Anjan Kumar; Kim, Namkug, E-mail: namkugkim@gmail.com
Purpose: To develop a semiautomated computer-aided diagnosis (CAD) system for thyroid cancer using two-dimensional ultrasound images that can be used to yield a second opinion in the clinic to differentiate malignant and benign lesions. Methods: A total of 118 ultrasound images that included axial and longitudinal images from patients with biopsy-confirmed malignant (n = 30) and benign (n = 29) nodules were collected. Thyroid CAD software was developed to extract quantitative features from these images based on thyroid nodule segmentation in which adaptive diffusion flow for active contours was used. Various features, including histogram, intensity differences, elliptical fit, gray-level co-occurrencemore » matrixes, and gray-level run-length matrixes, were evaluated for each region imaged. Based on these imaging features, a support vector machine (SVM) classifier was used to differentiate benign and malignant nodules. Leave-one-out cross-validation with sequential forward feature selection was performed to evaluate the overall accuracy of this method. Additionally, analyses with contingency tables and receiver operating characteristic (ROC) curves were performed to compare the performance of CAD with visual inspection by expert radiologists based on established gold standards. Results: Most univariate features for this proposed CAD system attained accuracies that ranged from 78.0% to 83.1%. When optimal SVM parameters that were established using a grid search method with features that radiologists use for visual inspection were employed, the authors could attain rates of accuracy that ranged from 72.9% to 84.7%. Using leave-one-out cross-validation results in a multivariate analysis of various features, the highest accuracy achieved using the proposed CAD system was 98.3%, whereas visual inspection by radiologists reached 94.9% accuracy. To obtain the highest accuracies, “axial ratio” and “max probability” in axial images were most frequently included in the optimal feature sets for the authors’ proposed CAD system, while “shape” and “calcification” in longitudinal images were most frequently included in the optimal feature sets for visual inspection by radiologists. The computed areas under curves in the ROC analysis were 0.986 and 0.979 for the proposed CAD system and visual inspection by radiologists, respectively; no significant difference was detected between these groups. Conclusions: The use of thyroid CAD to differentiate malignant from benign lesions shows accuracy similar to that obtained via visual inspection by radiologists. Thyroid CAD might be considered a viable way to generate a second opinion for radiologists in clinical practice.« less
Applying a CAD-generated imaging marker to assess short-term breast cancer risk
NASA Astrophysics Data System (ADS)
Mirniaharikandehei, Seyedehnafiseh; Zarafshani, Ali; Heidari, Morteza; Wang, Yunzhi; Aghaei, Faranak; Zheng, Bin
2018-02-01
Although whether using computer-aided detection (CAD) helps improve radiologists' performance in reading and interpreting mammograms is controversy due to higher false-positive detection rates, objective of this study is to investigate and test a new hypothesis that CAD-generated false-positives, in particular, the bilateral summation of false-positives, is a potential imaging marker associated with short-term breast cancer risk. An image dataset involving negative screening mammograms acquired from 1,044 women was retrospectively assembled. Each case involves 4 images of craniocaudal (CC) and mediolateral oblique (MLO) view of the left and right breasts. In the next subsequent mammography screening, 402 cases were positive for cancer detected and 642 remained negative. A CAD scheme was applied to process all "prior" negative mammograms. Some features from CAD scheme were extracted, which include detection seeds, the total number of false-positive regions, an average of detection scores and the sum of detection scores in CC and MLO view images. Then the features computed from two bilateral images of left and right breasts from either CC or MLO view were combined. In order to predict the likelihood of each testing case being positive in the next subsequent screening, two logistic regression models were trained and tested using a leave-one-case-out based cross-validation method. Data analysis demonstrated the maximum prediction accuracy with an area under a ROC curve of AUC=0.65+/-0.017 and the maximum adjusted odds ratio of 4.49 with a 95% confidence interval of [2.95, 6.83]. The results also illustrated an increasing trend in the adjusted odds ratio and risk prediction scores (p<0.01). Thus, the study showed that CAD-generated false-positives might provide a new quantitative imaging marker to help assess short-term breast cancer risk.
NASA Astrophysics Data System (ADS)
Tan, Maxine; Aghaei, Faranak; Wang, Yunzhi; Qian, Wei; Zheng, Bin
2016-03-01
Current commercialized CAD schemes have high false-positive (FP) detection rates and also have high correlations in positive lesion detection with radiologists. Thus, we recently investigated a new approach to improve the efficacy of applying CAD to assist radiologists in reading and interpreting screening mammograms. Namely, we developed a new global feature based CAD approach/scheme that can cue the warning sign on the cases with high risk of being positive. In this study, we investigate the possibility of fusing global feature or case-based scores with the local or lesion-based CAD scores using an adaptive cueing method. We hypothesize that the information from the global feature extraction (features extracted from the whole breast regions) are different from and can provide supplementary information to the locally-extracted features (computed from the segmented lesion regions only). On a large and diverse full-field digital mammography (FFDM) testing dataset with 785 cases (347 negative and 438 cancer cases with masses only), we ran our lesion-based and case-based CAD schemes "as is" on the whole dataset. To assess the supplementary information provided by the global features, we used an adaptive cueing method to adaptively adjust the original CAD-generated detection scores (Sorg) of a detected suspicious mass region based on the computed case-based score (Scase) of the case associated with this detected region. Using the adaptive cueing method, better sensitivity results were obtained at lower FP rates (<= 1 FP per image). Namely, increases of sensitivities (in the FROC curves) of up to 6.7% and 8.2% were obtained for the ROI and Case-based results, respectively.
Byars, Sean G.; Gray, Lesley-Ann; Ripatti, Samuli; Stearns, Stephen C.; Inouye, Michael
2017-01-01
Traditional genome-wide scans for positive selection have mainly uncovered selective sweeps associated with monogenic traits. While selection on quantitative traits is much more common, very few signals have been detected because of their polygenic nature. We searched for positive selection signals underlying coronary artery disease (CAD) in worldwide populations, using novel approaches to quantify relationships between polygenic selection signals and CAD genetic risk. We identified new candidate adaptive loci that appear to have been directly modified by disease pressures given their significant associations with CAD genetic risk. These candidates were all uniquely and consistently associated with many different male and female reproductive traits suggesting selection may have also targeted these because of their direct effects on fitness. We found that CAD loci are significantly enriched for lifetime reproductive success relative to the rest of the human genome, with evidence that the relationship between CAD and lifetime reproductive success is antagonistic. This supports the presence of antagonistic-pleiotropic tradeoffs on CAD loci and provides a novel explanation for the maintenance and high prevalence of CAD in modern humans. Lastly, we found that positive selection more often targeted CAD gene regulatory variants using HapMap3 lymphoblastoid cell lines, which further highlights the unique biological significance of candidate adaptive loci underlying CAD. Our study provides a novel approach for detecting selection on polygenic traits and evidence that modern human genomes have evolved in response to CAD-induced selection pressures and other early-life traits sharing pleiotropic links with CAD. PMID:28640878
Chang, Ruey-Feng; Lee, Chung-Chien; Lo, Chung-Ming
2016-09-01
The lifetime prevalence of shoulder pain approaches 70%, which is mostly attributable to rotator cuff lesions such as inflammation, calcific tendinitis and tears. On clinical examination, shoulder ultrasound is recommended for the detection of lesions. However, there exists inter-operator variability in diagnostic accuracy because of differences in the experience and expertise of operators. In this study, a computer-aided diagnosis (CAD) system was developed to assist ultrasound operators in diagnosing rotator cuff lesions and to improve the practicality of ultrasound examination. The collected cases included 43 cases of inflammation, 30 cases of calcific tendinitis and 26 tears. For each case, the lesion area and texture features were extracted from the entire lesions and combined in a multinomial logistic regression classifier for lesion classification. The proposed CAD achieved an accuracy of 87.9%. The individual accuracy of this CAD system was 88.4% for inflammation, 83.3% for calcific tendinitis and 92.3% for tears. Cohen's k was 0.798. On the basis of its diagnostic performance, clinical use of this CAD technique has promise. Copyright © 2016 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.
Shi, Zhenghao; Ma, Jiejue; Feng, Yaning; He, Lifeng; Suzuki, Kenji
2015-11-01
MTANN (Massive Training Artificial Neural Network) is a promising tool, which applied to eliminate false-positive for thoracic CT in recent years. In order to evaluate whether this method is feasible to eliminate false-positive of different CAD schemes, especially, when it is applied to commercial CAD software, this paper evaluate the performance of the method for eliminating false-positives produced by three different versions of commercial CAD software for lung nodules detection in chest radiographs. Experimental results demonstrate that the approach is useful in reducing FPs for different computer aided lung nodules detection software in chest radiographs.
Automatic detection of lung vessel bifurcation in thoracic CT images
NASA Astrophysics Data System (ADS)
Maduskar, Pragnya; Vikal, Siddharth; Devarakota, Pandu
2011-03-01
Computer-aided diagnosis (CAD) systems for detection of lung nodules have been an active topic of research for last few years. It is desirable that a CAD system should generate very low false positives (FPs) while maintaining high sensitivity. This work aims to reduce the number of false positives occurring at vessel bifurcation point. FPs occur quite frequently on vessel branching point due to its shape which can appear locally spherical due to the intrinsic geometry of intersecting tubular vessel structures combined with partial volume effects and soft tissue attenuation appearance surrounded by parenchyma. We propose a model-based technique for detection of vessel branching points using skeletonization, followed by branch-point analysis. First we perform vessel structure enhancement using a multi-scale Hessian filter to accurately segment tubular structures of various sizes followed by thresholding to get binary vessel structure segmentation [6]. A modified Reebgraph [7] is applied next to extract the critical points of structure and these are joined by a nearest neighbor criterion to obtain complete skeletal model of vessel structure. Finally, the skeletal model is traversed to identify branch points, and extract metrics including individual branch length, number of branches and angle between various branches. Results on 80 sub-volumes consisting of 60 actual vessel-branching and 20 solitary solid nodules show that the algorithm identified correctly vessel branching points for 57 sub-volumes (95% sensitivity) and misclassified 2 nodules as vessel branch. Thus, this technique has potential in explicit identification of vessel branching points for general vessel analysis, and could be useful in false positive reduction in a lung CAD system.
Timp, Sheila; Karssemeijer, Nico
2004-05-01
Mass segmentation plays a crucial role in computer-aided diagnosis (CAD) systems for classification of suspicious regions as normal, benign, or malignant. In this article we present a robust and automated segmentation technique--based on dynamic programming--to segment mass lesions from surrounding tissue. In addition, we propose an efficient algorithm to guarantee resulting contours to be closed. The segmentation method based on dynamic programming was quantitatively compared with two other automated segmentation methods (region growing and the discrete contour model) on a dataset of 1210 masses. For each mass an overlap criterion was calculated to determine the similarity with manual segmentation. The mean overlap percentage for dynamic programming was 0.69, for the other two methods 0.60 and 0.59, respectively. The difference in overlap percentage was statistically significant. To study the influence of the segmentation method on the performance of a CAD system two additional experiments were carried out. The first experiment studied the detection performance of the CAD system for the different segmentation methods. Free-response receiver operating characteristics analysis showed that the detection performance was nearly identical for the three segmentation methods. In the second experiment the ability of the classifier to discriminate between malignant and benign lesions was studied. For region based evaluation the area Az under the receiver operating characteristics curve was 0.74 for dynamic programming, 0.72 for the discrete contour model, and 0.67 for region growing. The difference in Az values obtained by the dynamic programming method and region growing was statistically significant. The differences between other methods were not significant.
Mazurowski, Maciej A; Lo, Joseph Y; Harrawood, Brian P; Tourassi, Georgia D
2011-01-01
Development of a computational decision aid for a new medical imaging modality typically is a long and complicated process. It consists of collecting data in the form of images and annotations, development of image processing and pattern recognition algorithms for analysis of the new images and finally testing of the resulting system. Since new imaging modalities are developed more rapidly than ever before, any effort for decreasing the time and cost of this development process could result in maximizing the benefit of the new imaging modality to patients by making the computer aids quickly available to radiologists that interpret the images. In this paper, we make a step in this direction and investigate the possibility of translating the knowledge about the detection problem from one imaging modality to another. Specifically, we present a computer-aided detection (CAD) system for mammographic masses that uses a mutual information-based template matching scheme with intelligently selected templates. We presented principles of template matching with mutual information for mammography before. In this paper, we present an implementation of those principles in a complete computer-aided detection system. The proposed system, through an automatic optimization process, chooses the most useful templates (mammographic regions of interest) using a large database of previously collected and annotated mammograms. Through this process, the knowledge about the task of detecting masses in mammograms is incorporated in the system. Then we evaluate whether our system developed for screen-film mammograms can be successfully applied not only to other mammograms but also to digital breast tomosynthesis (DBT) reconstructed slices without adding any DBT cases for training. Our rationale is that since mutual information is known to be a robust intermodality image similarity measure, it has high potential of transferring knowledge between modalities in the context of the mass detection task. Experimental evaluation of the system on mammograms showed competitive performance compared to other mammography CAD systems recently published in the literature. When the system was applied “as-is” to DBT, its performance was notably worse than that for mammograms. However, with a simple additional preprocessing step, the performance of the system reached levels similar to that obtained for mammograms. In conclusion, the presented CAD system not only performed competitively on screen-film mammograms but it also performed robustly on DBT showing that direct transfer of knowledge across breast imaging modalities for mass detection is in fact possible. PMID:21554985
NIR fluorescence lifetime sensing through a multimode fiber for intravascular molecular probing
NASA Astrophysics Data System (ADS)
Ingelberts, H.; Hernot, S.; Debie, P.; Lahoutte, T.; Kuijk, M.
2016-04-01
Coronary artery disease (CAD) contributes to millions of deaths each year. The identification of vulnerable plaques is essential to the diagnosis of CAD but is challenging. Molecular probes can improve the detection of these plaques using intravascular imaging methods. Fluorescence lifetime sensing is a safe and robust method to image these molecular probes. We present two variations of an optical system for intravascular near-infrared (NIR) fluorescence lifetime sensing through a multimode fiber. Both systems are built around a recently developed fast and efficient CMOS detector, the current-assisted photonic sampler (CAPS) that is optimized for sub-nanosecond NIR fluorescence lifetime sensing. One system mimics the optical setup of an epifluorescence microscope while the other uses a practical fiber optic coupler to separate fluorescence excitation and emission. We test both systems by measuring the lifetime of several NIR dyes in DMSO solutions and we show that these systems are capable of detecting lifetimes of solutions with concentrations down to 370 nM and this with short acquisition times. These results are compared with time-correlated single photon counting (TCSPC) measurements for reference.
Computer-aided-diagnosis (CAD) for colposcopy
NASA Astrophysics Data System (ADS)
Lange, Holger; Ferris, Daron G.
2005-04-01
Uterine cervical cancer is the second most common cancer among women worldwide. Colposcopy is a diagnostic method, whereby a physician (colposcopist) visually inspects the lower genital tract (cervix, vulva and vagina), with special emphasis on the subjective appearance of metaplastic epithelium comprising the transformation zone on the cervix. Cervical cancer precursor lesions and invasive cancer exhibit certain distinctly abnormal morphologic features. Lesion characteristics such as margin; color or opacity; blood vessel caliber, intercapillary spacing and distribution; and contour are considered by colposcopists to derive a clinical diagnosis. Clinicians and academia have suggested and shown proof of concept that automated image analysis of cervical imagery can be used for cervical cancer screening and diagnosis, having the potential to have a direct impact on improving women"s health care and reducing associated costs. STI Medical Systems is developing a Computer-Aided-Diagnosis (CAD) system for colposcopy -- ColpoCAD. At the heart of ColpoCAD is a complex multi-sensor, multi-data and multi-feature image analysis system. A functional description is presented of the envisioned ColpoCAD system, broken down into: Modality Data Management System, Image Enhancement, Feature Extraction, Reference Database, and Diagnosis and directed Biopsies. The system design and development process of the image analysis system is outlined. The system design provides a modular and open architecture built on feature based processing. The core feature set includes the visual features used by colposcopists. This feature set can be extended to include new features introduced by new instrument technologies, like fluorescence and impedance, and any other plausible feature that can be extracted from the cervical data. Preliminary results of our research on detecting the three most important features: blood vessel structures, acetowhite regions and lesion margins are shown. As this is a new and very complex field in medical image processing, the hope is that this paper can provide a framework and basis to encourage and facilitate collaboration and discussion between industry, academia, and medical practitioners.
Gao, Luying; Liu, Ruyu; Jiang, Yuxin; Song, Wenfeng; Wang, Ying; Liu, Jia; Wang, Juanjuan; Wu, Dongqian; Li, Shuai; Hao, Aimin; Zhang, Bo
2018-04-01
The purpose of this study was to compare the diagnostic efficiency of a thyroid ultrasound computer-aided diagnosis (CAD) system with that of 1 radiologist. This study retrospectively reviewed 342 surgically resected thyroid nodules from July 2013 to December 2013 at our center. The nodules were assessed on typical ultrasound images using the CAD system and reviewed by 1 experienced radiologist. The radiologist stratified the risk of malignancy using the Thyroid Imaging Reporting and Data Systems (TIRADS) and the American Thyroid Association (ATA) guidelines. The radiologist, using TI-RADS and ATA guidelines, performed better than the CAD system (P < .01). The sensitivity of the CAD system was similar to that of an experienced radiologist (P > .05; P < .01; and P > .05). However, we found that the CAD system had lower specificity (P < .01). The sensitivity of a thyroid ultrasound CAD system in differentiating nodules was similar to that of an experienced radiologist. However, the CAD system had lower specificity. © 2017 Wiley Periodicals, Inc.
Delayed contrast-enhanced MRI of the coronary artery wall in takayasu arteritis.
Schneeweis, Christopher; Schnackenburg, Bernhard; Stuber, Matthias; Berger, Alexander; Schneider, Udo; Yu, Jing; Gebker, Rolf; Weiss, Robert G; Fleck, Eckart; Kelle, Sebastian
2012-01-01
Takayasu arteritis (TA) is a rare form of chronic inflammatory granulomatous arteritis of the aorta and its major branches. Late gadolinium enhancement (LGE) with magnetic resonance imaging (MRI) has demonstrated its value for the detection of vessel wall alterations in TA. The aim of this study was to assess LGE of the coronary artery wall in patients with TA compared to patients with stable CAD. We enrolled 9 patients (8 female, average age 46±13 years) with proven TA. In the CAD group 9 patients participated (8 male, average age 65±10 years). Studies were performed on a commercial 3T whole-body MR imaging system (Achieva; Philips, Best, The Netherlands) using a 3D inversion prepared navigator gated spoiled gradient-echo sequence, which was repeated 34-45 minutes after low-dose gadolinium administration. No coronary vessel wall enhancement was observed prior to contrast in either group. Post contrast, coronary LGE on IR scans was detected in 28 of 50 segments (56%) seen on T2-Prep scans in TA and in 25 of 57 segments (44%) in CAD patients. LGE quantitative assessment of coronary artery vessel wall CNR post contrast revealed no significant differences between the two groups (CNR in TA: 6.0±2.4 and 7.3±2.5 in CAD; p = 0.474). Our findings suggest that LGE of the coronary artery wall seems to be common in patients with TA and similarly pronounced as in CAD patients. The observed coronary LGE seems to be rather unspecific, and differentiation between coronary vessel wall fibrosis and inflammation still remains unclear.
Stypulkowska, Karolina; Fijalek, Zbigniew; Sarna, Katarzyna
2010-01-01
A new, simple and repeatable liquid chromatography method with charged aerosol detection (LC-CAD) for the determination of gentamicin sulphate composition and related substances has been developed. Gentamicin lacks of chromophores, therefore its determination is quite problematic. Using a universal CAD enables to achieve good separation without sample derivatization. Mass spectrometry was employed to confirm the LC-CAD peak profile. The proposed method was validated and applied for the determination of gentamicin sulphate composition and related substances in pharmaceutical preparations. PMID:21212825
External validation of Medicare claims codes for digital mammography and computer-aided detection.
Fenton, Joshua J; Zhu, Weiwei; Balch, Steven; Smith-Bindman, Rebecca; Lindfors, Karen K; Hubbard, Rebecca A
2012-08-01
While Medicare claims are a potential resource for clinical mammography research or quality monitoring, the validity of key data elements remains uncertain. Claims codes for digital mammography and computer-aided detection (CAD), for example, have not been validated against a credible external reference standard. We matched Medicare mammography claims for women who received bilateral mammograms from 2003 to 2006 to corresponding mammography data from the Breast Cancer Surveillance Consortium (BCSC) registries in four U.S. states (N = 253,727 mammograms received by 120,709 women). We assessed the accuracy of the claims-based classifications of bilateral mammograms as either digital versus film and CAD versus non-CAD relative to a reference standard derived from BCSC data. Claims data correctly classified the large majority of film and digital mammograms (97.2% and 97.3%, respectively), yielding excellent agreement beyond chance (κ = 0.90). Claims data correctly classified the large majority of CAD mammograms (96.6%) but a lower percentage of non-CAD mammograms (86.7%). Agreement beyond chance remained high for CAD classification (κ = 0.83). From 2003 to 2006, the predictive values of claims-based digital and CAD classifications increased as the sample prevalences of each technology increased. Medicare claims data can accurately distinguish film and digital bilateral mammograms and mammograms conducted with and without CAD. The validity of Medicare claims data regarding film versus digital mammography and CAD suggests that these data elements can be useful in research and quality improvement. ©2012 AACR.
Bahari, Mahmoud; Savadi Oskoee, Siavash; Kimyai, Soodabeh; Pouralibaba, Firoz; Farhadi, Farrokh; Norouzi, Marouf
2014-01-01
Background and aims. The aim was to evaluate the effect of casein phosphopeptide-amorphous calcium phosphate (CPP-ACP) on microtensile bond strength (μTBS) to carious affected dentin (CAD) using etch-and-rinse and self-etch adhesive systems. Materials and methods. The occlusal surface of 32 human molars with moderate occlusal caries was removed. Infected dentin was removed until reaching CAD and the teeth were randomly divided into two groups based on the Single Bond (SB) and Clearfil SE Bond (CSE) adhesive systems. Before composite resin bonding, each group was subdivided into three subgroups of ND, CAD and CPP-ACP-treated CAD (CAD-CPP) based on the dentin substrate. After dissecting samples to l-mm-thick cross-sections (each subgroup: n = 13), μTBS was measured at a strain rate of 0.5 mm/min. Data was analyzed using two-way ANOVA, independent samples t-test and post-hoc Tukey tests (α=0.05). Results. Bond strength of both adhesive systems to ND was significantly higher than that to CAD (P <0.001) and CAD/CPP (P < 0.001). There were no significant differences between the μTBS of SB to CAD and CAD-CPP (P > 0.05).μTBS of CSE to CAD-CPP was higher than that to CAD; however, the difference was not significant (P > 0.05). Significant differences were found between SB and CSE systems only with CAD substrate (P < 0.001). Conclusion. Regardless of the adhesive system used, surface treatment of CAD with CPP-ACP did not have a significant effect on bond strength. However, bond strength to CAD was higher with SB rather than with CSE. PMID:25346832
The USEPA's National Homeland Security Research Center (NHSRC)Technology Testing and Evaluation Program (TTEP) is carrying out performance tests on homeland security technologies. Under TTEP, Battelle recently evaluated the performance of the Science Applications International Co...
CAD/CAE Integration Enhanced by New CAD Services Standard
NASA Technical Reports Server (NTRS)
Claus, Russell W.
2002-01-01
A Government-industry team led by the NASA Glenn Research Center has developed a computer interface standard for accessing data from computer-aided design (CAD) systems. The Object Management Group, an international computer standards organization, has adopted this CAD services standard. The new standard allows software (e.g., computer-aided engineering (CAE) and computer-aided manufacturing software to access multiple CAD systems through one programming interface. The interface is built on top of a distributed computing system called the Common Object Request Broker Architecture (CORBA). CORBA allows the CAD services software to operate in a distributed, heterogeneous computing environment.
An image database management system for conducting CAD research
NASA Astrophysics Data System (ADS)
Gruszauskas, Nicholas; Drukker, Karen; Giger, Maryellen L.
2007-03-01
The development of image databases for CAD research is not a trivial task. The collection and management of images and their related metadata from multiple sources is a time-consuming but necessary process. By standardizing and centralizing the methods in which these data are maintained, one can generate subsets of a larger database that match the specific criteria needed for a particular research project in a quick and efficient manner. A research-oriented management system of this type is highly desirable in a multi-modality CAD research environment. An online, webbased database system for the storage and management of research-specific medical image metadata was designed for use with four modalities of breast imaging: screen-film mammography, full-field digital mammography, breast ultrasound and breast MRI. The system was designed to consolidate data from multiple clinical sources and provide the user with the ability to anonymize the data. Input concerning the type of data to be stored as well as desired searchable parameters was solicited from researchers in each modality. The backbone of the database was created using MySQL. A robust and easy-to-use interface for entering, removing, modifying and searching information in the database was created using HTML and PHP. This standardized system can be accessed using any modern web-browsing software and is fundamental for our various research projects on computer-aided detection, diagnosis, cancer risk assessment, multimodality lesion assessment, and prognosis. Our CAD database system stores large amounts of research-related metadata and successfully generates subsets of cases that match the user's desired search criteria.
CAD system for automatic analysis of CT perfusion maps
NASA Astrophysics Data System (ADS)
Hachaj, T.; Ogiela, M. R.
2011-03-01
In this article, authors present novel algorithms developed for the computer-assisted diagnosis (CAD) system for analysis of dynamic brain perfusion, computer tomography (CT) maps, cerebral blood flow (CBF), and cerebral blood volume (CBV). Those methods perform both quantitative analysis [detection and measurement and description with brain anatomy atlas (AA) of potential asymmetries/lesions] and qualitative analysis (semantic interpretation of visualized symptoms). The semantic interpretation (decision about type of lesion: ischemic/hemorrhagic, is the brain tissue at risk of infraction or not) of visualized symptoms is done by, so-called, cognitive inference processes allowing for reasoning on character of pathological regions based on specialist image knowledge. The whole system is implemented in.NET platform (C# programming language) and can be used on any standard PC computer with.NET framework installed.
Chao, Nan; Liu, Shu-Xin; Liu, Bing-Mei; Li, Ning; Jiang, Xiang-Ning; Gai, Ying
2014-11-01
Nine CAD/CAD-like genes in P. tomentosa were classified into four classes based on expression patterns, phylogenetic analysis and biochemical properties with modification for the previous claim of SAD. Cinnamyl alcohol dehydrogenase (CAD) functions in monolignol biosynthesis and plays a critical role in wood development and defense. In this study, we isolated and cloned nine CAD/CAD-like genes in the Populus tomentosa genome. We investigated differential expression using microarray chips and found that PtoCAD1 was highly expressed in bud, root and vascular tissues (xylem and phloem) with the greatest expression in the root. Differential expression in tissues was demonstrated for PtoCAD3, PtoCAD6 and PtoCAD9. Biochemical analysis of purified PtoCADs in vitro indicated PtoCAD1, PtoCAD2 and PtoCAD8 had detectable activity against both coniferaldehyde and sinapaldehyde. PtoCAD1 used both substrates with high efficiency. PtoCAD2 showed no specific requirement for sinapaldehyde in spite of its high identity with so-called PtrSAD (sinapyl alcohol dehydrogenase). In addition, the enzymatic activity of PtoCAD1 and PtoCAD2 was affected by temperature. We classified these nine CAD/CAD-like genes into four classes: class I included PtoCAD1, which was a bone fide CAD with the highest activity; class II included PtoCAD2, -5, -7, -8, which might function in monolignol biosynthesis and defense; class III genes included PtoCAD3, -6, -9, which have a distinct expression pattern; class IV included PtoCAD12, which has a distinct structure. These data suggest divergence of the PtoCADs and its homologs, related to their functions. We propose genes in class II are a subset of CAD genes that evolved before angiosperms appeared. These results suggest CAD/CAD-like genes in classes I and II play a role in monolignol biosynthesis and contribute to our knowledge of lignin biosynthesis in P. tomentosa.
Arbab-Zadeh, Armin; Miller, Julie M; Rochitte, Carlos E; Dewey, Marc; Niinuma, Hiroyuki; Gottlieb, Ilan; Paul, Narinder; Clouse, Melvin E.; Shapiro, Edward P.; Hoe, John; Lardo, Albert C.; Bush, David E.; de Roos, Albert; Cox, Christopher; Brinker, Jeffrey; Lima, Joăo A. C.
2012-01-01
Objectives Assess the impact of patient population characteristics on accuracy by CT angiography (CTA) to detect obstructive coronary artery disease (CAD). Background The ability of CTA to exclude obstructive CAD in patients of different pretest probabilities and in presence of coronary calcification remains uncertain. Methods For the CorE-64 study 371 patients underwent CTA and cardiac catheterization for the detection of obstructive CAD defined as 50% or greater luminal stenosis by quantitative coronary angiography (QCA). This analysis includes 80 initially excluded patients with a calcium score ≥ 600. Area under the receiver-operating-characteristics curve (AUC) was used to evaluate CTA diagnostic accuracy compared to QCA in patients according to calcium score and pretest probability of CAD. Results Analysis of patient-based quantitative CTA accuracy revealed an AUC of 0.93 (95% confidence interval [CI] 0.90-0.95). AUC remained 0.93 (0.90-0.96) after excluding patients with known CAD but decreased to 0.81 (0.71-0.89) in patients with calcium score ≥ 600 (p=0.077). While AUC were similar (0.93, 0.92, and 0.93, respectively) for patients with intermediate, high pretest probability for CAD, and known CAD, negative predictive values were different: 0.90, 0.83, and 0.50, respectively. Negative predictive values decreased from 0.93 to 0.75 for patients with calcium score < or ≥ 100, respectively (p= 0.053). Conclusions Both pretest probability for CAD and coronary calcium scoring should be considered before using CTA for excluding obstructive CAD. CTA is less effective for this purpose in patients with calcium score ≥ 600 and in patients with a high pretest probability for obstructive CAD. PMID:22261160
Shiokawa, D; Tanuma, S
2004-10-01
In this study, we investigate the roles of two apoptotic endonucleases, CAD and DNase gamma, in neuronal apoptosis. High expression of CAD, but not DNase gamma, is detected in proliferating N1E-115 neuroblastoma cells, and apoptotic DNA fragmentation induced by staurosporine under proliferating conditions is abolished by the expression of a caspase-resistant form of ICAD. After the induction of neuronal differentiation, CAD disappearance and the induction of DNase gamma occur simultaneously in N1E-115 cells. Apoptotic DNA fragmentation that occurs under differentiating conditions is suppressed by the downregulation of DNase gamma caused by its antisense RNA. The induction of DNase gamma is also observed during neuronal differentiation of PC12 cells, and apoptotic DNA fragmentation induced by NGF deprivation is inhibited by the antisense-mediated downregulation of DNase gamma. These observations suggest that DNA fragmentation in neuronal apoptosis is catalyzed by either CAD or DNase gamma depending on the differentiation state. Furthermore, DNase gamma is suggested to be involved in naturally occurring apoptosis in developing nervous systems.
Investigation of IGES for CAD/CAE data transfer
NASA Technical Reports Server (NTRS)
Zobrist, George W.
1989-01-01
In a CAD/CAE facility there is always the possibility that one may want to transfer the design graphics database from the native system to a non-native system. This may occur because of dissimilar systems within an organization or a new CAD/CAE system is to be purchased. The Initial Graphics Exchange Specification (IGES) was developed in an attempt to solve this scenario. IGES is a neutral database format into which the CAD/CAE native database format can be translated to and from. Translating the native design database format to IGES requires a pre-processor and transling from IGES to the native database format requires a post-processor. IGES is an artifice to represent CAD/CAE product data in a neutral environment to allow interfacing applications, archive the database, interchange of product data between dissimilar CAD/CAE systems, and other applications. The intent here is to present test data on translating design product data from a CAD/CAE system to itself and to translate data initially prepared in IGES format to various native design formats. This information can be utilized in planning potential procurement and developing a design discipline within the CAD/CAE community.
Nguyen, Tan B.; Wang, Shijun; Anugu, Vishal; Rose, Natalie; McKenna, Matthew; Petrick, Nicholas; Burns, Joseph E.
2012-01-01
Purpose: To assess the diagnostic performance of distributed human intelligence for the classification of polyp candidates identified with computer-aided detection (CAD) for computed tomographic (CT) colonography. Materials and Methods: This study was approved by the institutional Office of Human Subjects Research. The requirement for informed consent was waived for this HIPAA-compliant study. CT images from 24 patients, each with at least one polyp of 6 mm or larger, were analyzed by using CAD software to identify 268 polyp candidates. Twenty knowledge workers (KWs) from a crowdsourcing platform labeled each polyp candidate as a true or false polyp. Two trials involving 228 KWs were conducted to assess reproducibility. Performance was assessed by comparing the area under the receiver operating characteristic curve (AUC) of KWs with the AUC of CAD for polyp classification. Results: The detection-level AUC for KWs was 0.845 ± 0.045 (standard error) in trial 1 and 0.855 ± 0.044 in trial 2. These were not significantly different from the AUC for CAD, which was 0.859 ± 0.043. When polyp candidates were stratified by difficulty, KWs performed better than CAD on easy detections; AUCs were 0.951 ± 0.032 in trial 1, 0.966 ± 0.027 in trial 2, and 0.877 ± 0.048 for CAD (P = .039 for trial 2). KWs who participated in both trials showed a significant improvement in performance going from trial 1 to trial 2; AUCs were 0.759 ± 0.052 in trial 1 and 0.839 ± 0.046 in trial 2 (P = .041). Conclusion: The performance of distributed human intelligence is not significantly different from that of CAD for colonic polyp classification. © RSNA, 2012 Supplemental material: http://radiology.rsna.org/lookup/suppl/doi:10.1148/radiol.11110938/-/DC1 PMID:22274839
DOE Office of Scientific and Technical Information (OSTI.GOV)
Toyama, Hirofumi; Arai, Fumio; Hosokawa, Kentaro
Highlights: Black-Right-Pointing-Pointer High N-cad expression was detected in E12.5 mouse FL LT-HSCs (EPCR{sup +} LSK cells). Black-Right-Pointing-Pointer Immunohistochemically, N-cad{sup +} HSCs co-localized with sinusoidal ECs (Lyve-1{sup +} cells) in E12.5 FL, but these gradually detached in E15.5 and E18.5 FL. Black-Right-Pointing-Pointer N-cad{sup +} LSK cells in E12.5 FL exhibited higher LTR activity versus N-cad{sup -} LSK cells, which decreased in E15.5 and E18.5. Black-Right-Pointing-Pointer N-cad expression may confer high LTR activity to HSCs by facilitating interactions with the perisinusoidal niche in FL. -- Abstract: Adult hematopoietic stem cells (HSCs) are maintained in a microenvironment known as the stem cell niche.more » The regulation of HSCs in fetal liver (FL) and their niche, however, remains to be elucidated. In this study, we investigated the role of N-cadherin (N-cad) in the maintenance of HSCs during FL hematopoiesis. By using anti-N-cad antibodies (Abs) produced by our laboratory, we detected high N-cad expression in embryonic day 12.5 (E12.5) mouse FL HSCs, but not in E15.5 and E18.5 FL. Immunofluorescence staining revealed that N-cad{sup +}c-Kit{sup +} and N-cad{sup +} endothelial protein C receptor (EPCR){sup +} HSCs co-localized with Lyve-1{sup +} sinusoidal endothelial cells (ECs) in E12.5 FL and that some of these cells also expressed N-cad. However, N-cad{sup +} HSCs were also observed to detach from the perisinusoidal niche at E15.5 and E18.5, concomitant with a down-regulation of N-cad and an up-regulation of E-cadherin (E-cad) in hepatic cells. Moreover, EPCR{sup +} long-term (LT)-HSCs were enriched in the N-cad{sup +}Lin{sup -}Sca-1{sup +}c-Kit{sup +} (LSK) fraction in E12.5 FL, but not in E15.5 or E18.5 FL. In a long-term reconstitution (LTR) activity assay, higher engraftment associated with N-cad{sup +} LSK cells versus N-cad{sup -} LSK cells in E12.5 FL when transplanted into lethally irradiated recipient mice. However, the higher engraftment of N-cad{sup +} LSK cells decreased subsequently in E15.5 and E18.5 FL. It is possible that N-cad expression conferred higher LTR activity to HSCs by facilitating interactions with the perisinusoidal niche, especially at E12.5. The down-regulation of N-cad during FL hematopoiesis may help us better understand the regulation and mobility of HSCs before migration into BM.« less
Delayed Contrast-Enhanced MRI of the Coronary Artery Wall in Takayasu Arteritis
Schneeweis, Christopher; Schnackenburg, Bernhard; Stuber, Matthias; Berger, Alexander; Schneider, Udo; Yu, Jing; Gebker, Rolf; Weiss, Robert G.; Fleck, Eckart; Kelle, Sebastian
2012-01-01
Background Takayasu arteritis (TA) is a rare form of chronic inflammatory granulomatous arteritis of the aorta and its major branches. Late gadolinium enhancement (LGE) with magnetic resonance imaging (MRI) has demonstrated its value for the detection of vessel wall alterations in TA. The aim of this study was to assess LGE of the coronary artery wall in patients with TA compared to patients with stable CAD. Methods We enrolled 9 patients (8 female, average age 46±13 years) with proven TA. In the CAD group 9 patients participated (8 male, average age 65±10 years). Studies were performed on a commercial 3T whole-body MR imaging system (Achieva; Philips, Best, The Netherlands) using a 3D inversion prepared navigator gated spoiled gradient-echo sequence, which was repeated 34–45 minutes after low-dose gadolinium administration. Results No coronary vessel wall enhancement was observed prior to contrast in either group. Post contrast, coronary LGE on IR scans was detected in 28 of 50 segments (56%) seen on T2-Prep scans in TA and in 25 of 57 segments (44%) in CAD patients. LGE quantitative assessment of coronary artery vessel wall CNR post contrast revealed no significant differences between the two groups (CNR in TA: 6.0±2.4 and 7.3±2.5 in CAD; p = 0.474). Conclusion Our findings suggest that LGE of the coronary artery wall seems to be common in patients with TA and similarly pronounced as in CAD patients. The observed coronary LGE seems to be rather unspecific, and differentiation between coronary vessel wall fibrosis and inflammation still remains unclear. PMID:23236382
Computer-aided design development transition for IPAD environment
NASA Technical Reports Server (NTRS)
Owens, H. G.; Mock, W. D.; Mitchell, J. C.
1980-01-01
The relationship of federally sponsored computer-aided design/computer-aided manufacturing (CAD/CAM) programs to the aircraft life cycle design process, an overview of NAAD'S CAD development program, an evaluation of the CAD design process, a discussion of the current computing environment within which NAAD is developing its CAD system, some of the advantages/disadvantages of the NAAD-IPAD approach, and CAD developments during transition into the IPAD system are discussed.
Computer Aided Drafting. Instructor's Guide.
ERIC Educational Resources Information Center
Henry, Michael A.
This guide is intended for use in introducing students to the operation and applications of computer-aided drafting (CAD) systems. The following topics are covered in the individual lessons: understanding CAD (CAD versus traditional manual drafting and care of software and hardware); using the components of a CAD system (primary and other input…
Levrini, G; Sghedoni, R; Mori, C; Botti, A; Vacondio, R; Nitrosi, A; Iori, M; Nicoli, F
2011-10-01
The aim of this study was to investigate the efficacy of a dedicated software tool for automated volume measurement of breast lesions in contrast-enhanced (CE) magnetic resonance mammography (MRM). The size of 52 breast lesions with a known histopathological diagnosis (three benign, 49 malignant) was automatically evaluated using different techniques. The volume of all lesions was measured automatically (AVM) from CE 3D MRM examinations by means of a computer-aided detection (CAD) system and compared with the size estimates based on maximum diameter measurement (MDM) on MRM, ultrasonography (US), mammography and histopathology. Compared with histopathology as the reference method, AVM understimated lesion size by 4% on average. This result was similar to MDM (3% understimation, not significantly different) but significantly better than US and mammographic lesion measurements (24% and 33% size underestimation, respectively). AVM is as accurate as MDM but faster. Both methods are more accurate for size assessment of breast lesions compared with US and mammography.
Structural Modeling Using "Scanning and Mapping" Technique
NASA Technical Reports Server (NTRS)
Amos, Courtney L.; Dash, Gerald S.; Shen, J. Y.; Ferguson, Frederick; Noga, Donald F. (Technical Monitor)
2000-01-01
Supported by NASA Glenn Center, we are in the process developing a structural damage diagnostic and monitoring system for rocket engines, which consists of five modules: Structural Modeling, Measurement Data Pre-Processor, Structural System Identification, Damage Detection Criterion, and Computer Visualization. The function of the system is to detect damage as it is incurred by the engine structures. The scientific principle to identify damage is to utilize the changes in the vibrational properties between the pre-damaged and post-damaged structures. The vibrational properties of the pre-damaged structure can be obtained based on an analytic computer model of the structure. Thus, as the first stage of the whole research plan, we currently focus on the first module - Structural Modeling. Three computer software packages are selected, and will be integrated for this purpose. They are PhotoModeler-Pro, AutoCAD-R14, and MSC/NASTRAN. AutoCAD is the most popular PC-CAD system currently available in the market. For our purpose, it plays like an interface to generate structural models of any particular engine parts or assembly, which is then passed to MSC/NASTRAN for extracting structural dynamic properties. Although AutoCAD is a powerful structural modeling tool, the complexity of engine components requires a further improvement in structural modeling techniques. We are working on a so-called "scanning and mapping" technique, which is a relatively new technique. The basic idea is to producing a full and accurate 3D structural model by tracing on multiple overlapping photographs taken from different angles. There is no need to input point positions, angles, distances or axes. Photographs can be taken by any types of cameras with different lenses. With the integration of such a modeling technique, the capability of structural modeling will be enhanced. The prototypes of any complex structural components will be produced by PhotoModeler first based on existing similar components, then passed to AutoCAD for modification and correction of any discrepancies seen in the Photomodeler version of the 3Dmodel. These three software packages are fully compatible. The DXF file can be used to transfer drawings among those packages. To begin this entire process, we are using a small replica of an actual engine blade as a test object. This paper introduces the accomplishment of our recent work.
Sporns, Peter B; Niederstadt, Thomas; Heindel, Walter; Raschke, Michael J; Hartensuer, René; Dittrich, Ralf; Hanning, Uta
2018-01-26
Cervical artery dissection (CAD) is an important etiology of ischemic stroke and early recognition is vital to protect patients from the major complication of cerebral embolization by administration of anticoagulants. The etiology of arterial dissections differ and can be either spontaneous or traumatic. Even though the historical gold standard is still catheter angiography, recent studies suggest a good performance of computed tomography angiography (CTA) for detection of CAD. We conducted this research to evaluate the variety and frequency of possible imaging signs of spontaneous and traumatic CAD and to guide neuroradiologists' decision making. Retrospective review of the database of our multiple injured patients admitted to the Department of Trauma, Hand, and Reconstructive Surgery of the University Hospital Münster in Germany (a level 1 trauma center) for patients with traumatic CAD (tCAD) and of our stroke database (2008-2015) for patients with spontaneous CAD (sCAD) and CT/CTA on initial clinical work-up. All images were evaluated concerning specific and sensitive radiological features for dissection by two experienced neuroradiologists. Imaging features were compared between the two etiologies. This study included 145 patients (99 male, 46 female; 45 ± 18.8 years of age), consisting of 126 dissected arteries with a traumatic and 43 with spontaneous etiology. Intimal flaps were more frequently observed after traumatic etiology (58.1% tCADs, 6.9% sCADs; p < 0.001); additionally, multivessel dissections were much more frequent in trauma patients (3 sCADs, 21 tCADs) and only less than half (42%) of the patients with traumatic dissections showed cervical spine fractures. Neuroradiologists should be aware that intimal flaps and multivessel dissections are more common after a traumatic etiology. In addition, it seems important to conduct a CTA in a trauma setting, even if no cervical spine fracture is detected.
Tan, Maxine; Aghaei, Faranak; Wang, Yunzhi; Zheng, Bin
2017-01-01
The purpose of this study is to evaluate a new method to improve performance of computer-aided detection (CAD) schemes of screening mammograms with two approaches. In the first approach, we developed a new case based CAD scheme using a set of optimally selected global mammographic density, texture, spiculation, and structural similarity features computed from all four full-field digital mammography (FFDM) images of the craniocaudal (CC) and mediolateral oblique (MLO) views by using a modified fast and accurate sequential floating forward selection feature selection algorithm. Selected features were then applied to a “scoring fusion” artificial neural network (ANN) classification scheme to produce a final case based risk score. In the second approach, we combined the case based risk score with the conventional lesion based scores of a conventional lesion based CAD scheme using a new adaptive cueing method that is integrated with the case based risk scores. We evaluated our methods using a ten-fold cross-validation scheme on 924 cases (476 cancer and 448 recalled or negative), whereby each case had all four images from the CC and MLO views. The area under the receiver operating characteristic curve was AUC = 0.793±0.015 and the odds ratio monotonically increased from 1 to 37.21 as CAD-generated case based detection scores increased. Using the new adaptive cueing method, the region based and case based sensitivities of the conventional CAD scheme at a false positive rate of 0.71 per image increased by 2.4% and 0.8%, respectively. The study demonstrated that supplementary information can be derived by computing global mammographic density image features to improve CAD-cueing performance on the suspicious mammographic lesions. PMID:27997380
Software Tools for Shipbuilding Productivity
1984-12-01
shipbuilding, is that design, manufacturing and robotic technology applications to shipbuilding have been proven. all aspects of shipbuilding is now a task...technical information about the process of Computer Aided Design (CAD) and Computer Aided Manufacturing (CAM) effectively has been a problem of serious and...Design (CAD) 3.4.1 CAD System Components 3.4.2 CAD System Benefits 3.4.3 New and Future CAD Technologies Computer Aided Manufacturing (CAM) 3.5.1 CAM
Wang, Shijun; McKenna, Matthew T; Nguyen, Tan B; Burns, Joseph E; Petrick, Nicholas; Sahiner, Berkman; Summers, Ronald M
2012-05-01
In this paper, we present development and testing results for a novel colonic polyp classification method for use as part of a computed tomographic colonography (CTC) computer-aided detection (CAD) system. Inspired by the interpretative methodology of radiologists using 3-D fly-through mode in CTC reading, we have developed an algorithm which utilizes sequences of images (referred to here as videos) for classification of CAD marks. For each CAD mark, we created a video composed of a series of intraluminal, volume-rendered images visualizing the detection from multiple viewpoints. We then framed the video classification question as a multiple-instance learning (MIL) problem. Since a positive (negative) bag may contain negative (positive) instances, which in our case depends on the viewing angles and camera distance to the target, we developed a novel MIL paradigm to accommodate this class of problems. We solved the new MIL problem by maximizing a L2-norm soft margin using semidefinite programming, which can optimize relevant parameters automatically. We tested our method by analyzing a CTC data set obtained from 50 patients from three medical centers. Our proposed method showed significantly better performance compared with several traditional MIL methods.
Wang, Shijun; McKenna, Matthew T.; Nguyen, Tan B.; Burns, Joseph E.; Petrick, Nicholas; Sahiner, Berkman
2012-01-01
In this paper we present development and testing results for a novel colonic polyp classification method for use as part of a computed tomographic colonography (CTC) computer-aided detection (CAD) system. Inspired by the interpretative methodology of radiologists using 3D fly-through mode in CTC reading, we have developed an algorithm which utilizes sequences of images (referred to here as videos) for classification of CAD marks. For each CAD mark, we created a video composed of a series of intraluminal, volume-rendered images visualizing the detection from multiple viewpoints. We then framed the video classification question as a multiple-instance learning (MIL) problem. Since a positive (negative) bag may contain negative (positive) instances, which in our case depends on the viewing angles and camera distance to the target, we developed a novel MIL paradigm to accommodate this class of problems. We solved the new MIL problem by maximizing a L2-norm soft margin using semidefinite programming, which can optimize relevant parameters automatically. We tested our method by analyzing a CTC data set obtained from 50 patients from three medical centers. Our proposed method showed significantly better performance compared with several traditional MIL methods. PMID:22552333
21 CFR 872.3661 - Optical Impression Systems for CAD/CAM.
Code of Federal Regulations, 2012 CFR
2012-04-01
... 21 Food and Drugs 8 2012-04-01 2012-04-01 false Optical Impression Systems for CAD/CAM. 872.3661... (CAD/CAM) is a device used to record the topographical characteristics of teeth, dental impressions, or... Design and Manufacturing (CAD/CAM) of Dental Restorations; Guidance for Industry and FDA.” For the...
21 CFR 872.3661 - Optical Impression Systems for CAD/CAM.
Code of Federal Regulations, 2013 CFR
2013-04-01
... 21 Food and Drugs 8 2013-04-01 2013-04-01 false Optical Impression Systems for CAD/CAM. 872.3661... (CAD/CAM) is a device used to record the topographical characteristics of teeth, dental impressions, or... Design and Manufacturing (CAD/CAM) of Dental Restorations; Guidance for Industry and FDA.” For the...
21 CFR 872.3661 - Optical Impression Systems for CAD/CAM.
Code of Federal Regulations, 2014 CFR
2014-04-01
... 21 Food and Drugs 8 2014-04-01 2014-04-01 false Optical Impression Systems for CAD/CAM. 872.3661... (CAD/CAM) is a device used to record the topographical characteristics of teeth, dental impressions, or... Design and Manufacturing (CAD/CAM) of Dental Restorations; Guidance for Industry and FDA.” For the...
A comparison study of image features between FFDM and film mammogram images
Jing, Hao; Yang, Yongyi; Wernick, Miles N.; Yarusso, Laura M.; Nishikawa, Robert M.
2012-01-01
Purpose: This work is to provide a direct, quantitative comparison of image features measured by film and full-field digital mammography (FFDM). The purpose is to investigate whether there is any systematic difference between film and FFDM in terms of quantitative image features and their influence on the performance of a computer-aided diagnosis (CAD) system. Methods: The authors make use of a set of matched film-FFDM image pairs acquired from cadaver breast specimens with simulated microcalcifications consisting of bone and teeth fragments using both a GE digital mammography system and a screen-film system. To quantify the image features, the authors consider a set of 12 textural features of lesion regions and six image features of individual microcalcifications (MCs). The authors first conduct a direct comparison on these quantitative features extracted from film and FFDM images. The authors then study the performance of a CAD classifier for discriminating between MCs and false positives (FPs) when the classifier is trained on images of different types (film, FFDM, or both). Results: For all the features considered, the quantitative results show a high degree of correlation between features extracted from film and FFDM, with the correlation coefficients ranging from 0.7326 to 0.9602 for the different features. Based on a Fisher sign rank test, there was no significant difference observed between the features extracted from film and those from FFDM. For both MC detection and discrimination of FPs from MCs, FFDM had a slight but statistically significant advantage in performance; however, when the classifiers were trained on different types of images (acquired with FFDM or SFM) for discriminating MCs from FPs, there was little difference. Conclusions: The results indicate good agreement between film and FFDM in quantitative image features. While FFDM images provide better detection performance in MCs, FFDM and film images may be interchangeable for the purposes of training CAD algorithms, and a single CAD algorithm may be applied to either type of images. PMID:22830771
Turnkey CAD/CAM systems' integration with IPAD systems
NASA Technical Reports Server (NTRS)
Blauth, R. E.
1980-01-01
Today's commercially available turnkey CAD/CAM systems provide a highly interactive environment, and support many specialized application functions for the design/drafting/manufacturing process. This paper presents an overview of several aerospace companies which have successfully integrated turnkey CAD/CAM systems with their own company wide engineering and manufacturing systems. It also includes a vendor's view of the benefits as well as the disadvantages of such integration efforts. Specific emphasis is placed upon the selection of standards for representing geometric engineering data and for communicating such information between different CAD/CAM systems.
Filip, Katarzyna; Grynkiewicz, Grzegorz; Gruza, Mariusz; Jatczak, Kamil; Zagrodzki, Bogdan
2014-01-01
Escin, a complex mixture of pentacyclic triterpene saponins obtained from horse chestnut seeds extract (HCSE; Aesculus hippocastanum L.), constitutes a traditional herbal active substance of preparations (drugs) used for a treatment of chronic venous insufficiency and capillary blood vessel leakage. A new approach to exploitation of pharmacological potential of this saponin complex has been recently proposed, in which the β-escin mixture is perceived as a source of a hitherto unavailable raw material, pentacyclic triterpene aglycone-protoescigenin. Although many liquid chromatography methods are described in the literature for saponins determination, analysis of protoescigenin is barely mentioned. In this work, a new ultra-high performance liquid chromatography (UHPLC) method developed for protoescigenin quantification has been described. CAD (charged aerosol detection), as a relatively new detection method based on aerosol charging, has been applied in this method as an alternative to ultraviolet (UV) detection. The influence of individual parameters on CAD response and sensitivity was studied. The detection was performed using CAD and UV (200 nm) simultaneously and the results were compared with reference to linearity, accuracy, precision and limit of detection.
Olsson, Petter; Holmbäck, Jan; Herslöf, Bengt
2014-11-21
This paper reports a simple chromatographic system to separate lipids classes as well as their molecular species. By the use of phenyl coated silica as stationary phase in combination with a simple mobile phase consisting of methanol and water, all tested lipid classes elute within 30 min. Furthermore, a method to accurately predict retention times of specific lipid components for this type of chromatography is presented. Common detection systems were used, namely evaporative light scattering detection (ELSD), charged aerosol detection (CAD), electrospray mass spectrometry (ESI-MS), and UV detection. Copyright © 2014 Elsevier B.V. All rights reserved.
Zhang, Yudong; Dong, Zhengchao; Phillips, Preetha; Wang, Shuihua; Ji, Genlin; Yang, Jiquan; Yuan, Ti-Fei
2015-01-01
Purpose: Early diagnosis or detection of Alzheimer's disease (AD) from the normal elder control (NC) is very important. However, the computer-aided diagnosis (CAD) was not widely used, and the classification performance did not reach the standard of practical use. We proposed a novel CAD system for MR brain images based on eigenbrains and machine learning with two goals: accurate detection of both AD subjects and AD-related brain regions. Method: First, we used maximum inter-class variance (ICV) to select key slices from 3D volumetric data. Second, we generated an eigenbrain set for each subject. Third, the most important eigenbrain (MIE) was obtained by Welch's t-test (WTT). Finally, kernel support-vector-machines with different kernels that were trained by particle swarm optimization, were used to make an accurate prediction of AD subjects. Coefficients of MIE with values higher than 0.98 quantile were highlighted to obtain the discriminant regions that distinguish AD from NC. Results: The experiments showed that the proposed method can predict AD subjects with a competitive performance with existing methods, especially the accuracy of the polynomial kernel (92.36 ± 0.94) was better than the linear kernel of 91.47 ± 1.02 and the radial basis function (RBF) kernel of 86.71 ± 1.93. The proposed eigenbrain-based CAD system detected 30 AD-related brain regions (Anterior Cingulate, Caudate Nucleus, Cerebellum, Cingulate Gyrus, Claustrum, Inferior Frontal Gyrus, Inferior Parietal Lobule, Insula, Lateral Ventricle, Lentiform Nucleus, Lingual Gyrus, Medial Frontal Gyrus, Middle Frontal Gyrus, Middle Occipital Gyrus, Middle Temporal Gyrus, Paracentral Lobule, Parahippocampal Gyrus, Postcentral Gyrus, Posterial Cingulate, Precentral Gyrus, Precuneus, Subcallosal Gyrus, Sub-Gyral, Superior Frontal Gyrus, Superior Parietal Lobule, Superior Temporal Gyrus, Supramarginal Gyrus, Thalamus, Transverse Temporal Gyrus, and Uncus). The results were coherent with existing literatures. Conclusion: The eigenbrain method was effective in AD subject prediction and discriminant brain-region detection in MRI scanning. PMID:26082713
Lodi, A; Angus, M; Nap, C J; Skellern, G; Nicolas, A
2015-01-01
A liquid chromatography coupled with charged aerosol detection (LC-CAD) procedure; capable of separating and quantifying the most common impurities of valine at levels as low as 0.05 per cent (m/m), has been developed. The procedure is simple (isocratic), rapid, linear, sensitive and repeatable. It employs a widely available and inexpensive stationary phase (C18).
A two-view ultrasound CAD system for spina bifida detection using Zernike features
NASA Astrophysics Data System (ADS)
Konur, Umut; Gürgen, Fikret; Varol, Füsun
2011-03-01
In this work, we address a very specific CAD (Computer Aided Detection/Diagnosis) problem and try to detect one of the relatively common birth defects - spina bifida, in the prenatal period. To do this, fetal ultrasound images are used as the input imaging modality, which is the most convenient so far. Our approach is to decide using two particular types of views of the fetal neural tube. Transcerebellar head (i.e. brain) and transverse (axial) spine images are processed to extract features which are then used to classify healthy (normal), suspicious (probably defective) and non-decidable cases. Decisions raised by two independent classifiers may be individually treated, or if desired and data related to both modalities are available, those decisions can be combined to keep matters more secure. Even more security can be attained by using more than two modalities and base the final decision on all those potential classifiers. Our current system relies on feature extraction from images for cases (for particular patients). The first step is image preprocessing and segmentation to get rid of useless image pixels and represent the input in a more compact domain, which is hopefully more representative for good classification performance. Next, a particular type of feature extraction, which uses Zernike moments computed on either B/W or gray-scale image segments, is performed. The aim here is to obtain values for indicative markers that signal the presence of spina bifida. Markers differ depending on the image modality being used. Either shape or texture information captured by moments may propose useful features. Finally, SVM is used to train classifiers to be used as decision makers. Our experimental results show that a promising CAD system can be actualized for the specific purpose. On the other hand, the performance of such a system would highly depend on the qualities of image preprocessing, segmentation, feature extraction and comprehensiveness of image data.
Kijima, Kumiko; Mita, Hajime; Kawakami, Mitsuyasu; Amada, Kei
2018-02-02
In the present study, we confirm that 2,4-dichlorophenoxyacetic acid (2,4-D) oxygenase from Sphingomonas agrestis 58-1 belongs to the family of Rieske non-heme iron aromatic ring-hydroxylating oxygenases, which comprise a core enzyme (oxygenase), ferredoxin, and oxidoreductase. It has previously been shown that cadAB genes are necessary for the conversion of 2,4-D to 2,4-dichlorophenol; however, the respective roles of ferredoxin and oxidoreductase in the 2,4-D oxygenase system from S. agrestis 58-1 remain unknown. Using nucleotide sequence analysis of the plasmid pCADAB1 from Sphingomonas sp. ERG5, which degrades 4-chloro-2-methylphenoxyacetic acid and 2,4-D, Nielsen et al. identified orf95, upstream of cadA, and orf98, downstream of cadB, which were predicted and designated as cadD (oxidoreductase) and cadC (ferredoxin), respectively (Nielsen et al., PLoS One, 8, 1-9, 2013). These designations were the result of sequence analysis; therefore, we constructed an expression system of CadABC and CadABCD in Escherichia coli and assayed their enzyme activities. Our findings indicate that CadC is essential for the activity of 2,4-D oxygenase and CadD promotes CadABC activity in recombinant E. coli cells. Copyright © 2018 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.
Leucker, Thorsten M.; Valenta, Ines; Schindler, Thomas Hellmut
2017-01-01
Positron emission tomography/computed tomography (PET/CT) applied with positron-emitting flow tracers such as 13N-ammonia and 82Rubidium enables the quantification of both myocardial perfusion and myocardial blood flow (MBF) in milliliters per gram per minute for coronary artery disease (CAD) detection and characterization. The detection of a regional myocardial perfusion defect during vasomotor stress commonly identifies the culprit lesion or most severe epicardial narrowing, whereas adding regional hyperemic MBFs, myocardial flow reserve (MFR), and/or longitudinal flow decrease may also signify less severe but flow-limiting stenosis in multivessel CAD. The addition of regional hyperemic flow parameters, therefore, may afford a comprehensive identification and characterization of flow-limiting effects of multivessel CAD. The non-specific origin of decreases in hyperemic MBFs and MFR, however, prompts an evaluation and interpretation of regional flow in the appropriate context with the presence of obstructive CAD. Conversely, initial results of the assessment of a longitudinal hyperemic flow gradient suggest this novel flow parameter to be specifically related to increases in CAD caused epicardial resistance. The concurrent assessment of myocardial perfusion and several hyperemic flow parameters with PET/CT may indeed open novel avenues of precision medicine to guide coronary revascularization procedures that may potentially lead to a further improvement in cardiovascular outcomes in CAD patients. PMID:28770213
den Dekker, M A M; van den Dungen, J J A M; Tielliu, I F J; Tio, R A; Jaspers, M M J J R; Oudkerk, M; Vliegenthart, R
2013-12-01
Patients with extra-cardiac arterial disease (ECAD) are at high risk of coronary artery disease (CAD). Prevalence of silent, significant CAD in patients with stenotic or aneurysmal ECAD was examined. Early detection and treatment may reduce CAD mortality in this high-risk group. ECAD patients without cardiac complaints underwent computed tomography (CT) for calcium scoring, coronary CT angiography (cCTA) if calcium score was 1,000 or under, and adenosine perfusion magnetic resonance imaging (APMR) if there was no left main stenosis. Significant CAD was defined as calcium score over 1,000, cCTA-detected coronary stenosis of at least 50% lumen diameter, and/or APMR-detected inducible myocardial ischemia. In cases of left main stenosis (or equivalent) or myocardial ischemia, patients were referred to a cardiologist. The prevalence of significant CAD was 56.8% (95% CI 47.5 to 66.0). One-hundred and eleven patients were included. Eighty-four patients (76%) had stenotic ECAD, and 27 (24%) had aneurysmal disease. In patients with stenotic ECAD, significant coronary stenosis was present in 32 (38%) and inducible ischemia in eight (12%). Corresponding results in aneurysmal ECAD were eight (30%) and two (11%), respectively (p for difference >.05). Sixteen (19%) patients with stenotic and six (22%) with aneurysmal ECAD were referred to a cardiologist, with subsequent cardiac intervention in seven (44%) and three (50%), respectively (both p >.05). Patients with stenotic or aneurysmal ECAD have a high prevalence of silent, significant CAD. Copyright © 2013 European Society for Vascular Surgery. Published by Elsevier Ltd. All rights reserved.
DOT National Transportation Integrated Search
2000-03-01
The Denver Regional Transportation District (RTD) acquired a CAD/AVL system that became fully operational in 1996. The CAD/AVL system added radio channels and covert alarms in buses, located vehicles in real time, and monitored schedule adherence. Th...
NASA Astrophysics Data System (ADS)
Liu, Z.; Kar, J.; Zeng, S.; Tackett, J. L.; Vaughan, M.; Trepte, C. R.; Omar, A. H.; Hu, Y.; Winker, D. M.
2017-12-01
In the CALIPSO retrieval algorithm, detection layers in the lidar measurements is followed by their classification as a "cloud" or "aerosol" using 5-dimensional probability density functions (PDFs). The five dimensions are the mean attenuated backscatter at 532 nm, the layer integrated total attenuated color ratio, the mid-layer altitude, integrated volume depolarization ratio and latitude. The new version 4 (V4) level 2 (L2) data products, released in November 2016, are the first major revision to the L2 product suite since May 2010. Significant calibration changes in the V4 level 1 data necessitated substantial revisions to the V4 L2 CAD algorithm. Accordingly, a new set of PDFs was generated to derive the V4 L2 data products. The V4 CAD algorithm is now applied to layers detected in the stratosphere, where volcanic layers and occasional cloud and smoke layers are observed. Previously, these layers were designated as `stratospheric', and not further classified. The V4 CAD algorithm is also applied to all layers detected at single shot (333 m) resolution. In prior data releases, single shot detections were uniformly classified as clouds. The CAD PDFs used in the earlier releases were generated using a full year (2008) of CALIPSO measurements. Because the CAD algorithm was not applied to stratospheric features, the properties of these layers were not incorporated into the PDFs. When building the V4 PDFs, the 2008 data were augmented with additional data from June 2011, and all stratospheric features were included. The Nabro and Puyehue-Cordon volcanos erupted in June 2011, and volcanic aerosol layers were observed in the upper troposphere and lower stratosphere in both the northern and southern hemispheres. The June 2011 data thus provides the stratospheric aerosol properties needed for comprehensive PDF generation. In contrast to earlier versions of the PDFs, which were generated based solely on observed distributions, construction of the V4 PDFs considered the typical optical and physical properties of feature subtypes, and thus provide a more comprehensive physical basis for discrimination. As a result of the changes made, the V4 CAD provides better performance and more reliable confidence levels. We describe the generation of V4 PDFs and present characterization and performance of the new CAD algorithm.
Canine adenovirus type 1 in a fennec fox (Vulpes zerda).
Choi, Jeong-Won; Lee, Hyun-Kyoung; Kim, Seong-Hee; Kim, Yeon-Hee; Lee, Kyoung-Ki; Lee, Myoung-Heon; Oem, Jae-Ku
2014-12-01
A 10-mo-old female fennec fox (Vulpes zerda) with drooling suddenly died and was examined postmortem. Histologic examination of different tissue samples was performed. Vacuolar degeneration and diffuse fatty change were observed in the liver. Several diagnostic methods were used to screen for canine parvovirus, canine distemper virus, canine influenza virus, canine coronavirus, canine parainfluenza virus, and canine adenovirus (CAdV). Only CAdV type 1 (CAdV-1) was detected in several organs (liver, lung, brain, kidney, spleen, and heart), and other viruses were not found. CAdV-1 was confirmed by virus isolation and nucleotide sequencing.
Papadiochou, Sofia; Pissiotis, Argirios L
2018-04-01
The comparative assessment of computer-aided design and computer-aided manufacturing (CAD-CAM) technology and other fabrication techniques pertaining to marginal adaptation should be documented. Limited evidence exists on the effect of restorative material on the performance of a CAD-CAM system relative to marginal adaptation. The purpose of this systematic review was to investigate whether the marginal adaptation of CAD-CAM single crowns, fixed dental prostheses, and implant-retained fixed dental prostheses or their infrastructures differs from that obtained by other fabrication techniques using a similar restorative material and whether it depends on the type of restorative material. An electronic search of English-language literature published between January 1, 2000, and June 30, 2016, was conducted of the Medline/PubMed database. Of the 55 included comparative studies, 28 compared CAD-CAM technology with conventional fabrication techniques, 12 contrasted CAD-CAM technology and copy milling, 4 compared CAD-CAM milling with direct metal laser sintering (DMLS), and 22 investigated the performance of a CAD-CAM system regarding marginal adaptation in restorations/infrastructures produced with different restorative materials. Most of the CAD-CAM restorations/infrastructures were within the clinically acceptable marginal discrepancy (MD) range. The performance of a CAD-CAM system relative to marginal adaptation is influenced by the restorative material. Compared with CAD-CAM, most of the heat-pressed lithium disilicate crowns displayed equal or smaller MD values. Slip-casting crowns exhibited similar or better marginal accuracy than those fabricated with CAD-CAM. Cobalt-chromium and titanium implant infrastructures produced using a CAD-CAM system elicited smaller MD values than zirconia. The majority of cobalt-chromium restorations/infrastructures produced by DMLS displayed better marginal accuracy than those fabricated with the casting technique. Compared with copy milling, the majority of zirconia restorations/infrastructures produced by CAD-CAM milling exhibited better marginal adaptation. No clear conclusions can be drawn about the superiority of CAD-CAM milling over the casting technique and DMLS regarding marginal adaptation. Copyright © 2017 Editorial Council for the Journal of Prosthetic Dentistry. Published by Elsevier Inc. All rights reserved.
Learning-based image preprocessing for robust computer-aided detection
NASA Astrophysics Data System (ADS)
Raghupathi, Laks; Devarakota, Pandu R.; Wolf, Matthias
2013-03-01
Recent studies have shown that low dose computed tomography (LDCT) can be an effective screening tool to reduce lung cancer mortality. Computer-aided detection (CAD) would be a beneficial second reader for radiologists in such cases. Studies demonstrate that while iterative reconstructions (IR) improve LDCT diagnostic quality, it however degrades CAD performance significantly (increased false positives) when applied directly. For improving CAD performance, solutions such as retraining with newer data or applying a standard preprocessing technique may not be suffice due to high prevalence of CT scanners and non-uniform acquisition protocols. Here, we present a learning-based framework that can adaptively transform a wide variety of input data to boost an existing CAD performance. This not only enhances their robustness but also their applicability in clinical workflows. Our solution consists of applying a suitable pre-processing filter automatically on the given image based on its characteristics. This requires the preparation of ground truth (GT) of choosing an appropriate filter resulting in improved CAD performance. Accordingly, we propose an efficient consolidation process with a novel metric. Using key anatomical landmarks, we then derive consistent feature descriptors for the classification scheme that then uses a priority mechanism to automatically choose an optimal preprocessing filter. We demonstrate CAD prototype∗ performance improvement using hospital-scale datasets acquired from North America, Europe and Asia. Though we demonstrated our results for a lung nodule CAD, this scheme is straightforward to extend to other post-processing tools dedicated to other organs and modalities.
Non-invasive assessment of low- and intermediate-risk patients with chest pain
Balfour, Pelbreton C.; Gonzalez, Jorge A.; Kramer, Christopher M.
2016-01-01
Coronary artery disease (CAD) remains a significant global public health burden despite advancements in prevention and therapeutic strategies. Common non-invasive imaging modalities, anatomic and functional, are available for the assessment of patients with stable chest pain. Exercise electrocardiography is a long-standing method for evaluation for CAD and remains the initial test for the majority of patients who can exercise adequately with a baseline interpretable electrocardiogram. The addition of cardiac imaging to exercise testing provides incremental benefit for accurate diagnosis for CAD and is particularly useful in patients who are unable to exercise adequately and/or have uninterpretable electrocardiograms. Radionuclide myocardial perfusion imaging and echocardiography with exercise or pharmacological stress provide high sensitivity and specificity in the detection and further risk stratification of patients with CAD. Recently, coronary computed tomography angiography has demonstrated its growing role to rule out significant CAD given its high negative predictive value. Although less available, stress cardiac magnetic resonance provides a comprehensive assessment of cardiac structure and function and provides a high diagnostic accuracy in the detection of CAD. The utilization of non-invasive testing is complex due to various advantages and limitations, particularly in the assessment of low- and intermediate-risk patients with chest pain, where no single study is suitable for all patients. This review will describe currently available non-invasive modalities, along with current evidence-based guidelines and appropriate use criteria in the assessment of low- and intermediate-risk patients with suspected, stable CAD. PMID:27717538
DOE Office of Scientific and Technical Information (OSTI.GOV)
Smith, K.L.
This document has been developed to provide guidance in the interchange of electronic CAD data with Martin Marietta Energy Systems, Inc., Oak Ridge, Tennessee. It is not meant to be as comprehensive as the existing standards and specifications, but to provide a minimum set of practices that will enhance the success of the CAD data exchange. It is now a Department of Energy (DOE) Oak Ridge Field Office requirement that Architect-Engineering (A-E) firms prepare all new drawings using a Computer Aided Design (CAD) system that is compatible with the Facility Manager`s (FM) CAD system. For Oak Ridge facilities, the CADmore » system used for facility design by the FM, Martin Marietta Energy Systems, Inc., is Intregraph. The format for interchange of CAD data for Oak Ridge facilities will be the Intergraph MicroStation/IGDS format.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Matsui, T; Ohki, M; Nakamura, T
Purpose: Sjoegren's syndrome (SS) is an autoimmune disease invading mainly salivary and lacrimal glands. Ultrasonography is used for an initial and non-invasive examination of this disease. However, the ultrasonography diagnosis tends to lack in objectivity and depends on the operator's skills. The purpose of this study is to propose a computer-aided diagnosis (CAD) system for SS based on a dual-tree complex wavelet transform (DT-CWT) and machine learning. Methods: The subjects of this study were 174 patients suspected of having SS at Nagasaki University Hospital and examined with ultrasonography of the parotid glands. Out of these patients, 77 patients were diagnosedmore » with SS by sialography. A region of interest (ROI) of 128 × 128 pixels was set within the parotid gland that was indicated by a dental radiologist. The DT-CWT was applied to the images in the ROI and every image was decomposed into 72 sub-images of the real and imaginary components in six different resolution levels and six orientations. The statistical features of the sub-image were calculated and used as data input for the support vector machine (SVM) classifier for the detection of SS. A ten-fold cross-validation was employed to verify the Resultof SVM. The accuracy of diagnosis was compared by a CAD system with a human observer performance. Results: The sensitivity, specificity, and accuracy in the detection of SS were 95%, 86%, and 91% through our CAD system respectively, while those by a human observer were 84%, 81%, and 83% respectively. Conclusion: The proposed computer-aided diagnosis system for Sjoegren's syndrome in ultrasonography based on dual-tree complex wavelet transform had a better performance than a human observer.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Young, S; Lo, P; Kim, G
2015-06-15
Purpose: While Lung Cancer Screening CT is being performed at low doses, the purpose of this study was to investigate the effects of further reducing dose on the performance of a CAD nodule-detection algorithm. Methods: We selected 50 cases from our local database of National Lung Screening Trial (NLST) patients for which we had both the image series and the raw CT data from the original scans. All scans were acquired with fixed mAs (25 for standard-sized patients, 40 for large patients) on a 64-slice scanner (Sensation 64, Siemens Healthcare). All images were reconstructed with 1-mm slice thickness, B50 kernel.more » 10 of the cases had at least one nodule reported on the NLST reader forms. Based on a previously-published technique, we added noise to the raw data to simulate reduced-dose versions of each case at 50% and 25% of the original NLST dose (i.e. approximately 1.0 and 0.5 mGy CTDIvol). For each case at each dose level, the CAD detection algorithm was run and nodules greater than 4 mm in diameter were reported. These CAD results were compared to “truth”, defined as the approximate nodule centroids from the NLST reports. Subject-level mean sensitivities and false-positive rates were calculated for each dose level. Results: The mean sensitivities of the CAD algorithm were 35% at the original dose, 20% at 50% dose, and 42.5% at 25% dose. The false-positive rates, in decreasing-dose order, were 3.7, 2.9, and 10 per case. In certain cases, particularly in larger patients, there were severe photon-starvation artifacts, especially in the apical region due to the high-attenuating shoulders. Conclusion: The detection task was challenging for the CAD algorithm at all dose levels, including the original NLST dose. However, the false-positive rate at 25% dose approximately tripled, suggesting a loss of CAD robustness somewhere between 0.5 and 1.0 mGy. NCI grant U01 CA181156 (Quantitative Imaging Network); Tobacco Related Disease Research Project grant 22RT-0131.« less
Construction and comparative evaluation of different activity detection methods in brain FDG-PET.
Buchholz, Hans-Georg; Wenzel, Fabian; Gartenschläger, Martin; Thiele, Frank; Young, Stewart; Reuss, Stefan; Schreckenberger, Mathias
2015-08-18
We constructed and evaluated reference brain FDG-PET databases for usage by three software programs (Computer-aided diagnosis for dementia (CAD4D), Statistical Parametric Mapping (SPM) and NEUROSTAT), which allow a user-independent detection of dementia-related hypometabolism in patients' brain FDG-PET. Thirty-seven healthy volunteers were scanned in order to construct brain FDG reference databases, which reflect the normal, age-dependent glucose consumption in human brain, using either software. Databases were compared to each other to assess the impact of different stereotactic normalization algorithms used by either software package. In addition, performance of the new reference databases in the detection of altered glucose consumption in the brains of patients was evaluated by calculating statistical maps of regional hypometabolism in FDG-PET of 20 patients with confirmed Alzheimer's dementia (AD) and of 10 non-AD patients. Extent (hypometabolic volume referred to as cluster size) and magnitude (peak z-score) of detected hypometabolism was statistically analyzed. Differences between the reference databases built by CAD4D, SPM or NEUROSTAT were observed. Due to the different normalization methods, altered spatial FDG patterns were found. When analyzing patient data with the reference databases created using CAD4D, SPM or NEUROSTAT, similar characteristic clusters of hypometabolism in the same brain regions were found in the AD group with either software. However, larger z-scores were observed with CAD4D and NEUROSTAT than those reported by SPM. Better concordance with CAD4D and NEUROSTAT was achieved using the spatially normalized images of SPM and an independent z-score calculation. The three software packages identified the peak z-scores in the same brain region in 11 of 20 AD cases, and there was concordance between CAD4D and SPM in 16 AD subjects. The clinical evaluation of brain FDG-PET of 20 AD patients with either CAD4D-, SPM- or NEUROSTAT-generated databases from an identical reference dataset showed similar patterns of hypometabolism in the brain regions known to be involved in AD. The extent of hypometabolism and peak z-score appeared to be influenced by the calculation method used in each software package rather than by different spatial normalization parameters.
An application protocol for CAD to CAD transfer of electronic information
NASA Technical Reports Server (NTRS)
Azu, Charles C., Jr.
1993-01-01
The exchange of Computer Aided Design (CAD) information between dissimilar CAD systems is a problem. This is especially true for transferring electronics CAD information such as multi-chip module (MCM), hybrid microcircuit assembly (HMA), and printed circuit board (PCB) designs. Currently, there exists several neutral data formats for transferring electronics CAD information. These include IGES, EDIF, and DXF formats. All these formats have limitations for use in exchanging electronic data. In an attempt to overcome these limitations, the Navy's MicroCIM program implemented a project to transfer hybrid microcircuit design information between dissimilar CAD systems. The IGES (Initial Graphics Exchange Specification) format is used since it is well established within the CAD industry. The goal of the project is to have a complete transfer of microelectronic CAD information, using IGES, without any data loss. An Application Protocol (AP) is being developed to specify how hybrid microcircuit CAD information will be represented by IGES entity constructs. The AP defines which IGES data items are appropriate for describing HMA geometry, connectivity, and processing as well as HMA material characteristics.
Thermogram breast cancer prediction approach based on Neutrosophic sets and fuzzy c-means algorithm.
Gaber, Tarek; Ismail, Gehad; Anter, Ahmed; Soliman, Mona; Ali, Mona; Semary, Noura; Hassanien, Aboul Ella; Snasel, Vaclav
2015-08-01
The early detection of breast cancer makes many women survive. In this paper, a CAD system classifying breast cancer thermograms to normal and abnormal is proposed. This approach consists of two main phases: automatic segmentation and classification. For the former phase, an improved segmentation approach based on both Neutrosophic sets (NS) and optimized Fast Fuzzy c-mean (F-FCM) algorithm was proposed. Also, post-segmentation process was suggested to segment breast parenchyma (i.e. ROI) from thermogram images. For the classification, different kernel functions of the Support Vector Machine (SVM) were used to classify breast parenchyma into normal or abnormal cases. Using benchmark database, the proposed CAD system was evaluated based on precision, recall, and accuracy as well as a comparison with related work. The experimental results showed that our system would be a very promising step toward automatic diagnosis of breast cancer using thermograms as the accuracy reached 100%.
A hybrid model for automatic identification of risk factors for heart disease.
Yang, Hui; Garibaldi, Jonathan M
2015-12-01
Coronary artery disease (CAD) is the leading cause of death in both the UK and worldwide. The detection of related risk factors and tracking their progress over time is of great importance for early prevention and treatment of CAD. This paper describes an information extraction system that was developed to automatically identify risk factors for heart disease in medical records while the authors participated in the 2014 i2b2/UTHealth NLP Challenge. Our approaches rely on several nature language processing (NLP) techniques such as machine learning, rule-based methods, and dictionary-based keyword spotting to cope with complicated clinical contexts inherent in a wide variety of risk factors. Our system achieved encouraging performance on the challenge test data with an overall micro-averaged F-measure of 0.915, which was competitive to the best system (F-measure of 0.927) of this challenge task. Copyright © 2015 Elsevier Inc. All rights reserved.
2012-01-01
Background Coronary artery calcifications (CAC) are markers of coronary atherosclerosis, but do not correlate well with stenosis severity. This study intended to evaluate clinical situations where a combined approach of coronary calcium scoring (CS) and nuclear stress test (SPECT-MPI) is useful for the detection of relevant CAD. Methods Patients with clinical indication for invasive coronary angiography (ICA) were included into our study during 08/2005-09/2008. At first all patients underwent CS procedure as part of the study protocol performed by either using a multidetector computed tomography (CT) scanner or a dual-source CT imager. CAC were automatically defined by dedicated software and the Agatston score was semi-automatically calculated. A stress-rest SPECT-MPI study was performed afterwards and scintigraphic images were evaluated quantitatively. Then all patients underwent ICA. Thereby significant CAD was defined as luminal stenosis ≥75% in quantitative coronary analysis (QCA) in ≥1 epicardial vessel. To compare data lacking Gaussian distribution an unpaired Wilcoxon-Test (Mann–Whitney) was used. Otherwise a Students t-test for unpaired samples was applied. Calculations were considered to be significant at a p-value of <0.05. Results We consecutively included 351 symptomatic patients (mean age: 61.2±12.3 years; range: 18–94 years; male: n=240) with a mean Agatston score of 258.5±512.2 (range: 0–4214). ICA verified exclusion of significant CAD in 66/67 (98.5%) patients without CAC. CAC was detected in remaining 284 patients. In 132/284 patients (46.5%) with CS>0 significant CAD was confirmed by ICA, and excluded in 152/284 (53.5%) patients. Sensitivity for CAD detection by CS alone was calculated as 99.2%, specificity was 30.3%, and negative predictive value was 98.5%. An additional SPECT in patients with CS>0 increased specificity to 80.9% while reducing sensitivity to 87.9%. Diagnostic accuracy was 84.2%. Conclusions In patients without CS=0 significant CAD can be excluded with a high negative predictive value by CS alone. An additional SPECT-MPI in those patients with CS>0 leads to a high diagnostic accuracy for the detection of CAD while reducing the number of patients needing invasive diagnostic procedure. PMID:23206557
Yang, Li-Juan; Liu, Yu-Qin; Gu, Bei; Bian, Xiao-Cui; Feng, Hai-Liang; Yang, Zhen-Li; Liu, Yan-Yan
2010-12-01
To investigate the role that E-cadherin (E-cad) plays on cell adhesion and proliferation of human breast carcinoma. E-cad expression vector was transfected into an E-cad-negative human breast carcinoma MDA-MB-231 cells. G418 was used to screen positive clones. E-cad, β-catenin (β-cat) and cyclin D1 expressions of these clones were confirmed by Western blot. Their cell-cell and cell-matrix adhesion abilities were detected. E-cad/β-catenin interaction was confirmed by immunoprecipitation. Cell proliferation was evaluated by MTT. Cell apoptosis was analyzed by flow cytometry. Direct two-step immunocytochemistry was used to detect the localization of β-cat. E-cad(+) cell strains Ecad-231-7 and Ecad-231-9 were established. When cultured in ultra-low-binding dishes Ecad-231 cells grow in suspension while Ecad-231-7 and Ecad-231-9 cells grow in large clamps. When co-cultured with HCT116 cells, the average adhesion rates at 30 min are 39.0%, 60.0% and 59.5% for MDA-MB-231, Ecad-231-7 and Ecad-231-9 respectively. The average detachment rates by EDTA for 5 min are 37.4%, 4.2% and 7.4% respectively. So E-cad expression enhanced hemotypic and heterotypic cell-cell adhesion and cell-matrix adhesion. Forced exogenously expressed E-cad could combine with endogenous β-cat, whereas down stream cyclin D1 expression was significantly decreased, as evidenced by Western blot. The rates of cell apoptosis of MDA-MB-231, Ecad-231-7 and Ecad-231-9 were 1.8%, 2.0% and 2.1%. Expression of E-cad had no obvious effect on the apoptosis of tumor cells with regular culture. β-cat increased in the cytoplasma. Two monoclonal tumor cell strains (Ecad-231-7 and Ecad-231-9) stably expressing E-cad were successfully established. E-cad could enhance adhesion and inhibit proliferation of human breast carcinoma cells through a pathway involving β-cat and cyclin D1.
ERIC Educational Resources Information Center
Franken, Ken; And Others
A multidisciplinary research team was assembled to review existing computer-aided drafting (CAD) systems for the purpose of enabling staff in the Design Drafting Department at Linn Technical College (Missouri) to select the best system out of the many CAD systems in existence. During the initial stage of the evaluation project, researchers…
Understanding dental CAD/CAM for restorations--accuracy from a mechanical engineering viewpoint.
Tapie, Laurent; Lebon, Nicolas; Mawussi, Bernardin; Fron-Chabouis, Hélène; Duret, Francois; Attal, Jean-Pierre
2015-01-01
As is the case in the field of medicine, as well as in most areas of daily life, digital technology is increasingly being introduced into dental practice. Computer-aided design/ computer-aided manufacturing (CAD/CAM) solutions are available not only for chairside practice but also for creating inlays, crowns, fixed partial dentures (FPDs), implant abutments, and other dental prostheses. CAD/CAM dental practice can be considered as the handling of devices and software processing for the almost automatic design and creation of dental restorations. However, dentists who want to use dental CAD/CAM systems often do not have enough information to understand the variations offered by such technology practice. Knowledge of the random and systematic errors in accuracy with CAD/CAM systems can help to achieve successful restorations with this technology, and help with the purchasing of a CAD/CAM system that meets the clinical needs of restoration. This article provides a mechanical engineering viewpoint of the accuracy of CAD/ CAM systems, to help dentists understand the impact of this technology on restoration accuracy.
NASA Astrophysics Data System (ADS)
Harkness, E. F.; Lim, Y. Y.; Wilson, M. W.; Haq, R.; Zhou, J.; Tate, C.; Maxwell, A. J.; Astley, S. M.; Gilbert, F. J.
2015-03-01
Digital breast tomosynthesis (DBT) addresses limitations of 2-D projection imaging for detection of masses. Microcalcification clusters may be more difficult to appreciate in DBT as individual calcifications within clusters may appear on different slices. This research aims to evaluate the performance of ImageChecker 3D Calc CAD v1.0. Women were recruited as part of the TOMMY trial. From the trial, 169 were included in this study. The DBT images were processed with the computer aided detection (CAD) algorithm. Three consultant radiologists reviewed the images and recorded whether CAD prompts were on or off target. 79/80 (98.8%) malignant cases had a prompt on the area of microcalcification. In these cases, there were 1-15 marks (median 5) with the majority of false prompts (n=326/431) due to benign (68%) and vascular (24%) calcifications. Of 89 normal/benign cases, there were 1-13 prompts (median 3), 27 (30%) had no prompts and the majority of false prompts (n=238) were benign (77%) calcifications. CAD is effective in prompting malignant microcalcification clusters and may overcome the difficulty of detecting clusters in slice images. Although there was a high rate of false prompts, further advances in the software may improve specificity.
Computer-Aided Diagnostic (CAD) Scheme by Use of Contralateral Subtraction Technique
NASA Astrophysics Data System (ADS)
Nagashima, Hiroyuki; Harakawa, Tetsumi
We developed a computer-aided diagnostic (CAD) scheme for detection of subtle image findings of acute cerebral infarction in brain computed tomography (CT) by using a contralateral subtraction technique. In our computerized scheme, the lateral inclination of image was first corrected automatically by rotating and shifting. The contralateral subtraction image was then derived by subtraction of reversed image from original image. Initial candidates for acute cerebral infarctions were identified using the multiple-thresholding and image filtering techniques. As the 1st step for removing false positive candidates, fourteen image features were extracted in each of the initial candidates. Halfway candidates were detected by applying the rule-based test with these image features. At the 2nd step, five image features were extracted using the overlapping scale with halfway candidates in interest slice and upper/lower slice image. Finally, acute cerebral infarction candidates were detected by applying the rule-based test with five image features. The sensitivity in the detection for 74 training cases was 97.4% with 3.7 false positives per image. The performance of CAD scheme for 44 testing cases had an approximate result to training cases. Our CAD scheme using the contralateral subtraction technique can reveal suspected image findings of acute cerebral infarctions in CT images.
Ghafoorian, Mohsen; Karssemeijer, Nico; Heskes, Tom; Bergkamp, Mayra; Wissink, Joost; Obels, Jiri; Keizer, Karlijn; de Leeuw, Frank-Erik; Ginneken, Bram van; Marchiori, Elena; Platel, Bram
2017-01-01
Lacunes of presumed vascular origin (lacunes) are associated with an increased risk of stroke, gait impairment, and dementia and are a primary imaging feature of the small vessel disease. Quantification of lacunes may be of great importance to elucidate the mechanisms behind neuro-degenerative disorders and is recommended as part of study standards for small vessel disease research. However, due to the different appearance of lacunes in various brain regions and the existence of other similar-looking structures, such as perivascular spaces, manual annotation is a difficult, elaborative and subjective task, which can potentially be greatly improved by reliable and consistent computer-aided detection (CAD) routines. In this paper, we propose an automated two-stage method using deep convolutional neural networks (CNN). We show that this method has good performance and can considerably benefit readers. We first use a fully convolutional neural network to detect initial candidates. In the second step, we employ a 3D CNN as a false positive reduction tool. As the location information is important to the analysis of candidate structures, we further equip the network with contextual information using multi-scale analysis and integration of explicit location features. We trained, validated and tested our networks on a large dataset of 1075 cases obtained from two different studies. Subsequently, we conducted an observer study with four trained observers and compared our method with them using a free-response operating characteristic analysis. Shown on a test set of 111 cases, the resulting CAD system exhibits performance similar to the trained human observers and achieves a sensitivity of 0.974 with 0.13 false positives per slice. A feasibility study also showed that a trained human observer would considerably benefit once aided by the CAD system.
Zhang, Lijun; Song, Xiantao; Dong, Li; Li, Jianan; Dou, Ruiyu; Fan, Zhanming; An, Jing; Li, Debiao
2018-04-30
The purpose of the work was to evaluate the incremental diagnostic value of free-breathing, contrast-enhanced, whole-heart, 3 T cardiovascular magnetic resonance coronary angiography (CE-MRCA) to stress/rest myocardial perfusion imaging (MPI) and late gadolinium enhancement (LGE) imaging for detecting coronary artery disease (CAD). Fifty-one patients with suspected CAD underwent a comprehensive cardiovascular magnetic resonance (CMR) examination (CE-MRCA, MPI, and LGE). The additive diagnostic value of MRCA to MPI and LGE was evaluated using invasive x-ray coronary angiography (XA) as the standard for defining functionally significant CAD (≥ 50% stenosis in vessels > 2 mm in diameter). 90.2% (46/51) patients (54.0 ± 11.5 years; 71.7% men) completed CE-MRCA successfully. On per-patient basis, compared to MPI/LGE alone or MPI alone, the addition of MRCA resulted in higher sensitivity (100% vs. 76.5%, p < 0.01), no change in specificity (58.3% vs. 66.7%, p = 0.6), and higher accuracy (89.1% vs 73.9%, p < 0.01) for CAD detection (prevalence = 73.9%). Compared to LGE alone, the addition of CE-MRCA resulted in higher sensitivity (97.1% vs. 41.2%, p < 0.01), inferior specificity (83.3% vs. 91.7%, p = 0.02), and higher diagnostic accuracy (93.5% vs. 54.3%, p < 0.01). The inclusion of successful free-breathing, whole-heart, 3 T CE-MRCA significantly improved the sensitivity and diagnostic accuracy as compared to MPI and LGE alone for CAD detection.
NASA Technical Reports Server (NTRS)
Starc, V.; Schlegel, T. T.; Arenare, B.; Greco, E. C.; DePalma, J. L.; Nunez, T.; Medina, R.; Jugo, D.; Rahman, M. A.; Delgado, R.
2007-01-01
We investigated the ability of beat-to-beat QT interval variability (QTV) and related parameters to differentiate healthy individuals from patients with obstructive coronary artery disease (CAD) and cardiomyopathy (CM). For this purpose we developed a PC-based ECG software program that in real time, acquires, analyzes and displays QTV in each of the eight independent channels that constitute the 12-lead conventional ECG. The system also analyzes and displays the QTV from QT interval signals that are derived from multiple channels and from singular value decomposition (SVD) to substantially reduce the effect of noise and other artifacts on the QTV results. It also provides other useful SVD-related parameters such as the normalized 3-dimensional volume of the T wave (nTV) = 100*(rho(sub 2)*rho(sub 3)rho(sub 1^2). Advanced high-fidelity 12-lead ECG tests (approx. 5-min supine) were first performed on a "training set" of 99 individuals: 33 with ischemic or dilated CM and low ejection fraction (EF less than 40%); 33 with catheterization-proven obstructive CAD but normal EF; and 33 age-/gender-matched healthy controls. All QTV parameters that were studied for their accuracy in detecting CM and CAD significantly differentiated both CM and CAD from controls (p less than 0.0001). Retrospective areas under the ROC curve (AUC) of SDNN-QTV, rmsSD-QTV, and QTV Index (QTVI) for CM vs. controls in the lead V5 were 0.85, 0.90, and 0.99, respectively, and those for CAD vs. controls in the lead II were 0.82, 0.82, and 0.89. Other advanced ECG parameters, such as HFQRS RAZ score, LF Lomb of RRV or QRS-T angle, differentiated both CM and CAD from controls less significantly, with the respective AUC values of 0.89, 0.88 and 0.98 for CM vs. controls, and 0.73, 0.71 and 0.80 for CAD vs. controls. QTV parameters (especially QTVI, which is QTV as indexed to RRV) were, diagnostically speaking, amongst the best performing of the advanced ECG techniques studied thus far.
Misawa, Masashi; Kudo, Shin-Ei; Mori, Yuichi; Takeda, Kenichi; Maeda, Yasuharu; Kataoka, Shinichi; Nakamura, Hiroki; Kudo, Toyoki; Wakamura, Kunihiko; Hayashi, Takemasa; Katagiri, Atsushi; Baba, Toshiyuki; Ishida, Fumio; Inoue, Haruhiro; Nimura, Yukitaka; Oda, Msahiro; Mori, Kensaku
2017-05-01
Real-time characterization of colorectal lesions during colonoscopy is important for reducing medical costs, given that the need for a pathological diagnosis can be omitted if the accuracy of the diagnostic modality is sufficiently high. However, it is sometimes difficult for community-based gastroenterologists to achieve the required level of diagnostic accuracy. In this regard, we developed a computer-aided diagnosis (CAD) system based on endocytoscopy (EC) to evaluate cellular, glandular, and vessel structure atypia in vivo. The purpose of this study was to compare the diagnostic ability and efficacy of this CAD system with the performances of human expert and trainee endoscopists. We developed a CAD system based on EC with narrow-band imaging that allowed microvascular evaluation without dye (ECV-CAD). The CAD algorithm was programmed based on texture analysis and provided a two-class diagnosis of neoplastic or non-neoplastic, with probabilities. We validated the diagnostic ability of the ECV-CAD system using 173 randomly selected EC images (49 non-neoplasms, 124 neoplasms). The images were evaluated by the CAD and by four expert endoscopists and three trainees. The diagnostic accuracies for distinguishing between neoplasms and non-neoplasms were calculated. ECV-CAD had higher overall diagnostic accuracy than trainees (87.8 vs 63.4%; [Formula: see text]), but similar to experts (87.8 vs 84.2%; [Formula: see text]). With regard to high-confidence cases, the overall accuracy of ECV-CAD was also higher than trainees (93.5 vs 71.7%; [Formula: see text]) and comparable to experts (93.5 vs 90.8%; [Formula: see text]). ECV-CAD showed better diagnostic accuracy than trainee endoscopists and was comparable to that of experts. ECV-CAD could thus be a powerful decision-making tool for less-experienced endoscopists.
Ramírez, J; Górriz, J M; Segovia, F; Chaves, R; Salas-Gonzalez, D; López, M; Alvarez, I; Padilla, P
2010-03-19
This letter shows a computer aided diagnosis (CAD) technique for the early detection of the Alzheimer's disease (AD) by means of single photon emission computed tomography (SPECT) image classification. The proposed method is based on partial least squares (PLS) regression model and a random forest (RF) predictor. The challenge of the curse of dimensionality is addressed by reducing the large dimensionality of the input data by downscaling the SPECT images and extracting score features using PLS. A RF predictor then forms an ensemble of classification and regression tree (CART)-like classifiers being its output determined by a majority vote of the trees in the forest. A baseline principal component analysis (PCA) system is also developed for reference. The experimental results show that the combined PLS-RF system yields a generalization error that converges to a limit when increasing the number of trees in the forest. Thus, the generalization error is reduced when using PLS and depends on the strength of the individual trees in the forest and the correlation between them. Moreover, PLS feature extraction is found to be more effective for extracting discriminative information from the data than PCA yielding peak sensitivity, specificity and accuracy values of 100%, 92.7%, and 96.9%, respectively. Moreover, the proposed CAD system outperformed several other recently developed AD CAD systems. Copyright 2010 Elsevier Ireland Ltd. All rights reserved.
Michaelides, Andreas P; Liakos, Charalampos I; Vyssoulis, Gregory P; Chatzistamatiou, Evangelos I; Markou, Maria I; Tzamou, Vanessa; Stefanadis, Christodoulos I
2013-03-01
Delayed blood pressure (BP) and heart rate (HR) decline at recovery post-exercise are independent predictors of incident coronary artery disease (CAD). Delayed BP recovery and exaggerated BP response to exercise are independent predictors of future arterial hypertension (AH). This study sought to examine whether the combination of two exercise parameters provides additional prognostic value than each variable alone. A total of 830 non-CAD patients (374 normotensive) were followed for new-onset CAD and/or AH for 5 years after diagnostic exercise testing (ET). At the end of follow-up, patients without overt CAD underwent a second ET. Stress imaging modalities and coronary angiography, where appropriate, ruled out CAD. New-onset CAD was detected in 110 participants (13.3%) whereas AH was detected in 41 former normotensives (11.0%). The adjusted (for confounders) relative risk (RR) of CAD in abnormal BP and HR recovery patients was 1.95 (95% confidence interval [CI], 1.28-2.98; P=.011) compared with delayed BP and normal HR recovery patients and 1.71 (95% CI, 1.08-2.75; P=.014) compared with normal BP and delayed HR recovery patients. The adjusted RR of AH in normotensives with abnormal BP recovery and response was 2.18 (95% CI, 1.03-4.72; P=.047) compared with delayed BP recovery and normal BP response patients and 2.48 (95% CI, 1.14-4.97; P=.038) compared with normal BP recovery and exaggerated BP response individuals. In conclusion, the combination of two independent exercise predictors is an even stronger CAD/AH predictor than its components. © 2012 Wiley Periodicals, Inc.
NASA Astrophysics Data System (ADS)
Ahlers, Volker; Weigl, Paul; Schachtzabel, Hartmut
2005-04-01
Due to the increasing demand for high-quality ceramic crowns and bridges, the CAD/CAM-based production of dental restorations has been a subject of intensive research during the last fifteen years. A prerequisite for the efficient processing of the 3D measurement of prepared teeth with a minimal amount of user interaction is the automatic determination of the preparation line, which defines the sealing margin between the restoration and the prepared tooth. Current dental CAD/CAM systems mostly require the interactive definition of the preparation line by the user, at least by means of giving a number of start points. Previous approaches to the automatic extraction of the preparation line rely on single contour detection algorithms. In contrast, we use a combination of different contour detection algorithms to find several independent potential preparation lines from a height profile of the measured data. The different algorithms (gradient-based, contour-based, and region-based) show their strengths and weaknesses in different clinical situations. A classifier consisting of three stages (range check, decision tree, support vector machine), which is trained by human experts with real-world data, finally decides which is the correct preparation line. In a test with 101 clinical preparations, a success rate of 92.0% has been achieved. Thus the combination of different contour detection algorithms yields a reliable method for the automatic extraction of the preparation line, which enables the setup of a turn-key dental CAD/CAM process chain with a minimal amount of interactive screen work.
NASA Astrophysics Data System (ADS)
Giannini, Valentina; Vignati, Anna; Mazzetti, Simone; De Luca, Massimo; Bracco, Christian; Stasi, Michele; Russo, Filippo; Armando, Enrico; Regge, Daniele
2013-02-01
Prostate specific antigen (PSA)-based screening reduces the rate of death from prostate cancer (PCa) by 31%, but this benefit is associated with a high risk of overdiagnosis and overtreatment. As prostate transrectal ultrasound-guided biopsy, the standard procedure for prostate histological sampling, has a sensitivity of 77% with a considerable false-negative rate, more accurate methods need to be found to detect or rule out significant disease. Prostate magnetic resonance imaging has the potential to improve the specificity of PSA-based screening scenarios as a non-invasive detection tool, in particular exploiting the combination of anatomical and functional information in a multiparametric framework. The purpose of this study was to describe a computer aided diagnosis (CAD) method that automatically produces a malignancy likelihood map by combining information from dynamic contrast enhanced MR images and diffusion weighted images. The CAD system consists of multiple sequential stages, from a preliminary registration of images of different sequences, in order to correct for susceptibility deformation and/or movement artifacts, to a Bayesian classifier, which fused all the extracted features into a probability map. The promising results (AUROC=0.87) should be validated on a larger dataset, but they suggest that the discrimination on a voxel basis between benign and malignant tissues is feasible with good performances. This method can be of benefit to improve the diagnostic accuracy of the radiologist, reduce reader variability and speed up the reading time, automatically highlighting probably cancer suspicious regions.
Sailer, Irena; Benic, Goran I; Fehmer, Vincent; Hämmerle, Christoph H F; Mühlemann, Sven
2017-07-01
Clinical studies are needed to evaluate the entire digital and conventional workflows in prosthetic dentistry. The purpose of the second part of this clinical study was to compare the laboratory production time for tooth-supported single crowns made with 4 different digital workflows and 1 conventional workflow and to compare these crowns clinically. For each of 10 participants, a monolithic crown was fabricated in lithium disilicate-reinforced glass ceramic (IPS e.max CAD). The computer-aided design and computer-aided manufacturing (CAD-CAM) systems were Lava C.O.S. CAD software and centralized CAM (group L), Cares CAD software and centralized CAM (group iT), Cerec Connect CAD software and lab side CAM (group CiL), and Cerec Connect CAD software with centralized CAM (group CiD). The conventional fabrication (group K) included a wax pattern of the crown and heat pressing according to the lost-wax technique (IPS e.max Press). The time for the fabrication of the casts and the crowns was recorded. Subsequently, the crowns were clinically evaluated and the corresponding treatment times were recorded. The Paired Wilcoxon test with the Bonferroni correction was applied to detect differences among treatment groups (α=.05). The total mean (±standard deviation) active working time for the dental technician was 88 ±6 minutes in group L, 74 ±12 minutes in group iT, 74 ±5 minutes in group CiL, 92 ±8 minutes in group CiD, and 148 ±11 minutes in group K. The dental technician spent significantly more working time for the conventional workflow than for the digital workflows (P<.001). No statistically significant differences were found between group L and group CiD or between group iT and group CiL. No statistical differences in time for the clinical evaluation were found among groups, indicating similar outcomes (P>.05). Irrespective of the CAD-CAM system, the overall laboratory working time for a digital workflow was significantly shorter than for the conventional workflow, since the dental technician needed less active working time. Copyright © 2016 Editorial Council for the Journal of Prosthetic Dentistry. Published by Elsevier Inc. All rights reserved.
A review of intelligent systems for heart sound signal analysis.
Nabih-Ali, Mohammed; El-Dahshan, El-Sayed A; Yahia, Ashraf S
2017-10-01
Intelligent computer-aided diagnosis (CAD) systems can enhance the diagnostic capabilities of physicians and reduce the time required for accurate diagnosis. CAD systems could provide physicians with a suggestion about the diagnostic of heart diseases. The objective of this paper is to review the recent published preprocessing, feature extraction and classification techniques and their state of the art of phonocardiogram (PCG) signal analysis. Published literature reviewed in this paper shows the potential of machine learning techniques as a design tool in PCG CAD systems and reveals that the CAD systems for PCG signal analysis are still an open problem. Related studies are compared to their datasets, feature extraction techniques and the classifiers they used. Current achievements and limitations in developing CAD systems for PCG signal analysis using machine learning techniques are presented and discussed. In the light of this review, a number of future research directions for PCG signal analysis are provided.
NASA Astrophysics Data System (ADS)
Sánchez, Clara I.; Niemeijer, Meindert; Kockelkorn, Thessa; Abràmoff, Michael D.; van Ginneken, Bram
2009-02-01
Computer-aided Diagnosis (CAD) systems for the automatic identification of abnormalities in retinal images are gaining importance in diabetic retinopathy screening programs. A huge amount of retinal images are collected during these programs and they provide a starting point for the design of machine learning algorithms. However, manual annotations of retinal images are scarce and expensive to obtain. This paper proposes a dynamic CAD system based on active learning for the automatic identification of hard exudates, cotton wool spots and drusen in retinal images. An uncertainty sampling method is applied to select samples that need to be labeled by an expert from an unlabeled set of 4000 retinal images. It reduces the number of training samples needed to obtain an optimum accuracy by dynamically selecting the most informative samples. Results show that the proposed method increases the classification accuracy compared to alternative techniques, achieving an area under the ROC curve of 0.87, 0.82 and 0.78 for the detection of hard exudates, cotton wool spots and drusen, respectively.
Histology image analysis for carcinoma detection and grading
He, Lei; Long, L. Rodney; Antani, Sameer; Thoma, George R.
2012-01-01
This paper presents an overview of the image analysis techniques in the domain of histopathology, specifically, for the objective of automated carcinoma detection and classification. As in other biomedical imaging areas such as radiology, many computer assisted diagnosis (CAD) systems have been implemented to aid histopathologists and clinicians in cancer diagnosis and research, which have been attempted to significantly reduce the labor and subjectivity of traditional manual intervention with histology images. The task of automated histology image analysis is usually not simple due to the unique characteristics of histology imaging, including the variability in image preparation techniques, clinical interpretation protocols, and the complex structures and very large size of the images themselves. In this paper we discuss those characteristics, provide relevant background information about slide preparation and interpretation, and review the application of digital image processing techniques to the field of histology image analysis. In particular, emphasis is given to state-of-the-art image segmentation methods for feature extraction and disease classification. Four major carcinomas of cervix, prostate, breast, and lung are selected to illustrate the functions and capabilities of existing CAD systems. PMID:22436890
Computer-aided diagnosis of breast microcalcifications based on dual-tree complex wavelet transform.
Jian, Wushuai; Sun, Xueyan; Luo, Shuqian
2012-12-19
Digital mammography is the most reliable imaging modality for breast carcinoma diagnosis and breast micro-calcifications is regarded as one of the most important signs on imaging diagnosis. In this paper, a computer-aided diagnosis (CAD) system is presented for breast micro-calcifications based on dual-tree complex wavelet transform (DT-CWT) to facilitate radiologists like double reading. Firstly, 25 abnormal ROIs were extracted according to the center and diameter of the lesions manually and 25 normal ROIs were selected randomly. Then micro-calcifications were segmented by combining space and frequency domain techniques. We extracted three texture features based on wavelet (Haar, DB4, DT-CWT) transform. Totally 14 descriptors were introduced to define the characteristics of the suspicious micro-calcifications. Principal Component Analysis (PCA) was used to transform these descriptors to a compact and efficient vector expression. Support Vector Machine (SVM) classifier was used to classify potential micro-calcifications. Finally, we used the receiver operating characteristic (ROC) curve and free-response operating characteristic (FROC) curve to evaluate the performance of the CAD system. The results of SVM classifications based on different wavelets shows DT-CWT has a better performance. Compared with other results, DT-CWT method achieved an accuracy of 96% and 100% for the classification of normal and abnormal ROIs, and the classification of benign and malignant micro-calcifications respectively. In FROC analysis, our CAD system for clinical dataset detection achieved a sensitivity of 83.5% at a false positive per image of 1.85. Compared with general wavelets, DT-CWT could describe the features more effectively, and our CAD system had a competitive performance.
Computer-aided diagnosis of breast microcalcifications based on dual-tree complex wavelet transform
2012-01-01
Background Digital mammography is the most reliable imaging modality for breast carcinoma diagnosis and breast micro-calcifications is regarded as one of the most important signs on imaging diagnosis. In this paper, a computer-aided diagnosis (CAD) system is presented for breast micro-calcifications based on dual-tree complex wavelet transform (DT-CWT) to facilitate radiologists like double reading. Methods Firstly, 25 abnormal ROIs were extracted according to the center and diameter of the lesions manually and 25 normal ROIs were selected randomly. Then micro-calcifications were segmented by combining space and frequency domain techniques. We extracted three texture features based on wavelet (Haar, DB4, DT-CWT) transform. Totally 14 descriptors were introduced to define the characteristics of the suspicious micro-calcifications. Principal Component Analysis (PCA) was used to transform these descriptors to a compact and efficient vector expression. Support Vector Machine (SVM) classifier was used to classify potential micro-calcifications. Finally, we used the receiver operating characteristic (ROC) curve and free-response operating characteristic (FROC) curve to evaluate the performance of the CAD system. Results The results of SVM classifications based on different wavelets shows DT-CWT has a better performance. Compared with other results, DT-CWT method achieved an accuracy of 96% and 100% for the classification of normal and abnormal ROIs, and the classification of benign and malignant micro-calcifications respectively. In FROC analysis, our CAD system for clinical dataset detection achieved a sensitivity of 83.5% at a false positive per image of 1.85. Conclusions Compared with general wavelets, DT-CWT could describe the features more effectively, and our CAD system had a competitive performance. PMID:23253202
Tam, James; Ahmad, Imad A Haidar; Blasko, Andrei
2018-06-05
A four parameter optimization of a stability indicating method for non-chromophoric degradation products of 1,2-distearoyl-sn-glycero-3-phosphocholine (DSPC), 1-stearoyl-sn-glycero-3-phosphocholine and 2-stearoyl-sn-glycero-3-phosphocholine was achieved using a reverse phase liquid chromatography-charged aerosol detection (RPLC-CAD) technique. Using the hydrophobic subtraction model of selectivity, a core-shell, polar embedded RPLC column was selected followed by gradient-temperature optimization, resulting in ideal relative peak placements for a robust, stability indicating separation. The CAD instrument parameters, power function value (PFV) and evaporator temperature were optimized for lysophosphatidylcholines to give UV absorbance detector-like linearity performance within a defined concentration range. The two lysophosphatidylcholines gave the same response factor in the selected conditions. System specific power function values needed to be set for the two RPLC-CAD instruments used. A custom flow-divert profile, sending only a portion of the column effluent to the detector, was necessary to mitigate detector response drifting effects. The importance of the PFV optimization for each instrument of identical build and how to overcome recovery issues brought on by the matrix effects from the lipid-RP stationary phase interaction is reported. Copyright © 2018 Elsevier B.V. All rights reserved.
Mass classification in mammography with multi-agent based fusion of human and machine intelligence
NASA Astrophysics Data System (ADS)
Xi, Dongdong; Fan, Ming; Li, Lihua; Zhang, Juan; Shan, Yanna; Dai, Gang; Zheng, Bin
2016-03-01
Although the computer-aided diagnosis (CAD) system can be applied for classifying the breast masses, the effects of this method on improvement of the radiologist' accuracy for distinguishing malignant from benign lesions still remain unclear. This study provided a novel method to classify breast masses by integrating the intelligence of human and machine. In this research, 224 breast masses were selected in mammography from database of DDSM with Breast Imaging Reporting and Data System (BI-RADS) categories. Three observers (a senior and a junior radiologist, as well as a radiology resident) were employed to independently read and classify these masses utilizing the Positive Predictive Values (PPV) for each BI-RADS category. Meanwhile, a CAD system was also implemented for classification of these breast masses between malignant and benign. To combine the decisions from the radiologists and CAD, the fusion method of the Multi-Agent was provided. Significant improvements are observed for the fusion system over solely radiologist or CAD. The area under the receiver operating characteristic curve (AUC) of the fusion system increased by 9.6%, 10.3% and 21% compared to that of radiologists with senior, junior and resident level, respectively. In addition, the AUC of this method based on the fusion of each radiologist and CAD are 3.5%, 3.6% and 3.3% higher than that of CAD alone. Finally, the fusion of the three radiologists with CAD achieved AUC value of 0.957, which was 5.6% larger compared to CAD. Our results indicated that the proposed fusion method has better performance than radiologist or CAD alone.
An open access thyroid ultrasound image database
NASA Astrophysics Data System (ADS)
Pedraza, Lina; Vargas, Carlos; Narváez, Fabián.; Durán, Oscar; Muñoz, Emma; Romero, Eduardo
2015-01-01
Computer aided diagnosis systems (CAD) have been developed to assist radiologists in the detection and diagnosis of abnormalities and a large number of pattern recognition techniques have been proposed to obtain a second opinion. Most of these strategies have been evaluated using different datasets making their performance incomparable. In this work, an open access database of thyroid ultrasound images is presented. The dataset consists of a set of B-mode Ultrasound images, including a complete annotation and diagnostic description of suspicious thyroid lesions by expert radiologists. Several types of lesions as thyroiditis, cystic nodules, adenomas and thyroid cancers were included while an accurate lesion delineation is provided in XML format. The diagnostic description of malignant lesions was confirmed by biopsy. The proposed new database is expected to be a resource for the community to assess different CAD systems.
Korosoglou, Grigorios; Lossnitzer, Dirk; Schellberg, Dieter; Lewien, Antje; Wochele, Angela; Schaeufele, Tim; Neizel, Mirja; Steen, Henning; Giannitsis, Evangelos; Katus, Hugo A.; Osman, Nael F.
2009-01-01
Background High-dose dobutamine stress magnetic resonance imaging (DS-MRI) is safe and feasible for the diagnosis of coronary artery disease (CAD) in humans. However, the assessment of cine scans relies on the visual interpretation of regional wall motion, which is subjective. Recently, Strain-Encoded MRI (SENC) has been proposed for the direct color-coded visualization of myocardial strain. The purpose of our study was to compare the diagnostic value of SENC to that provided by conventional wall motion analysis for the detection of inducible ischemia during DS-MRI. Methods and Results Stress induced ischemia was assessed by wall motion analysis and by SENC in 101 patients with suspected or known CAD and in 17 healthy volunteers who underwent DS-MRI in a clinical 1.5T scanner. Quantitative coronary angiography deemed as the standard reference for the presence or absence of significant CAD (≥50% diameter stenosis). On a coronary vessel level, SENC detected inducible ischemia in 86/101 versus 71/101 diseased coronary vessels (p<0.01 versus cine), and showed normal strain response in 189/202 versus 194/202 vessels with <50% stenosis (p=NS versus cine). On a patient level, SENC detected inducible ischemia in 63/64 versus 55/64 patients with CAD (p<0.05 versus cine), and showed normal strain response in 32/37 versus 34/37 patients without CAD (p=NS versus cine).Quantification analysis demonstrated a significant correlation between strain rate reserve (SRreserve) and coronary artery stenosis severity (r²=0.56, p<0.001), and a cut-off value of SRreserve=1.64 deemed as a highly accurate marker for the detection of stenosis≥50% (AUC=0.96, SE=0.01, 95% CI = 0.94–0.98, p<0.001). Conclusions The direct color-coded visualization of strain on MR-images is a useful adjunct for DS-MRI, which provides incremental value for the detection of CAD compared to conventional wall motion readings on cine images. PMID:19808579
Korosoglou, Grigorios; Lossnitzer, Dirk; Schellberg, Dieter; Lewien, Antje; Wochele, Angela; Schaeufele, Tim; Neizel, Mirja; Steen, Henning; Giannitsis, Evangelos; Katus, Hugo A; Osman, Nael F
2009-03-01
High-dose dobutamine stress MRI is safe and feasible for the diagnosis of coronary artery disease (CAD) in humans. However, the assessment of cine scans relies on the visual interpretation of regional wall motion, which is subjective. Recently, strain-encoded MRI (SENC) has been proposed for the direct color-coded visualization of myocardial strain. The purpose of our study was to compare the diagnostic value of SENC with that provided by conventional wall motion analysis for the detection of inducible ischemia during dobutamine stress MRI. Stress-induced ischemia was assessed by wall motion analysis and by SENC in 101 patients with suspected or known CAD and in 17 healthy volunteers who underwent dobutamine stress MRI in a clinical 1.5-T scanner. Quantitative coronary angiography deemed as the standard reference for the presence or absence of significant CAD (> or =50% diameter stenosis). On a coronary vessel level, SENC detected inducible ischemia in 86 of 101 versus 71 of 101 diseased coronary vessels (P<0.01 versus cine) and showed normal strain response in 189 of 202 versus 194 of 202 vessels with <50% stenosis (P=NS versus cine). On a patient level, SENC detected inducible ischemia in 63 of 64 versus 55 of 64 patients with CAD (P<0.05 versus cine) and showed normal strain response in 32 of 37 versus 34 of 37 patients without CAD (P=NS versus cine). Quantification analysis demonstrated a significant correlation between strain rate reserve and coronary artery stenosis severity (r(2)=0.56, P<0.001), and a cutoff value of strain rate reserve of 1.64 was deemed as a highly accurate marker for the detection of > or =50% stenosis (area under the curve, 0.96; SE, 0.01; 95% CI, 0.94 to 0.98; P<0.001). The direct color-coded visualization of strain on MR images is a useful adjunct for dobutamine stress MRI, which provides incremental value for the detection of CAD compared with conventional wall motion readings on cine images.
2012-01-01
Background Exercise electrocardiography (ECG) is frequently used in the work-up of patients with suspected coronary artery disease (CAD), however the accuracy is reduced in women. Cardiovascular magnetic resonance (CMR) stress testing can accurately diagnose CAD in women. To date, a direct comparison of CMR to ECG has not been performed. Methods and results We prospectively enrolled 88 consecutive women with chest pain or other symptoms suggestive of CAD. Patients underwent a comprehensive clinical evaluation, exercise ECG, a CMR stress test including perfusion and infarct imaging, and x-ray coronary angiography (CA) within 24 hours. CAD was defined as stenosis ≥70% on quantitative analysis of CA. Exercise ECG, CMR and CA was completed in 68 females (age 66.4 ± 8.8 years, number of CAD risk factors 3.5 ± 1.4). The prevalence of CAD on CA was 29%. The Duke treadmill score (DTS) in the entire group was −3.0 ± 5.4 and was similar in those with and without CAD (−4.5 ± 5.8 and −2.4 ± 5.1; P = 0.12). Sensitivity, specificity and accuracy for CAD diagnosis was higher for CMR compared with exercise ECG (sensitivities 85% and 50%, P = 0.02, specificities 94% and 73%, P = 0.01, and accuracies 91% and 66%, P = 0.0007, respectively). Even after applying the DTS the accuracy of CMR was higher compared to exercise ECG (area under ROC curve 0.94 ± 0.03 vs 0.56 ± 0.07; P = 0.0001). Conclusions In women with intermediate-to-high risk for CAD who are able to exercise and have interpretable resting ECG, CMR stress perfusion imaging has higher accuracy for the detection of relevant obstruction of the epicardial coronaries when directly compared to exercise ECG. PMID:22697372
A new semiquantitative method for evaluation of metastasis progression.
Volarevic, A; Ljujic, B; Volarevic, V; Milovanovic, M; Kanjevac, T; Lukic, A; Arsenijevic, N
2012-01-01
Although recent technical advancements are directed toward developing novel assays and methods for detection of micro and macro metastasis, there are still no reports of reliable, simple to use imaging software that could be used for the detection and quantification of metastasis in tissue sections. We herein report a new semiquantitative method for evaluation of metastasis progression in a well established 4T1 orthotopic mouse model of breast cancer metastasis. The new semiquantitative method presented here was implemented by using the Autodesk AutoCAD 2012 program, a computer-aided design program used primarily for preparing technical drawings in 2 dimensions. By using the Autodesk AutoCAD 2012 software- aided graphical evaluation we managed to detect each metastatic lesion and we precisely calculated the average percentage of lung and liver tissue parenchyma with metastasis in 4T1 tumor-bearing mice. The data were highly specific and relevant to descriptive histological analysis, confirming reliability and accuracy of the AutoCAD 2012 software as new method for quantification of metastatic lesions. The new semiquantitative method using AutoCAD 2012 software provides a novel approach for the estimation of metastatic progression in histological tissue sections.
Spatial data software integration - Merging CAD/CAM/mapping with GIS and image processing
NASA Technical Reports Server (NTRS)
Logan, Thomas L.; Bryant, Nevin A.
1987-01-01
The integration of CAD/CAM/mapping with image processing using geographic information systems (GISs) as the interface is examined. Particular emphasis is given to the development of software interfaces between JPL's Video Image Communication and Retrieval (VICAR)/Imaged Based Information System (IBIS) raster-based GIS and the CAD/CAM/mapping system. The design and functions of the VICAR and IBIS are described. Vector data capture and editing are studied. Various software programs for interfacing between the VICAR/IBIS and CAD/CAM/mapping are presented and analyzed.
Computer-aided diagnosis: A survey with bibliometric analysis.
Takahashi, Ryohei; Kajikawa, Yuya
2017-05-01
Computer-aided diagnosis (CAD) has been a promising area of research over the last two decades. However, CAD is a very complicated subject because it involves a number of medicine and engineering-related fields. To develop a research overview of CAD, we conducted a literature survey with bibliometric analysis, which we report here. Our study determined that CAD research has been classified and categorized according to disease type and imaging modality. This classification began with the CAD of mammograms and eventually progressed to that of brain disease. Furthermore, based on our results, we discuss future directions and opportunities for CAD research. First, in contrast to the typical hypothetical approach, the data-driven approach has shown promise. Second, the normalization of the test datasets and an evaluation method is necessary when adopting an algorithm and a system. Third, we discuss opportunities for the co-evolution of CAD research and imaging instruments-for example, the CAD of bones and pancreatic cancer. Fourth, the potential of synergy with CAD and clinical decision support systems is also discussed. Copyright © 2017 Elsevier B.V. All rights reserved.
Computer-aided diagnosis and artificial intelligence in clinical imaging.
Shiraishi, Junji; Li, Qiang; Appelbaum, Daniel; Doi, Kunio
2011-11-01
Computer-aided diagnosis (CAD) is rapidly entering the radiology mainstream. It has already become a part of the routine clinical work for the detection of breast cancer with mammograms. The computer output is used as a "second opinion" in assisting radiologists' image interpretations. The computer algorithm generally consists of several steps that may include image processing, image feature analysis, and data classification via the use of tools such as artificial neural networks (ANN). In this article, we will explore these and other current processes that have come to be referred to as "artificial intelligence." One element of CAD, temporal subtraction, has been applied for enhancing interval changes and for suppressing unchanged structures (eg, normal structures) between 2 successive radiologic images. To reduce misregistration artifacts on the temporal subtraction images, a nonlinear image warping technique for matching the previous image to the current one has been developed. Development of the temporal subtraction method originated with chest radiographs, with the method subsequently being applied to chest computed tomography (CT) and nuclear medicine bone scans. The usefulness of the temporal subtraction method for bone scans was demonstrated by an observer study in which reading times and diagnostic accuracy improved significantly. An additional prospective clinical study verified that the temporal subtraction image could be used as a "second opinion" by radiologists with negligible detrimental effects. ANN was first used in 1990 for computerized differential diagnosis of interstitial lung diseases in CAD. Since then, ANN has been widely used in CAD schemes for the detection and diagnosis of various diseases in different imaging modalities, including the differential diagnosis of lung nodules and interstitial lung diseases in chest radiography, CT, and position emission tomography/CT. It is likely that CAD will be integrated into picture archiving and communication systems and will become a standard of care for diagnostic examinations in daily clinical work. Copyright © 2011 Elsevier Inc. All rights reserved.
TGeoCad: an Interface between ROOT and CAD Systems
NASA Astrophysics Data System (ADS)
Luzzi, C.; Carminati, F.
2014-06-01
In the simulation of High Energy Physics experiment a very high precision in the description of the detector geometry is essential to achieve the required performances. The physicists in charge of Monte Carlo Simulation of the detector need to collaborate efficiently with the engineers working at the mechanical design of the detector. Often, this collaboration is made hard by the usage of different and incompatible software. ROOT is an object-oriented C++ framework used by physicists for storing, analyzing and simulating data produced by the high-energy physics experiments while CAD (Computer-Aided Design) software is used for mechanical design in the engineering field. The necessity to improve the level of communication between physicists and engineers led to the implementation of an interface between the ROOT geometrical modeler used by the virtual Monte Carlo simulation software and the CAD systems. In this paper we describe the design and implementation of the TGeoCad Interface that has been developed to enable the use of ROOT geometrical models in several CAD systems. To achieve this goal, the ROOT geometry description is converted into STEP file format (ISO 10303), which can be imported and used by many CAD systems.
Computer aided detection of brain micro-bleeds in traumatic brain injury
NASA Astrophysics Data System (ADS)
van den Heuvel, T. L. A.; Ghafoorian, M.; van der Eerden, A. W.; Goraj, B. M.; Andriessen, T. M. J. C.; ter Haar Romeny, B. M.; Platel, B.
2015-03-01
Brain micro-bleeds (BMBs) are used as surrogate markers for detecting diffuse axonal injury in traumatic brain injury (TBI) patients. The location and number of BMBs have been shown to influence the long-term outcome of TBI. To further study the importance of BMBs for prognosis, accurate localization and quantification are required. The task of annotating BMBs is laborious, complex and prone to error, resulting in a high inter- and intra-reader variability. In this paper we propose a computer-aided detection (CAD) system to automatically detect BMBs in MRI scans of moderate to severe neuro-trauma patients. Our method consists of four steps. Step one: preprocessing of the data. Both susceptibility (SWI) and T1 weighted MRI scans are used. The images are co-registered, a brain-mask is generated, the bias field is corrected, and the image intensities are normalized. Step two: initial candidates for BMBs are selected as local minima in the processed SWI scans. Step three: feature extraction. BMBs appear as round or ovoid signal hypo-intensities on SWI. Twelve features are computed to capture these properties of a BMB. Step four: Classification. To identify BMBs from the set of local minima using their features, different classifiers are trained on a database of 33 expert annotated scans and 18 healthy subjects with no BMBs. Our system uses a leave-one-out strategy to analyze its performance. With a sensitivity of 90% and 1.3 false positives per BMB, our CAD system shows superior results compared to state-of-the-art BMB detection algorithms (developed for non-trauma patients).
The genetic basis for survivorship in coronary artery disease
Dungan, Jennifer R.; Hauser, Elizabeth R.; Qin, Xuejun; Kraus, William E.
2013-01-01
Survivorship is a trait characterized by endurance and virility in the face of hardship. It is largely considered a psychosocial attribute developed during fatal conditions, rather than a biological trait for robustness in the context of complex, age-dependent diseases like coronary artery disease (CAD). The purpose of this paper is to present the novel phenotype, survivorship in CAD as an observed survival advantage concurrent with clinically significant CAD. We present a model for characterizing survivorship in CAD and its relationships with overlapping time- and clinically-related phenotypes. We offer an optimal measurement interval for investigating survivorship in CAD. We hypothesize genetic contributions to this construct and review the literature for evidence of genetic contribution to overlapping phenotypes in support of our hypothesis. We also present preliminary evidence of genetic effects on survival in people with clinically significant CAD from a primary case-control study of symptomatic coronary disease. Identifying gene variants that confer improved survival in the context of clinically appreciable CAD may improve our understanding of cardioprotective mechanisms acting at the gene level and potentially impact patients clinically in the future. Further, characterizing other survival-variant genetic effects may improve signal-to-noise ratio in detecting gene associations for CAD. PMID:24143143
NASA Astrophysics Data System (ADS)
Lartizien, Carole; Marache-Francisco, Simon; Prost, Rémy
2012-02-01
Positron emission tomography (PET) using fluorine-18 deoxyglucose (18F-FDG) has become an increasingly recommended tool in clinical whole-body oncology imaging for the detection, diagnosis, and follow-up of many cancers. One way to improve the diagnostic utility of PET oncology imaging is to assist physicians facing difficult cases of residual or low-contrast lesions. This study aimed at evaluating different schemes of computer-aided detection (CADe) systems for the guided detection and localization of small and low-contrast lesions in PET. These systems are based on two supervised classifiers, linear discriminant analysis (LDA) and the nonlinear support vector machine (SVM). The image feature sets that serve as input data consisted of the coefficients of an undecimated wavelet transform. An optimization study was conducted to select the best combination of parameters for both the SVM and the LDA. Different false-positive reduction (FPR) methods were evaluated to reduce the number of false-positive detections per image (FPI). This includes the removal of small detected clusters and the combination of the LDA and SVM detection maps. The different CAD schemes were trained and evaluated based on a simulated whole-body PET image database containing 250 abnormal cases with 1230 lesions and 250 normal cases with no lesion. The detection performance was measured on a separate series of 25 testing images with 131 lesions. The combination of the LDA and SVM score maps was shown to produce very encouraging detection performance for both the lung lesions, with 91% sensitivity and 18 FPIs, and the liver lesions, with 94% sensitivity and 10 FPIs. Comparison with human performance indicated that the different CAD schemes significantly outperformed human detection sensitivities, especially regarding the low-contrast lesions.
Integrating CAD modules in a PACS environment using a wide computing infrastructure.
Suárez-Cuenca, Jorge J; Tilve, Amara; López, Ricardo; Ferro, Gonzalo; Quiles, Javier; Souto, Miguel
2017-04-01
The aim of this paper is to describe a project designed to achieve a total integration of different CAD algorithms into the PACS environment by using a wide computing infrastructure. The aim is to build a system for the entire region of Galicia, Spain, to make CAD accessible to multiple hospitals by employing different PACSs and clinical workstations. The new CAD model seeks to connect different devices (CAD systems, acquisition modalities, workstations and PACS) by means of networking based on a platform that will offer different CAD services. This paper describes some aspects related to the health services of the region where the project was developed, CAD algorithms that were either employed or selected for inclusion in the project, and several technical aspects and results. We have built a standard-based platform with which users can request a CAD service and receive the results in their local PACS. The process runs through a web interface that allows sending data to the different CAD services. A DICOM SR object is received with the results of the algorithms stored inside the original study in the proper folder with the original images. As a result, a homogeneous service to the different hospitals of the region will be offered. End users will benefit from a homogeneous workflow and a standardised integration model to request and obtain results from CAD systems in any modality, not dependant on commercial integration models. This new solution will foster the deployment of these technologies in the entire region of Galicia.
Pursnani, Amit; Mayrhofer, Thomas; Ferencik, Maros; Hoffmann, Udo
2014-11-01
The recently released 2013 ACC/AHA guidelines for management of blood cholesterol have substantially increased the number of adults who are eligible for preventive statin therapy. We sought to determine whether eligibility for statin therapy as determined by the 2013 ACC/AHA guideline recommendation is better aligned with the actual presence of coronary artery disease (CAD) as detected by coronary CT angiography (CCTA) when compared to prior guidelines including the 2004 NCEP ATP III and 2011 ESC/EAS guidelines. In this secondary analysis of the prospective observational ROMICAT I (Rule Out Myocardial Infarction with Computer Assisted Tomography) cohort study, we included all men and women aged 40-79 years presenting with acute chest pain but not diagnosed with acute coronary syndrome nor on admission statin. Based on risk factor assessment and lipid data, we determined guideline-based eligibility for statin therapy by the 2013 ACC/AHA, the 2004 NCEP ATP III, and the 2011 ESC/EAS guidelines. We determined the presence and severity of CAD as detected by CCTA. The 2013 ACC/AHA algorithm identified nearly twice as many individuals as eligible for statins (n = 77/189; 41%) as compared to the 2004 ATP III criteria: (n = 41/189; 22%), (p < .0001) In addition, the 2013 ACC/AHA guidelines were more sensitive for treatment of CCTA-detected CAD than the 2004 ATP III guidelines [53.4% (42.5-64.1) vs 27.3% (18.3-37.8), p < .001] and the 2011 ESC/EAE guidelines [53.4% (42.5-64.1) vs 34.1% (24.3-45.0), p < .001]. However, the specificity of these guidelines was modestly reduced compared to the 2004 ATP III guidelines [70.3 (60.4-79.0) vs 83.2 (74.4-89.9), p < .001] and the 2011 ESC/EAE guidelines [70.3 (60.4-79.0) vs 86.1 (77.8-92.2), p < .001], suggesting increased treatment of subjects without CCTA-detected CAD. Overall, the 2013 ACC/AHA guidelines are more sensitive to identify patients who have CAD detected by CCTA eligible for statin therapy as compared with prior guidelines, with an acceptable trade-off in specificity for recommending statin therapy in those without CAD. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.
Pursnani, Amit; Mayrhofer, Thomas; Ferencik, Maros; Hoffmann, Udo
2018-01-01
The recently released 2013 ACC/AHA guidelines for management of blood cholesterol have substantially increased the number of adults who are eligible for preventive statin therapy. We sought to determine whether eligibility for statin therapy as determined by the 2013 ACC/AHA guideline recommendation is better aligned with the actual presence of coronary artery disease (CAD) as detected by coronary CT angiography (CCTA) when compared to prior guidelines including the 2004 NCEP ATP III and 2011 ESC/EAS guidelines. In this secondary analysis of the prospective observational ROMICAT I (Rule Out Myocardial Infarction with Computer Assisted Tomography) cohort study, we included all men and women aged 40–79 years presenting with acute chest pain but not diagnosed with acute coronary syndrome nor on admission statin. Based on risk factor assessment and lipid data, we determined guideline-based eligibility for statin therapy by the 2013 ACC/AHA, the 2004 NCEP ATP II, and the 2011 ESC/EAS guidelines. We determined the presence and severity of CAD as detected by CCTA. The 2013 ACC/AHA algorithm identified nearly twice as many individuals as eligible for statins (n=77/189; 41%) as compared to the 2004 ATPIII criteria: (n=41/189; 22%), (P<.0001) In addition, the 2013 ACC/AHA guidelines were more sensitive for treatment of CCTA-detected CAD than the 2004 ATP III guidelines [53.4% (42.5–64.1) vs 27.3% (18.3–37.8), p<.001] and the 2011 ESC/EAE guidelines [53.4% (42.5–64.1) vs 34.1% (24.3–45.0), p<.001]. However, the specificity of these guidelines was modestly reduced compared to the 2004 ATP III guidelines [70.3 (60.4–79.0) vs 83.2 (74.4–89.9), p<.001] and the 2011 ESC/EAE guidelines [70.3 (60.4–79.0) vs 86.1 (77.8–92.2), p<.001], suggesting increased treatment of subjects without CCTA-detected CAD. Overall, the 2013 ACC/AHA guidelines are more sensitive to identify patients who have CAD detected by CCTA eligible for statin therapy as compared with prior guidelines, with an acceptable trade-off in specificity for recommending statin therapy in those without CAD. PMID:25299966
Chino, A; Yamamoto, N; Kato, Y; Morishige, K; Ishikawa, H; Kishihara, T; Fujisaki, J; Ishikawa, Y; Tamegai, Y; Igarashi, M
2016-02-01
Sessile serrated adenoma/polyps (SSAPs) are suspected to have a high malignant potential, although few reports have evaluated the incidence of carcinomas derived from SSAPs using the new classification for serrated polyps (SPs). The aim of study was to compare the frequency of cancer coexisting with the various SP subtypes including mixed polyps (MIXs) and conventional adenomas (CADs). A total of 18,667 CADs were identified between April 2005 and December 2011, and 1858 SPs (re-classified as SSAP, hyperplastic polyp (HP), traditional serrated adenoma (TSA), or MIX) were removed via snare polypectomy, endoscopic mucosal resection, or endoscopic sub-mucosal dissection. Among 1160 HP lesions, 1 (0.1%) coexisting sub-mucosal invasive carcinoma (T1) was detected. Among 430 SSAP lesions, 3 (0.7%) high-grade dysplasia (HGD/Tis) and 1 (0.2%) T1 were detected. All of the lesions were detected in the proximal colon, with a mean tumor diameter of 18 mm (SD 9 mm). Among 212 TSA lesions, 3 (1%) HGD/Tis were detected but no T1 cancer. Among 56 MIX lesions, 9 (16%) HGD/Tis and 1 (2%) T1 cancers were detected, and among 18,677 CAD lesions, 964 (5%) HGD/Tis and 166 (1%) T1 cancers were identified. Among the resected lesions that were detected during endoscopic examination, a smaller proportion (1%) of SSAPs harbored HGD or coexisting cancer, compared to CAD or MIX lesions. Therefore, more attention should be paid to accurately identifying lesions endoscopically for intentional resection and the surveillance of each SP subtype.
NASA Astrophysics Data System (ADS)
Qiu, Yuchen; Lu, Xianglan; Tan, Maxine; Li, Shibo; Liu, Hong; Zheng, Bin
2015-03-01
The purpose of this study is to investigate the feasibility of applying automatic interphase FISH cells analysis method for detecting the residual malignancy of post chemotherapy leukemia patients. In the experiment, two clinical specimens with translocation between chromosome No. 9 and 22 or No. 11 and 14 were selected from the patients underwent leukemia diagnosis and treatment. The entire slide of each specimen was first digitalized by a commercial fluorescent microscope using a 40× objective lens. Then, the scanned images were processed by a computer-aided detecting (CAD) scheme to identify the analyzable FISH cells, which is accomplished by applying a series of features including the region size, Brenner gradient and maximum intensity. For each identified cell, the scheme detected and counted the number of the FISH signal dots inside the nucleus, using the adaptive threshold of the region size and distance of the labeled FISH dots. The results showed that the new CAD scheme detected 8093 and 6675 suspicious regions of interest (ROI) in two specimens, among which 4546 and 3807 ROI contain analyzable interphase FISH cell. In these analyzable ROIs, CAD selected 334 and 405 residual malignant cancer cells, which is substantially more than those visually detected in a cytogenetic laboratory of our medical center (334 vs. 122, 405 vs. 160). This investigation indicates that an automatic interphase FISH cell scanning and CAD method has the potential to improve the accuracy and efficiency of the prognostic assessment for leukemia and other genetic related cancer patients in the future.
NASA Astrophysics Data System (ADS)
Emaminejad, Nastaran; Lo, Pechin; Ghahremani, Shahnaz; Kim, Grace H.; Brown, Matthew S.; McNitt-Gray, Michael F.
2017-03-01
For pediatric oncology patients, CT scans are performed to assess treatment response and disease progression. CAD may be used to detect lung nodules which would reflect metastatic disease. The purpose of this study was to investigate the effects of reducing radiation dose and varying slice thickness on CAD performance in the detection of solid lung nodules in pediatric patients. The dataset consisted of CT scans of 58 pediatric chest cases, from which 7 cases had lung nodules detected by radiologist, and a total of 28 nodules were marked. For each case, the original raw data (sinogram data) was collected and a noise addition model was used to simulate reduced-dose scans of 50%, 25% and 10% of the original dose. In addition, the original and reduced-dose raw data were reconstructed at slice thicknesses of 1.5 and 3 mm using a medium sharp (B45) kernel; the result was eight datasets (4 dose levels x 2 thicknesses) for each case An in-house CAD tool was applied on all reconstructed scans, and results were compared with the radiologist's markings. Patient level mean sensitivities at 3mm thickness were 24%, 26%, 25%, 27%, and at 1.5 mm thickness were 23%, 29%, 35%, 36% for 10%, 25%, 50%, and 100% dose level, respectively. Mean FP numbers were 1.5, 0.9, 0.8, 0.7 at 3 mm and 11.4, 3.5, 2.8, 2.8 at 1.5 mm thickness for 10%, 25%, 50%, and 100% dose level respectively. CAD sensitivity did not change with dose level for 3mm thickness, but did change with dose for 1.5 mm. False Positives increased at low dose levels where noise values were high.
Assessing operating characteristics of CAD algorithms in the absence of a gold standard
DOE Office of Scientific and Technical Information (OSTI.GOV)
Roy Choudhury, Kingshuk; Paik, David S.; Yi, Chin A.
2010-04-15
Purpose: The authors examine potential bias when using a reference reader panel as ''gold standard'' for estimating operating characteristics of CAD algorithms for detecting lesions. As an alternative, the authors propose latent class analysis (LCA), which does not require an external gold standard to evaluate diagnostic accuracy. Methods: A binomial model for multiple reader detections using different diagnostic protocols was constructed, assuming conditional independence of readings given true lesion status. Operating characteristics of all protocols were estimated by maximum likelihood LCA. Reader panel and LCA based estimates were compared using data simulated from the binomial model for a range ofmore » operating characteristics. LCA was applied to 36 thin section thoracic computed tomography data sets from the Lung Image Database Consortium (LIDC): Free search markings of four radiologists were compared to markings from four different CAD assisted radiologists. For real data, bootstrap-based resampling methods, which accommodate dependence in reader detections, are proposed to test of hypotheses of differences between detection protocols. Results: In simulation studies, reader panel based sensitivity estimates had an average relative bias (ARB) of -23% to -27%, significantly higher (p-value <0.0001) than LCA (ARB -2% to -6%). Specificity was well estimated by both reader panel (ARB -0.6% to -0.5%) and LCA (ARB 1.4%-0.5%). Among 1145 lesion candidates LIDC considered, LCA estimated sensitivity of reference readers (55%) was significantly lower (p-value 0.006) than CAD assisted readers' (68%). Average false positives per patient for reference readers (0.95) was not significantly lower (p-value 0.28) than CAD assisted readers' (1.27). Conclusions: Whereas a gold standard based on a consensus of readers may substantially bias sensitivity estimates, LCA may be a significantly more accurate and consistent means for evaluating diagnostic accuracy.« less
A new approach to develop computer-aided detection schemes of digital mammograms
NASA Astrophysics Data System (ADS)
Tan, Maxine; Qian, Wei; Pu, Jiantao; Liu, Hong; Zheng, Bin
2015-06-01
The purpose of this study is to develop a new global mammographic image feature analysis based computer-aided detection (CAD) scheme and evaluate its performance in detecting positive screening mammography examinations. A dataset that includes images acquired from 1896 full-field digital mammography (FFDM) screening examinations was used in this study. Among them, 812 cases were positive for cancer and 1084 were negative or benign. After segmenting the breast area, a computerized scheme was applied to compute 92 global mammographic tissue density based features on each of four mammograms of the craniocaudal (CC) and mediolateral oblique (MLO) views. After adding three existing popular risk factors (woman’s age, subjectively rated mammographic density, and family breast cancer history) into the initial feature pool, we applied a sequential forward floating selection feature selection algorithm to select relevant features from the bilateral CC and MLO view images separately. The selected CC and MLO view image features were used to train two artificial neural networks (ANNs). The results were then fused by a third ANN to build a two-stage classifier to predict the likelihood of the FFDM screening examination being positive. CAD performance was tested using a ten-fold cross-validation method. The computed area under the receiver operating characteristic curve was AUC = 0.779 ± 0.025 and the odds ratio monotonically increased from 1 to 31.55 as CAD-generated detection scores increased. The study demonstrated that this new global image feature based CAD scheme had a relatively higher discriminatory power to cue the FFDM examinations with high risk of being positive, which may provide a new CAD-cueing method to assist radiologists in reading and interpreting screening mammograms.
Infantino, M; Meacci, F; Grossi, V; Manfredi, M; Benucci, M; Merone, M; Soda, P
2017-02-01
According to the recent recommendations of the American College of Rheumatology, ANA Task Force, IIF technique should be considered the gold standard in antinuclear antibodies (ANAs) testing. To overcome the lack of standardization, biomedical industries have developed several computer-aided diagnosis (CAD) systems. Two hundred and sixty-one consecutive samples with suspected autoimmune diseases were tested for ANA by means of IIF on routinely HEp-2 assay kit (Euroimmun AG). Assignment of result was made if consensus for positive/negative was reached by at least 2 out of 3 expert physicians. ANA-IIF was also carried out using 3 CAD systems: Zenit G-Sight (n = 84), Helios (n = 85) and NOVA View (n = 92); human evaluation was repeated on the same substrate of each CAD system (Immco, Aesku and Inova HEp-2 cells, respectively). To anonymize the results, we randomly named these three systems as A, B and C. We ran a statistical analysis computing several measures of agreement between the ratings, and we also improved the evaluation by using the Wilcoxon's test for nonparametric data. Agreement between the human readings on routinely HEp-2 assay kit and human readings on CAD HEp-2 assay was substantial for A (k = 0.82) and B (k = 0.72), and almost perfect for C (k = 0.89). Such readings were statistically different only in case A. Comparing experts' readings with the readings of CAD systems, when the samples were prepared using CAD HEp-2 assay kits, we found almost perfect agreement for B and C (k = 0.86; k = 0.82) and substantial agreement for A (k = 0.73). Again, human and CAD readings were statistically different only in A. When we compared the readings of medical experts on routinely HEp-2 assay kit with the output of the CAD systems that worked using their own slides, we found substantial agreement for all the systems (A: k = 0.62; B: k = 0.65; C: k = 0.71). Such readings were not statistically different. The change of the assay kit and/or the introduction of a CAD system affect the laboratory reporting, with an evident impact on the autoimmune laboratory workflow. The CAD systems may represent one of the most important novel elements of harmonization in the autoimmunity field, reducing intra- and inter-laboratory variability in a new vision of the diagnostic autoimmune platform.
21 CFR 872.3661 - Optical Impression Systems for CAD/CAM.
Code of Federal Regulations, 2011 CFR
2011-04-01
... (CONTINUED) MEDICAL DEVICES DENTAL DEVICES Prosthetic Devices § 872.3661 Optical Impression Systems for CAD... (CAD/CAM) is a device used to record the topographical characteristics of teeth, dental impressions, or stone models by analog or digital methods for use in the computer-assisted design and manufacturing of...
Automatic image database generation from CAD for 3D object recognition
NASA Astrophysics Data System (ADS)
Sardana, Harish K.; Daemi, Mohammad F.; Ibrahim, Mohammad K.
1993-06-01
The development and evaluation of Multiple-View 3-D object recognition systems is based on a large set of model images. Due to the various advantages of using CAD, it is becoming more and more practical to use existing CAD data in computer vision systems. Current PC- level CAD systems are capable of providing physical image modelling and rendering involving positional variations in cameras, light sources etc. We have formulated a modular scheme for automatic generation of various aspects (views) of the objects in a model based 3-D object recognition system. These views are generated at desired orientations on the unit Gaussian sphere. With a suitable network file sharing system (NFS), the images can directly be stored on a database located on a file server. This paper presents the image modelling solutions using CAD in relation to multiple-view approach. Our modular scheme for data conversion and automatic image database storage for such a system is discussed. We have used this approach in 3-D polyhedron recognition. An overview of the results, advantages and limitations of using CAD data and conclusions using such as scheme are also presented.
Next Generation CAD/CAM/CAE Systems
NASA Technical Reports Server (NTRS)
Noor, Ahmed K. (Compiler); Malone, John B. (Compiler)
1997-01-01
This document contains presentations from the joint UVA/NASA Workshop on Next Generation CAD/CAM/CAE Systems held at NASA Langley Research Center in Hampton, Virginia on March 18-19, 1997. The presentations focused on current capabilities and future directions of CAD/CAM/CAE systems, aerospace industry projects, and university activities related to simulation-based design. Workshop attendees represented NASA, commercial software developers, the aerospace industry, government labs, and academia. The workshop objectives were to assess the potential of emerging CAD/CAM/CAE technology for use in intelligent simulation-based design and to provide guidelines for focused future research leading to effective use of CAE systems for simulating the entire life cycle of aerospace systems.
NASA Astrophysics Data System (ADS)
Guo, Yanhui; Zhou, Chuan; Chan, Heang-Ping; Wei, Jun; Chughtai, Aamer; Sundaram, Baskaran; Hadjiiski, Lubomir M.; Patel, Smita; Kazerooni, Ella A.
2013-04-01
A 3D multiscale intensity homogeneity transformation (MIHT) method was developed to reduce false positives (FPs) in our previously developed CAD system for pulmonary embolism (PE) detection. In MIHT, the voxel intensity of a PE candidate region was transformed to an intensity homogeneity value (IHV) with respect to the local median intensity. The IHVs were calculated in multiscales (MIHVs) to measure the intensity homogeneity, taking into account vessels of different sizes and different degrees of occlusion. Seven new features including the entropy, gradient, and moments that characterized the intensity distributions of the candidate regions were derived from the MIHVs and combined with the previously designed features that described the shape and intensity of PE candidates for the training of a linear classifier to reduce the FPs. 59 CTPA PE cases were collected from our patient files (UM set) with IRB approval and 69 cases from the PIOPED II data set with access permission. 595 and 800 PEs were identified as reference standard by experienced thoracic radiologists in the UM and PIOPED set, respectively. FROC analysis was used for performance evaluation. Compared with our previous CAD system, at a test sensitivity of 80%, the new method reduced the FP rate from 18.9 to 14.1/scan for the PIOPED set when the classifier was trained with the UM set and from 22.6 to 16.0/scan vice versa. The improvement was statistically significant (p<0.05) by JAFROC analysis. This study demonstrated that the MIHT method is effective in reducing FPs and improving the performance of the CAD system.
NASA Astrophysics Data System (ADS)
Le, Anh H.; Park, Young W.; Ma, Kevin; Jacobs, Colin; Liu, Brent J.
2010-03-01
Multiple Sclerosis (MS) is a progressive neurological disease affecting myelin pathways in the brain. Multiple lesions in the white matter can cause paralysis and severe motor disabilities of the affected patient. To solve the issue of inconsistency and user-dependency in manual lesion measurement of MRI, we have proposed a 3-D automated lesion quantification algorithm to enable objective and efficient lesion volume tracking. The computer-aided detection (CAD) of MS, written in MATLAB, utilizes K-Nearest Neighbors (KNN) method to compute the probability of lesions on a per-voxel basis. Despite the highly optimized algorithm of imaging processing that is used in CAD development, MS CAD integration and evaluation in clinical workflow is technically challenging due to the requirement of high computation rates and memory bandwidth in the recursive nature of the algorithm. In this paper, we present the development and evaluation of using a computing engine in the graphical processing unit (GPU) with MATLAB for segmentation of MS lesions. The paper investigates the utilization of a high-end GPU for parallel computing of KNN in the MATLAB environment to improve algorithm performance. The integration is accomplished using NVIDIA's CUDA developmental toolkit for MATLAB. The results of this study will validate the practicality and effectiveness of the prototype MS CAD in a clinical setting. The GPU method may allow MS CAD to rapidly integrate in an electronic patient record or any disease-centric health care system.
3D Silicon Coincidence Avalanche Detector (3D-SiCAD) for charged particle detection
NASA Astrophysics Data System (ADS)
Vignetti, M. M.; Calmon, F.; Pittet, P.; Pares, G.; Cellier, R.; Quiquerez, L.; Chaves de Albuquerque, T.; Bechetoille, E.; Testa, E.; Lopez, J.-P.; Dauvergne, D.; Savoy-Navarro, A.
2018-02-01
Single-Photon Avalanche Diodes (SPADs) are p-n junctions operated in Geiger Mode by applying a reverse bias above the breakdown voltage. SPADs have the advantage of featuring single photon sensitivity with timing resolution in the picoseconds range. Nevertheless, their relatively high Dark Count Rate (DCR) is a major issue for charged particle detection, especially when it is much higher than the incoming particle rate. To tackle this issue, we have developed a 3D Silicon Coincidence Avalanche Detector (3D-SiCAD). This novel device implements two vertically aligned SPADs featuring on-chip electronics for the detection of coincident avalanche events occurring on both SPADs. Such a coincidence detection mode allows an efficient discrimination of events related to an incoming charged particle (producing a quasi-simultaneous activation of both SPADs) from dark counts occurring independently on each SPAD. A 3D-SiCAD detector prototype has been fabricated in CMOS technology adopting a 3D flip-chip integration technique, and the main results of its characterization are reported in this work. The particle detection efficiency and noise rejection capability for this novel device have been evaluated by means of a β- strontium-90 radioactive source. Moreover the impact of the main operating parameters (i.e. the hold-off time, the coincidence window duration, the SPAD excess bias voltage) over the particle detection efficiency has been studied. Measurements have been performed with different β- particles rates and show that a 3D-SiCAD device outperforms single SPAD detectors: the former is indeed capable to detect particle rates much lower than the individual DCR observed in a single SPAD-based detectors (i.e. 2 to 3 orders of magnitudes lower).
Cao, Peng; Liu, Xiaoli; Bao, Hang; Yang, Jinzhu; Zhao, Dazhe
2015-01-01
The false-positive reduction (FPR) is a crucial step in the computer aided detection system for the breast. The issues of imbalanced data distribution and the limitation of labeled samples complicate the classification procedure. To overcome these challenges, we propose oversampling and semi-supervised learning methods based on the restricted Boltzmann machines (RBMs) to solve the classification of imbalanced data with a few labeled samples. To evaluate the proposed method, we conducted a comprehensive performance study and compared its results with the commonly used techniques. Experiments on benchmark dataset of DDSM demonstrate the effectiveness of the RBMs based oversampling and semi-supervised learning method in terms of geometric mean (G-mean) for false positive reduction in Breast CAD.
Schlenz, Maximiliane Amelie; Schmidt, Alexander; Rehmann, Peter; Niem, Thomas; Wöstmann, Bernd
2018-04-24
To investigate debonding of full crowns made of CAD/CAM composites, CAD/CAM technology was applied to manufacture standardized test abutments to increase the reproducibility of human teeth used in in vitro studies. A virtual test abutment and the corresponding virtual crown were designed and two STL data sets were generated. Sixty-four human third molars and CAD/CAM blocks were milled using a CNC machine. Crowns of four different composite blocks (Lava Ultimate (LU), Brilliant Crios (BC), Cerasmart (CS), Experimental (EX)) were adhesively bonded with their corresponding luting system (LU: Scotchbond Universal/RelyX Ultimate; BC: One Coat 7 Universal/DuoCem; CS: G-PremioBond/G-Cem LinkForce; EX: Experimental-Bond/Experimental-Luting-Cement). Half of the specimens were chemical-cured (CC) and the others were light-cured (LC). Afterwards, specimens were artificially aged in a chewing simulator (WL-tec, 1 million cycles, 50-500 N, 2 Hz, 37 °C). Finally, a dye penetration test was used to detect debonding. For inspection, the specimens were sliced, and penetration depth was measured with a digital microscope. Data were analyzed with the Mann-Whitney U test. No cases of total debonding were observed after cyclic loading. However, the LC specimens showed a significantly lower amount of leakage than the CC ones (p < 0.05). Furthermore, the CC specimens exhibited broad scattering. Only the LC-EX blocks showed no debonding. The CC-CS blocks showed the highest leakage and scattering of all tested specimens. Natural human teeth can be manufactured by CAD/CAM technology in highly standardized test abutments for in vitro testing. For CAD/CAM composites, light curing should be performed. The success of a restoration depends on the long-term sealing ability of the luting materials, which avoids debonding along with microleakage. For CAD/CAM composites, separate light curing of the adhesive and luting composite is highly recommended.
21 CFR 872.3661 - Optical Impression Systems for CAD/CAM.
Code of Federal Regulations, 2010 CFR
2010-04-01
... 21 Food and Drugs 8 2010-04-01 2010-04-01 false Optical Impression Systems for CAD/CAM. 872.3661 Section 872.3661 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN SERVICES... Design and Manufacturing (CAD/CAM) of Dental Restorations; Guidance for Industry and FDA.” For the...
2017-01-01
Purpose Inflammatory rheumatic diseases (IRD) are associated with accelerated coronary artery disease (CAD), which may result from both systemic and vascular wall inflammation. There are indications that complement may be involved in the pathogenesis of CAD in Systemic Lupus Erythematosus (SLE) and Rheumatoid Arthritis (RA). This study aimed to evaluate the associations between circulating complement and complement activation products with mononuclear cell infiltrates (MCI, surrogate marker of vascular inflammation) in the aortic media and adventitia in IRDCAD and non-IRDCAD patients undergoing coronary artery bypass grafting (CABG). Furthermore, we compared complement activation product deposition patterns in rare aorta adventitial and medial biopsies from SLE, RA and non-IRD patients. Methods We examined plasma C3 (p-C3) and terminal complement complexes (p-TCC) in 28 IRDCAD (SLE = 3; RA = 25), 52 non-IRDCAD patients, and 32 IRDNo CAD (RA = 32) from the Feiring Heart Biopsy Study. Aortic biopsies taken from the CAD only patients during CABG were previously evaluated for adventitial MCIs. The rare aortic biopsies from 3 SLE, 3 RA and 3 non-IRDCAD were assessed for the presence of C3 and C3d using immunohistochemistry. Results IRDCAD patients had higher p-TCC than non-IRDCAD or IRDNo CAD patients (p<0.0001), but a similar p-C3 level (p = 0.42). Circulating C3 was associated with IRD duration (ρ, p-value: 0.46, 0.03). In multiple logistic regression analysis, IRD remained significantly related to the presence and size of MCI (p<0.05). C3 was present in all tissue samples. C3d was detected in the media of all patients and only in the adventitia of IRD patients (diffuse in all SLE and focal in one RA). Conclusion The independent association of IRD status with MCI and the observed C3d deposition supports the unique relationship between rheumatic disease, and, in particular, SLE with the complement system. Exaggerated systemic and vascular complement activation may accelerate CVD, serve as a CVD biomarker, and represent a target for new therapies. PMID:28362874
Nomura, Yukihiro; Higaki, Toru; Fujita, Masayo; Miki, Soichiro; Awaya, Yoshikazu; Nakanishi, Toshio; Yoshikawa, Takeharu; Hayashi, Naoto; Awai, Kazuo
2017-02-01
This study aimed to evaluate the effects of iterative reconstruction (IR) algorithms on computer-assisted detection (CAD) software for lung nodules in ultra-low-dose computed tomography (ULD-CT) for lung cancer screening. We selected 85 subjects who underwent both a low-dose CT (LD-CT) scan and an additional ULD-CT scan in our lung cancer screening program for high-risk populations. The LD-CT scans were reconstructed with filtered back projection (FBP; LD-FBP). The ULD-CT scans were reconstructed with FBP (ULD-FBP), adaptive iterative dose reduction 3D (AIDR 3D; ULD-AIDR 3D), and forward projected model-based IR solution (FIRST; ULD-FIRST). CAD software for lung nodules was applied to each image dataset, and the performance of the CAD software was compared among the different IR algorithms. The mean volume CT dose indexes were 3.02 mGy (LD-CT) and 0.30 mGy (ULD-CT). For overall nodules, the sensitivities of CAD software at 3.0 false positives per case were 78.7% (LD-FBP), 9.3% (ULD-FBP), 69.4% (ULD-AIDR 3D), and 77.8% (ULD-FIRST). Statistical analysis showed that the sensitivities of ULD-AIDR 3D and ULD-FIRST were significantly higher than that of ULD-FBP (P < .001). The performance of CAD software in ULD-CT was improved by using IR algorithms. In particular, the performance of CAD in ULD-FIRST was almost equivalent to that in LD-FBP. Copyright © 2017 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.
Education and Training Packages for CAD/CAM.
ERIC Educational Resources Information Center
Wright, I. C.
1986-01-01
Discusses educational efforts in the fields of Computer Assisted Design and Manufacturing (CAD/CAM). Describes two educational training initiatives underway in the United Kingdom, one of which is a resource materials package for teachers of CAD/CAM at the undergraduate level, and the other a training course for managers of CAD/CAM systems. (TW)
Role of nuclear cardiology in evaluating the total ischemic burden in coronary artery disease
DOE Office of Scientific and Technical Information (OSTI.GOV)
Beller, G.A.
1987-03-09
Goals of exercise radionuclide imaging are to: enhance sensitivity, specificity and predictive value of coronary artery disease (CAD) detection; noninvasively assess extent and severity of functionally significant CAD; determine prognosis so that specific therapeutic strategies can be more rationally implemented; detect silent ischemia in asymptomatic subjects or in patients with known CAD with a higher degree of specificity than can be accomplished by electrocardiogram stress testing alone; evaluate the response to therapeutic interventions aimed at enhancing coronary blood flow. Two major radionuclide techniques are currently used in evaluating the total ischemic burden in patients with CAD. These are myocardial perfusionmore » imaging with either thallium-201 or rubidium-82, and radionuclide angiography performed after administration of technetium-99m. Areas of diminished thallium-201 activity on early postexercise images are abnormal and represent either areas of stress-induced ischemia or myocardial scar. To differentiate between the two, delayed images are obtained to determine if the initial postexercise defect either persists or demonstrates redistribution. Defects demonstrating redistribution represent transient ischemia, whereas areas of previous infarction or scar usually appear as persistent defects. Patients with left main or 3-vessel CAD usually show multiple thallium-201 redistribution defects in more than 1 vascular supply region, a phenomenon often associated with abnormal lung thallium-201 uptake.« less
Eadie, Leila H; Taylor, Paul; Gibson, Adam P
2012-04-01
Computer-assisted diagnosis (CAD) describes a diverse, heterogeneous range of applications rather than a single entity. The aims and functions of CAD systems vary considerably and comparing studies and systems is challenging due to methodological and design differences. In addition, poor study quality and reporting can reduce the value of some publications. Meta-analyses of CAD are therefore difficult and may not provide reliable conclusions. Aiming to determine the major sources of heterogeneity and thereby what CAD researchers could change to allow this sort of assessment, this study reviews a sample of 147 papers concerning CAD used with imaging for cancer diagnosis. It discusses sources of variability, including the goal of the CAD system, learning methodology, study population, design, outcome measures, inclusion of radiologists, and study quality. Based upon this evidence, recommendations are made to help researchers optimize the quality and comparability of their trial design and reporting. Copyright © 2011 Elsevier Inc. All rights reserved.
Marginal and internal fits of fixed dental prostheses zirconia retainers.
Beuer, Florian; Aggstaller, Hans; Edelhoff, Daniel; Gernet, Wolfgang; Sorensen, John
2009-01-01
CAM (computer-aided manufacturing) and CAD (computer-aided design)/CAM systems facilitate the use of zirconia substructure materials for all-ceramic fixed partial dentures. This in vitro study compared the precision of fit of frameworks milled from semi-sintered zirconia blocks that were designed and machined with two CAD/CAM and one CAM system. Three-unit posterior fixed dental prostheses (FDP) (n=10) were fabricated for standardized dies by: a milling center CAD/CAM system (Etkon), a laboratory CAD/CAM system (Cerec InLab), and a laboratory CAM system (Cercon). After adaptation by a dental technician, the FDP were cemented on definitive dies, embedded and sectioned. The marginal and internal fits were measured under an optical microscope at 50x magnification. A one-way analysis of variance (ANOVA) was used to compare data (alpha=0.05). The mean (S.D.) for the marginal fit and internal fit adaptation were: 29.1 microm (14.0) and 62.7 microm (18.9) for the milling center system, 56.6 microm (19.6) and 73.5 microm (20.6) for the laboratory CAD/CAM system, and 81.4 microm (20.3) and 119.2 microm (37.5) for the laboratory CAM system. One-way ANOVA showed significant differences between systems for marginal fit (P<0.001) and internal fit (P<0.001). All systems showed marginal gaps below 120 microm and were therefore considered clinically acceptable. The CAD/CAM systems were more precise than the CAM system.
Coy, Heidi; Young, Jonathan R; Douek, Michael L; Brown, Matthew S; Sayre, James; Raman, Steven S
2017-07-01
To evaluate the performance of a novel, quantitative computer-aided diagnostic (CAD) algorithm on four-phase multidetector computed tomography (MDCT) to detect peak lesion attenuation to enable differentiation of clear cell renal cell carcinoma (ccRCC) from chromophobe RCC (chRCC), papillary RCC (pRCC), oncocytoma, and fat-poor angiomyolipoma (fp-AML). We queried our clinical databases to obtain a cohort of histologically proven renal masses with preoperative MDCT with four phases [unenhanced (U), corticomedullary (CM), nephrographic (NP), and excretory (E)]. A whole lesion 3D contour was obtained in all four phases. The CAD algorithm determined a region of interest (ROI) of peak lesion attenuation within the 3D lesion contour. For comparison, a manual ROI was separately placed in the most enhancing portion of the lesion by visual inspection for a reference standard, and in uninvolved renal cortex. Relative lesion attenuation for both CAD and manual methods was obtained by normalizing the CAD peak lesion attenuation ROI (and the reference standard manually placed ROI) to uninvolved renal cortex with the formula [(peak lesion attenuation ROI - cortex ROI)/cortex ROI] × 100%. ROC analysis and area under the curve (AUC) were used to assess diagnostic performance. Bland-Altman analysis was used to compare peak ROI between CAD and manual method. The study cohort comprised 200 patients with 200 unique renal masses: 106 (53%) ccRCC, 32 (16%) oncocytomas, 18 (9%) chRCCs, 34 (17%) pRCCs, and 10 (5%) fp-AMLs. In the CM phase, CAD-derived ROI enabled characterization of ccRCC from chRCC, pRCC, oncocytoma, and fp-AML with AUCs of 0.850 (95% CI 0.732-0.968), 0.959 (95% CI 0.930-0.989), 0.792 (95% CI 0.716-0.869), and 0.825 (95% CI 0.703-0.948), respectively. On Bland-Altman analysis, there was excellent agreement of CAD and manual methods with mean differences between 14 and 26 HU in each phase. A novel, quantitative CAD algorithm enabled robust peak HU lesion detection and discrimination of ccRCC from other renal lesions with similar performance compared to the manual method.
Non-localization and localization ROC analyses using clinically based scoring
NASA Astrophysics Data System (ADS)
Paquerault, Sophie; Samuelson, Frank W.; Myers, Kyle J.; Smith, Robert C.
2009-02-01
We are investigating the potential for differences in study conclusions when assessing the estimated impact of a computer-aided detection (CAD) system on readers' performance. The data utilized in this investigation were derived from a multi-reader multi-case observer study involving one hundred mammographic background images to which fixed-size and fixed-intensity Gaussian signals were added, generating a low- and high-intensity signal sets. The study setting allowed CAD assessment in two situations: when CAD sensitivity was 1) superior or 2) lower than the average reader. Seven readers were asked to review each set in the unaided and CAD-aided reading modes, mark and rate their findings. Using this data, we studied the effect on study conclusion of three clinically-based receiver operating characteristic (ROC) scoring definitions. These scoring definitions included both location-specific and non-location-specific rules. The results showed agreement in the estimated impact of CAD on the overall reader performance. In the study setting where CAD sensitivity is superior to the average reader, the mean difference in AUC between the CAD-aided read and unaided read was 0.049 (95%CIs: -0.027; 0.130) for the image scoring definition that is based on non-location-specific rules, and 0.104 (95%CIs: 0.036; 0.174) and 0.090 (95%CIs: 0.031; 0.155) for image scoring definitions that are based on location-specific rules. The increases in AUC were statistically significant for the location-specific scoring definitions. It was further observed that the variance on these estimates was reduced when using the location-specific scoring definitions compared to that using a non-location-specific scoring definition. In the study setting where CAD sensitivity is equivalent or lower than the average reader, the mean differences in AUC are slightly above 0.01 for all image scoring definitions. These increases in AUC were not statistical significant for any of the image scoring definitions. The results on the variance analysis differed from those observed in the other study setting. This investigation furthers our understanding of the relationships between non-localization-specific and localization-specific ROC assessment methodologies and their relevance to clinical practice.
Knol, Remco J J; Kan, Huub; Wondergem, Maurits; Cornel, Jan H; Umans, Victor A W M; van der Ploeg, Tjeerd; van der Zant, Friso M
2018-04-01
The value of exercise electrocardiogram (ExECG) in symptomatic female patients with low to intermediate risk for significant coronary artery disease (CAD) has been under debate for many years, and nondiagnostic or even erroneous test results are frequently encountered. Cardiac-CT may be more appropriate to exclude CAD in women. This study compares the results of ExECGs with those of cardiac-CTs, performed within a time frame of 1 month in an all-comers female chest pain population. Five hundred fifty-one consecutive female patients from a patient registry were included. ExECGs were negative in 324 (59%), positive in 14 (3%), and nondiagnostic in 213 (39%) patients. CAD was revealed by cardiac-CT in 57% of the women with negative ExECG. No signs of CAD were present on cardiac-CT in 64% of the women with a positive ExECG. Cardiac-CT showed presence of CAD in 268/551 (49%) patients, of whom 56/268 (21%) was diagnosed with ≥50% stenosis. The ExECG of the latter group was negative in 26 (46%), inconclusive in 29 (52%), and positive in 1 (2%). Considering ≥50% stenosis at cardiac-CT as the reference, sensitivity, specificity, PPV, and NPV of ExECG for the present population were 3.7%, 95.7%, 7.1%, and 91.7%, respectively. Similar diagnostic performance was calculated when considering ≥70% stenosis at cardiac-CT as the reference. ExECG failed to detect CAD in more than half of this cohort and in almost half of women with >50% stenosis at cardiac-CT. Importantly, no CAD was detected by cardiac-CT in 64% of women with a positive ExECG. ExECG is therefore questionable as a diagnostic strategy in women with low-to-intermediate risk of CAD, although prospective studies are warranted to determine whether replacing ExECG by cardiac-CT provides better prognoses.
An automated distinction of DICOM images for lung cancer CAD system
NASA Astrophysics Data System (ADS)
Suzuki, H.; Saita, S.; Kubo, M.; Kawata, Y.; Niki, N.; Nishitani, H.; Ohmatsu, H.; Eguchi, K.; Kaneko, M.; Moriyama, N.
2009-02-01
Automated distinction of medical images is an important preprocessing in Computer-Aided Diagnosis (CAD) systems. The CAD systems have been developed using medical image sets with specific scan conditions and body parts. However, varied examinations are performed in medical sites. The specification of the examination is contained into DICOM textual meta information. Most DICOM textual meta information can be considered reliable, however the body part information cannot always be considered reliable. In this paper, we describe an automated distinction of DICOM images as a preprocessing for lung cancer CAD system. Our approach uses DICOM textual meta information and low cost image processing. Firstly, the textual meta information such as scan conditions of DICOM image is distinguished. Secondly, the DICOM image is set to distinguish the body parts which are identified by image processing. The identification of body parts is based on anatomical structure which is represented by features of three regions, body tissue, bone, and air. The method is effective to the practical use of lung cancer CAD system in medical sites.
Dodani, Sunita
2008-01-01
Background: Coronary artery disease (CAD) is the leading cause of mortality and morbidity in the United States (US), and South Asian immigrants (SAIs) have a higher risk of CAD compared to Caucasians. Traditional risk factors may not completely explain high risk, and some of the unknown risk factors need to be explored. This short review is mainly focused on the possible role of dysfunctional high-density lipoprotein (HDL) in causing CAD and presents an overview of available literature on dysfunctional HDL. Discussion: The conventional risk factors, insulin resistance parameters, and metabolic syndrome, although important in predicting CAD risk, may not sufficiently predict risk in SAIs. HDL has antioxidant, antiinflammatory, and antithrombotic properties that contribute to its function as an antiatherogenic agent. Recent Caucasian studies have shown HDL is not only ineffective as an antioxidant but, paradoxically, appears to be prooxidant, and has been found to be associated with CAD. Several causes have been hypothesized for HDL to become dysfunctional, including Apo lipoprotein A-I (Apo A-I) polymorphisms. New risk factors and markers like dysfunctional HDL and genetic polymorphisms may be associated with CAD. Conclusions: More research is required in SAIs to explore associations with CAD and to enhance early detection and prevention of CAD in this high risk group. PMID:19183743
Ribeiro, Isabella Lima Arrais; Campos, Fernanda; Sousa, Rafael Santiago; Alves, Maria Luiza Lima; Rodrigues, Dalton Matos; Souza, Rodrigo Othavio Assuncão; Bottino, Marco Antonio
2015-01-01
Discrepancies at the abutment/crown interface can affect the longevity of zirconia restorations. The aim was to evaluate the marginal and internal discrepancies (MD and ID) of zirconia copings manufactured by two milling systems with different finish lines. Three aluminum-master-dies (h = 5.5 mm; Ψ =7.5 mm; 6), with different finish lines (large chamfer [LC]; tilted chamfer [TC]; rounded shoulder [RS]) were fabricated. Twenty impressions were made from each master die and poured. Sixty zirconia copings were manufactured and divided according to the factors "finish line" and "milling system" (n = 10): CAD LC = Computer-aided design/computer-aided manufacturing (CAD/CAM) + LC; CAD TC = CAD/CAM + TC; CAD RS = CAD/CAM + RS; MAD LC = manually aided design/manually aided manufacturing (MAD/MAM) + LC; MAD TC = MAD/MAM + TC; and MAD RS = MAD/MAM + RS. For MD analysis, each coping was fixed, and the distance between the external edges of the coping and the edge of the cervical preparation was measured (50 points). Using the same copings, the ID of each coping was evaluated, by the replica technique, at 12 points equally distributed among the regions (n = 10): Ray (R), axial (A), and occlusal (Occl). The measurements were performed by optical microscopy (Χ250). The data (μm) were subjected to parametric and non-parametric statistical analyses. For the MAD/MAM system, the "finish line" (P = 0.0001) affected significantly the MD median values (μm): LC = 251.80 a , RS = 68.40 a and TC = 8.10 b (Dunn's test). For the CAD/CAM system, the median MD values (μm) were not affected by the factor "finish line" (P = 0.4037): LC = 0.82 a , RS = 0.52 a , and TC = 0.89 a . For the ID, it was observed interaction between the finish line types and the region (P = 0.0001) and between region and milling system (P = 0.0031) (RM-ANOVA). The CAD/CAM system presented lower MD values, regardless the finish line. However, the MAD/MAM system showed ID values smaller than those of CAD/CAM.
TH-AB-207A-12: CT Lung Cancer Screening and the Effects of Further Dose Reduction On CAD Performance
DOE Office of Scientific and Technical Information (OSTI.GOV)
Young, S; Lo, P; Hoffman, J
Purpose: CT lung screening is already performed at low doses. In this study, we investigated the effects of further dose reduction on a lung-nodule CAD detection algorithm. Methods: The original raw CT data and images from 348 patients were obtained from our local database of National Lung Screening Trial (NLST) cases. 61 patients (17.5%) had at least one nodule reported on the NLST reader forms. All scans were acquired with fixed mAs (25 for standard-sized patients, 40 for large patients) on a 64-slice scanner (Sensation 64, Siemens Healthcare). All images were reconstructed with 1-mm slice thickness, B50 kernel. Based onmore » a previously-published technique, we added noise to the raw data to simulate reduced-dose versions of each case at 50% and 25% of the original NLST dose (i.e. approximately 1.0 and 0.5 mGy CTDIvol). For each case at each dose level, a CAD detection algorithm was run and nodules greater than 4 mm in diameter were reported. These CAD results were compared to “truth”, defined as the approximate nodule centroids from the NLST forms. Sensitivities and false-positive rates (FPR) were calculated for each dose level, with a sub-analysis by nodule LungRADS category. Results: For larger category 4 nodules, median sensitivities were 100% at all three dose levels, and mean sensitivity decreased with dose. For the more challenging category 2 and 3 nodules, the dose dependence was less obvious. Overall, mean subject-level sensitivity varied from 38.5% at 100% dose to 40.4% at 50% dose, a difference of only 1.9%. However, median FPR quadrupled from 1 per case at 100% dose to 4 per case at 25% dose. Conclusions: Dose reduction affected nodule detectability differently depending on the LungRADS category, and FPR was very sensitive at sub-screening levels. Care should be taken to adapt CAD for the very challenging noise characteristics of screening. Funding support: NIH U01 CA181156; Disclosures (McNitt-Gray): Institutional research agreement, Siemens Healthcare; Past recipient, research grant support, Siemens Healthcare; Consultant, Toshiba America Medical Systems; Consultant, Samsung Electronics.« less
The Use of a Parametric Feature Based CAD System to Teach Introductory Engineering Graphics.
ERIC Educational Resources Information Center
Howell, Steven K.
1995-01-01
Describes the use of a parametric-feature-based computer-aided design (CAD) System, AutoCAD Designer, in teaching concepts of three dimensional geometrical modeling and design. Allows engineering graphics to go beyond the role of documentation and communication and allows an engineer to actually build a virtual prototype of a design idea and…
Ji, Min-Kyung; Park, Ji-Hee; Park, Sang-Won; Yun, Kwi-Dug; Oh, Gye-Jeong; Lim, Hyun-Pil
2015-08-01
This study was to evaluate the marginal fit of two CAD-CAM anatomic contour zirconia crown systems compared to lithium disilicate glass-ceramic crowns. Shoulder and deep chamfer margin were formed on each acrylic resin tooth model of a maxillary first premolar. Two CAD-CAM systems (Prettau®Zirconia and ZENOSTAR®ZR translucent) and lithium disilicate glass ceramic (IPS e.max®press) crowns were made (n=16). Each crown was bonded to stone dies with resin cement (Rely X Unicem). Marginal gap and absolute marginal discrepancy of crowns were measured using a light microscope equipped with a digital camera (Leica DFC295) magnified by a factor of 100. Two-way analysis of variance (ANOVA) and post-hoc Tukey's HSD test were conducted to analyze the significance of crown marginal fit regarding the finish line configuration and the fabrication system. The mean marginal gap of lithium disilicate glass ceramic crowns (IPS e.max®press) was significantly lower than that of the CAD-CAM anatomic contour zirconia crown system (Prettau®Zirconia) (P<.05). Both fabrication systems and finish line configurations significantly influenced the absolute marginal discrepancy (P<.05). The lithium disilicate glass ceramic crown (IPS e.max®press) had significantly smaller marginal gap than the CAD-CAM anatomic contour zirconia crown system (Prettau®Zirconia). In terms of absolute marginal discrepancy, the CAD-CAM anatomic contour zirconia crown system (ZENOSTAR®ZR translucent) had under-extended margin, whereas the CAD-CAM anatomic contour zirconia crown system (Prettau®Zirconia) and lithium disilicate glass ceramic crowns (IPS e.max®press) had overextended margins.
Computer-aided detection of prostate cancer in T2-weighted MRI within the peripheral zone
NASA Astrophysics Data System (ADS)
Rampun, Andrik; Zheng, Ling; Malcolm, Paul; Tiddeman, Bernie; Zwiggelaar, Reyer
2016-07-01
In this paper we propose a prostate cancer computer-aided diagnosis (CAD) system and suggest a set of discriminant texture descriptors extracted from T2-weighted MRI data which can be used as a good basis for a multimodality system. For this purpose, 215 texture descriptors were extracted and eleven different classifiers were employed to achieve the best possible results. The proposed method was tested based on 418 T2-weighted MR images taken from 45 patients and evaluated using 9-fold cross validation with five patients in each fold. The results demonstrated comparable results to existing CAD systems using multimodality MRI. We achieved an area under the receiver operating curve (A z ) values equal to 90.0%+/- 7.6% , 89.5%+/- 8.9% , 87.9%+/- 9.3% and 87.4%+/- 9.2% for Bayesian networks, ADTree, random forest and multilayer perceptron classifiers, respectively, while a meta-voting classifier using average probability as a combination rule achieved 92.7%+/- 7.4% .
NASA Astrophysics Data System (ADS)
Mirniaharikandehei, Seyedehnafiseh; Hollingsworth, Alan B.; Patel, Bhavika; Heidari, Morteza; Liu, Hong; Zheng, Bin
2018-05-01
This study aims to investigate the feasibility of identifying a new quantitative imaging marker based on false-positives generated by a computer-aided detection (CAD) scheme to help predict short-term breast cancer risk. An image dataset including four view mammograms acquired from 1044 women was retrospectively assembled. All mammograms were originally interpreted as negative by radiologists. In the next subsequent mammography screening, 402 women were diagnosed with breast cancer and 642 remained negative. An existing CAD scheme was applied ‘as is’ to process each image. From CAD-generated results, four detection features including the total number of (1) initial detection seeds and (2) the final detected false-positive regions, (3) average and (4) sum of detection scores, were computed from each image. Then, by combining the features computed from two bilateral images of left and right breasts from either craniocaudal or mediolateral oblique view, two logistic regression models were trained and tested using a leave-one-case-out cross-validation method to predict the likelihood of each testing case being positive in the next subsequent screening. The new prediction model yielded the maximum prediction accuracy with an area under a ROC curve of AUC = 0.65 ± 0.017 and the maximum adjusted odds ratio of 4.49 with a 95% confidence interval of (2.95, 6.83). The results also showed an increasing trend in the adjusted odds ratio and risk prediction scores (p < 0.01). Thus, this study demonstrated that CAD-generated false-positives might include valuable information, which needs to be further explored for identifying and/or developing more effective imaging markers for predicting short-term breast cancer risk.
Wu, Minghua; Pedroza, Mesias; Lafyatis, Robert; George, Anuh-Teresa; Mayes, Maureen D.; Assassi, Shervin; Tan, Filemon K.; Brenner, Michael B.; Agarwal, Sandeep K.
2014-01-01
Objective Systemic sclerosis (SSc) is a chronic autoimmune disease clinically manifesting as progressive fibrosis of the skin and internal organs. Recent microarray studies demonstrated that cadherin 11 (Cad-11) expression is increased in the affected skin of patients with SSc. The purpose of this study was to examine our hypothesis that Cad-11 is a mediator of dermal fibrosis. Methods Biopsy samples of skin from SSc patients and healthy control subjects were used for real-time quantitative polymerase chain reaction analysis to assess Cad-11 expression and for immunohistochemistry to determine the expression pattern of Cad-11. To determine whether Cad-11 is a mediator of dermal fibrosis, Cad-11–deficient mice and anti–Cad-11 monoclonal antibodies (mAb) were used in the bleomycin-induced dermal fibrosis model. In vitro studies with dermal fibroblasts and bone marrow–derived macrophages were used to determine the mechanisms by which Cad-11 contributes to the development of tissue fibrosis. Results Levels of messenger RNA for Cad-11 were increased in skin biopsy samples from patients with SSc and correlated with the modified Rodnan skin thickness scores. Cad-11 expression was localized to dermal fibroblasts and macrophages in SSc skin. Cad-11–knockout mice injected with bleomycin had markedly attenuated dermal fibrosis, as quantified by measurements of skin thickness, collagen levels, myofibroblast accumulation, and profibrotic gene expression, in lesional skin as compared to the skin of wild-type mice. In addition, anti–Cad-11 mAb decreased fibrosis at various time points in the bleomycin-induced dermal fibrosis model. In vitro studies demonstrated that Cad-11 regulated the production of transforming growth factor β (TGFβ) by macrophages and the migration of fibroblasts. Conclusion These data demonstrate that Cad-11 is a mediator of dermal fibrosis and TGFβ production and suggest that Cad-11 may be a therapeutic target in SSc. PMID:24757152
Hochman, J; Urowitz, M B; Ibañez, D; Gladman, D D
2009-04-01
We sought to determine the impact of hormone replacement therapy (HRT) on the occurrence of coronary artery disease (CAD) in women with systemic lupus erythematosus (SLE). Women in the University of Toronto lupus database who had taken HRT with no history of CAD were compared with all post-menopausal female patients with no history of HRT or CAD. Chi-squared and t-tests were used to compare the risk factors of CAD and Kaplan-Meier curve, log rank test and proportional hazard model with time-dependent covariates were used to compare the time from entry into the clinic to occurrence of CAD. A total of 114 HRT-user patients with no history of CAD were compared with 227 post-menopausal non-HRT user SLE controls. The groups were similar with respect to lupus anticoagulant, antiphospholipid antibody, cumulative steroid dose and classic cardiac risk factors. A similar percentage of patients developed CAD in the control (13.7%) and HRT (11.4%) groups. There was no difference in the time to development of CAD. In the multivariate analysis, HRT was not a risk factor for CAD. Only age (P = 0.0001, HR = 1.11, 95% CI = 1.05, 1.17) and SLEDAI-2K (P = 0.0001, HR = 1.10, 95% CI = 1.05, 1.16) were significantly associated with the risk of CAD. In this small group of patients with SLE, HRT alone did not appear to predispose to CAD.
Cam Design Projects in an Advanced CAD Course for Mechanical Engineers
ERIC Educational Resources Information Center
Ault, H. K.
2009-01-01
The objective of this paper is to present applications of solid modeling aimed at modeling of complex geometries such as splines and blended surfaces in advanced CAD courses. These projects, in CAD-based Mechanical Engineering courses, are focused on the use of the CAD system to solve design problems for applications in machine design, namely the…
A step-by-step introduction to rule-based design of synthetic genetic constructs using GenoCAD.
Wilson, Mandy L; Hertzberg, Russell; Adam, Laura; Peccoud, Jean
2011-01-01
GenoCAD is an open source web-based system that provides a streamlined, rule-driven process for designing genetic sequences. GenoCAD provides a graphical interface that allows users to design sequences consistent with formalized design strategies specific to a domain, organization, or project. Design strategies include limited sets of user-defined parts and rules indicating how these parts are to be combined in genetic constructs. In addition to reducing design time to minutes, GenoCAD improves the quality and reliability of the finished sequence by ensuring that the designs follow established rules of sequence construction. GenoCAD.org is a publicly available instance of GenoCAD that can be found at www.genocad.org. The source code and latest build are available from SourceForge to allow advanced users to install and customize GenoCAD for their unique needs. This chapter focuses primarily on how the GenoCAD tools can be used to organize genetic parts into customized personal libraries, then how these libraries can be used to design sequences. In addition, GenoCAD's parts management system and search capabilities are described in detail. Instructions are provided for installing a local instance of GenoCAD on a server. Some of the future enhancements of this rapidly evolving suite of applications are briefly described. Copyright © 2011 Elsevier Inc. All rights reserved.
Meinel, Felix G; Schoepf, U Joseph; Townsend, Jacob C; Flowers, Brian A; Geyer, Lucas L; Ebersberger, Ullrich; Krazinski, Aleksander W; Kunz, Wolfgang G; Thierfelder, Kolja M; Baker, Deborah W; Khan, Ashan M; Fernandes, Valerian L; O'Brien, Terrence X
2018-06-15
We aimed to determine the diagnostic yield and accuracy of coronary CT angiography (CCTA) in patients referred for invasive coronary angiography (ICA) based on clinical concern for coronary artery disease (CAD) and an abnormal nuclear stress myocardial perfusion imaging (MPI) study. We enrolled 100 patients (84 male, mean age 59.6 ± 8.9 years) with an abnormal MPI study and subsequent referral for ICA. Each patient underwent CCTA prior to ICA. We analyzed the prevalence of potentially obstructive CAD (≥50% stenosis) on CCTA and calculated the diagnostic accuracy of ≥50% stenosis on CCTA for the detection of clinically significant CAD on ICA (defined as any ≥70% stenosis or ≥50% left main stenosis). On CCTA, 54 patients had at least one ≥50% stenosis. With ICA, 45 patients demonstrated clinically significant CAD. A positive CCTA had 100% sensitivity and 84% specificity with a 100% negative predictive value and 83% positive predictive value for clinically significant CAD on a per patient basis in MPI positive symptomatic patients. In conclusion, almost half (48%) of patients with suspected CAD and an abnormal MPI study demonstrate no obstructive CAD on CCTA.
Yanagawa, Masahiro; Honda, Osamu; Kikuyama, Ayano; Gyobu, Tomoko; Sumikawa, Hiromitsu; Koyama, Mitsuhiro; Tomiyama, Noriyuki
2012-10-01
To evaluate the effects of ASIR on CAD system of pulmonary nodules using clinical routine-dose CT and lower-dose CT. Thirty-five patients (body mass index, 22.17 ± 4.37 kg/m(2)) were scanned by multidetector-row CT with tube currents (clinical routine-dose CT, automatically adjusted mA; lower-dose CT, 10 mA) and X-ray voltage (120 kVp). Each 0.625-mm-thick image was reconstructed at 0%-, 50%-, and 100%-ASIR: 0%-ASIR is reconstructed using only the filtered back-projection algorithm (FBP), while 100%-ASIR is reconstructed using the maximum ASIR and 50%-ASIR implies a blending of 50% FBP and ASIR. CAD output was compared retrospectively with the results of the reference standard which was established using a consensus panel of three radiologists. Data were analyzed using Bonferroni/Dunn's method. Radiation dose was calculated by multiplying dose-length product by conversion coefficient of 0.021. The consensus panel found 265 non-calcified nodules ≤ 30 mm (ground-glass opacity [GGO], 103; part-solid, 34; and solid, 128). CAD sensitivity was significantly higher at 100%-ASIR [clinical routine-dose CT, 71% (overall), 49% (GGO); lower-dose CT, 52% (overall), 67% (solid)] than at 0%-ASIR [clinical routine-dose CT, 54% (overall), 25% (GGO); lower-dose CT, 36% (overall), 50% (solid)] (p<0.001). Mean number of false-positive findings per examination was significantly higher at 100%-ASIR (clinical routine-dose CT, 8.5; lower-dose CT, 6.2) than at 0%-ASIR (clinical routine-dose CT, 4.6; lower-dose CT, 3.5; p<0.001). Effective doses were 10.77 ± 3.41 mSv in clinical routine-dose CT and 2.67 ± 0.17 mSv in lower-dose CT. CAD sensitivity at 100%-ASIR on lower-dose CT is almost equal to that at 0%-ASIR on clinical routine-dose CT. ASIR can increase CAD sensitivity despite increased false-positive findings. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.
Automatic detection of multi-level acetowhite regions in RGB color images of the uterine cervix
NASA Astrophysics Data System (ADS)
Lange, Holger
2005-04-01
Uterine cervical cancer is the second most common cancer among women worldwide. Colposcopy is a diagnostic method used to detect cancer precursors and cancer of the uterine cervix, whereby a physician (colposcopist) visually inspects the metaplastic epithelium on the cervix for certain distinctly abnormal morphologic features. A contrast agent, a 3-5% acetic acid solution, is used, causing abnormal and metaplastic epithelia to turn white. The colposcopist considers diagnostic features such as the acetowhite, blood vessel structure, and lesion margin to derive a clinical diagnosis. STI Medical Systems is developing a Computer-Aided-Diagnosis (CAD) system for colposcopy -- ColpoCAD, a complex image analysis system that at its core assesses the same visual features as used by colposcopists. The acetowhite feature has been identified as one of the most important individual predictors of lesion severity. Here, we present the details and preliminary results of a multi-level acetowhite region detection algorithm for RGB color images of the cervix, including the detection of the anatomic features: cervix, os and columnar region, which are used for the acetowhite region detection. The RGB images are assumed to be glare free, either obtained by cross-polarized image acquisition or glare removal pre-processing. The basic approach of the algorithm is to extract a feature image from the RGB image that provides a good acetowhite to cervix background ratio, to segment the feature image using novel pixel grouping and multi-stage region-growing algorithms that provide region segmentations with different levels of detail, to extract the acetowhite regions from the region segmentations using a novel region selection algorithm, and then finally to extract the multi-levels from the acetowhite regions using multiple thresholds. The performance of the algorithm is demonstrated using human subject data.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Suzuki, Kenji; Yoshida, Hiroyuki; Naeppi, Janne
2006-10-15
One of the limitations of the current computer-aided detection (CAD) of polyps in CT colonography (CTC) is a relatively large number of false-positive (FP) detections. Rectal tubes (RTs) are one of the typical sources of FPs because a portion of a RT, especially a portion of a bulbous tip, often exhibits a cap-like shape that closely mimics the appearance of a small polyp. Radiologists can easily recognize and dismiss RT-induced FPs; thus, they may lose their confidence in CAD as an effective tool if the CAD scheme generates such ''obvious'' FPs due to RTs consistently. In addition, RT-induced FPs maymore » distract radiologists from less common true positives in the rectum. Therefore, removal RT-induced FPs as well as other types of FPs is desirable while maintaining a high sensitivity in the detection of polyps. We developed a three-dimensional (3D) massive-training artificial neural network (MTANN) for distinction between polyps and RTs in 3D CTC volumetric data. The 3D MTANN is a supervised volume-processing technique which is trained with input CTC volumes and the corresponding ''teaching'' volumes. The teaching volume for a polyp contains a 3D Gaussian distribution, and that for a RT contains zeros for enhancement of polyps and suppression of RTs, respectively. For distinction between polyps and nonpolyps including RTs, a 3D scoring method based on a 3D Gaussian weighting function is applied to the output of the trained 3D MTANN. Our database consisted of CTC examinations of 73 patients, scanned in both supine and prone positions (146 CTC data sets in total), with optical colonoscopy as a reference standard for the presence of polyps. Fifteen patients had 28 polyps, 15 of which were 5-9 mm and 13 were 10-25 mm in size. These CTC cases were subjected to our previously reported CAD scheme that included centerline-based segmentation of the colon, shape-based detection of polyps, and reduction of FPs by use of a Bayesian neural network based on geometric and texture features. Application of this CAD scheme yielded 96.4% (27/28) by-polyp sensitivity with 3.1 (224/73) FPs per patient, among which 20 FPs were caused by RTs. To eliminate the FPs due to RTs and possibly other normal structures, we trained a 3D MTANN with ten representative polyps and ten RTs, and applied the trained 3D MTANN to the above CAD true- and false-positive detections. In the output volumes of the 3D MTANN, polyps were represented by distributions of bright voxels, whereas RTs and other normal structures partly similar to RTs appeared as darker voxels, indicating the ability of the 3D MTANN to suppress RTs as well as other normal structures effectively. Application of the 3D MTANN to the CAD detections showed that the 3D MTANN eliminated all RT-induced 20 FPs, as well as 53 FPs due to other causes, without removal of any true positives. Overall, the 3D MTANN was able to reduce the FP rate of the CAD scheme from 3.1 to 2.1 FPs per patient (33% reduction), while the original by-polyp sensitivity of 96.4% was maintained.« less
Computer-aided diagnosis of cavernous malformations in brain MR images.
Wang, Huiquan; Ahmed, S Nizam; Mandal, Mrinal
2018-06-01
Cavernous malformation or cavernoma is one of the most common epileptogenic lesions. It is a type of brain vessel abnormality that can cause serious symptoms such as seizures, intracerebral hemorrhage, and various neurological disorders. Manual detection of cavernomas by physicians in a large set of brain MRI slices is a time-consuming and labor-intensive task and often delays diagnosis. In this paper, we propose a computer-aided diagnosis (CAD) system for cavernomas based on T2-weighted axial plane MRI image analysis. The proposed technique first extracts the brain area based on atlas registration and active contour model, and then performs template matching to obtain candidate cavernoma regions. Texture, the histogram of oriented gradients and local binary pattern features of each candidate region are calculated, and principal component analysis is applied to reduce the feature dimensionality. Support vector machines (SVMs) are finally used to classify each region into cavernoma or non-cavernoma so that most of the false positives (obtained by template matching) are eliminated. The performance of the proposed CAD system is evaluated and experimental results show that it provides superior performance in cavernoma detection compared to existing techniques. Copyright © 2018 Elsevier Ltd. All rights reserved.
CAD-RADS - a new clinical decision support tool for coronary computed tomography angiography.
Foldyna, Borek; Szilveszter, Bálint; Scholtz, Jan-Erik; Banerji, Dahlia; Maurovich-Horvat, Pál; Hoffmann, Udo
2018-04-01
Coronary computed tomography angiography (CTA) has been established as an accurate method to non-invasively assess coronary artery disease (CAD). The proposed 'Coronary Artery Disease Reporting and Data System' (CAD-RADS) may enable standardised reporting of the broad spectrum of coronary CTA findings related to the presence, extent and composition of coronary atherosclerosis. The CAD-RADS classification is a comprehensive tool for summarising findings on a per-patient-basis dependent on the highest-grade coronary artery lesion, ranging from CAD-RADS 0 (absence of CAD) to CAD-RADS 5 (total occlusion of a coronary artery). In addition, it provides suggestions for clinical management for each classification, including further testing and therapeutic options. Despite some limitations, CAD-RADS may facilitate improved communication between imagers and patient caregivers. As such, CAD-RADS may enable a more efficient use of coronary CTA leading to more accurate utilisation of invasive coronary angiograms. Furthermore, widespread use of CAD-RADS may facilitate registry-based research of diagnostic and prognostic aspects of CTA. • CAD-RADS is a tool for standardising coronary CTA reports. • CAD-RADS includes clinical treatment recommendations based on CTA findings. • CAD-RADS has the potential to reduce variability of CTA reports.
Choi, Young Jun; Baek, Jung Hwan; Park, Hye Sun; Shim, Woo Hyun; Kim, Tae Yong; Shong, Young Kee; Lee, Jeong Hyun
2017-04-01
An initial clinical assessment is described of a new, commercially available, computer-aided diagnosis (CAD) system using artificial intelligence (AI) for thyroid ultrasound, and its performance is evaluated in the diagnosis of malignant thyroid nodules and categorization of nodule characteristics. Patients with thyroid nodules with decisive diagnosis, whether benign or malignant, were consecutively enrolled from November 2015 to February 2016. An experienced radiologist reviewed the ultrasound image characteristics of the thyroid nodules, while another radiologist assessed the same thyroid nodules using the CAD system, providing ultrasound characteristics and a diagnosis of whether nodules were benign or malignant. The diagnostic performance and agreement of US characteristics between the experienced radiologist and the CAD system were compared. In total, 102 thyroid nodules from 89 patients were included; 59 (57.8%) were benign and 43 (42.2%) were malignant. The CAD system showed a similar sensitivity as the experienced radiologist (90.7% vs. 88.4%, p > 0.99), but a lower specificity and a lower area under the receiver operating characteristic (AUROC) curve (specificity: 74.6% vs. 94.9%, p = 0.002; AUROC: 0.83 vs. 0.92, p = 0.021). Classifications of the ultrasound characteristics (composition, orientation, echogenicity, and spongiform) between radiologist and CAD system were in substantial agreement (κ = 0.659, 0.740, 0.733, and 0.658, respectively), while the margin showed a fair agreement (κ = 0.239). The sensitivity of the CAD system using AI for malignant thyroid nodules was as good as that of the experienced radiologist, while specificity and accuracy were lower than those of the experienced radiologist. The CAD system showed an acceptable agreement with the experienced radiologist for characterization of thyroid nodules.
IFEMS, an Interactive Finite Element Modeling System Using a CAD/CAM System
NASA Technical Reports Server (NTRS)
Mckellip, S.; Schuman, T.; Lauer, S.
1980-01-01
A method of coupling a CAD/CAM system with a general purpose finite element mesh generator is described. The three computer programs which make up the interactive finite element graphics system are discussed.
Suzuki, Kenji
2009-09-21
Computer-aided diagnosis (CAD) has been an active area of study in medical image analysis. A filter for the enhancement of lesions plays an important role for improving the sensitivity and specificity in CAD schemes. The filter enhances objects similar to a model employed in the filter; e.g. a blob-enhancement filter based on the Hessian matrix enhances sphere-like objects. Actual lesions, however, often differ from a simple model; e.g. a lung nodule is generally modeled as a solid sphere, but there are nodules of various shapes and with internal inhomogeneities such as a nodule with spiculations and ground-glass opacity. Thus, conventional filters often fail to enhance actual lesions. Our purpose in this study was to develop a supervised filter for the enhancement of actual lesions (as opposed to a lesion model) by use of a massive-training artificial neural network (MTANN) in a CAD scheme for detection of lung nodules in CT. The MTANN filter was trained with actual nodules in CT images to enhance actual patterns of nodules. By use of the MTANN filter, the sensitivity and specificity of our CAD scheme were improved substantially. With a database of 69 lung cancers, nodule candidate detection by the MTANN filter achieved a 97% sensitivity with 6.7 false positives (FPs) per section, whereas nodule candidate detection by a difference-image technique achieved a 96% sensitivity with 19.3 FPs per section. Classification-MTANNs were applied for further reduction of the FPs. The classification-MTANNs removed 60% of the FPs with a loss of one true positive; thus, it achieved a 96% sensitivity with 2.7 FPs per section. Overall, with our CAD scheme based on the MTANN filter and classification-MTANNs, an 84% sensitivity with 0.5 FPs per section was achieved.
Version control system of CAD documents and PLC projects
NASA Astrophysics Data System (ADS)
Khudyakov, P. Yu; Kisel’nikov, A. Yu; Startcev, I. M.; Kovalev, A. A.
2018-05-01
The paper presents the process of developing a version control system for CAD documents and PLC projects. The software was tested and the optimal composition of the modules was selected. The introduction of the system has made it possible to increase the safety and stability of the process control systems, as well as to reduce the number of conflicts for versions of CAD files. The number of incidents at the enterprise related to the use of incorrect versions of PLC projects is reduced to 0.
Alqahtani, Fawaz
2017-01-01
The purpose of this study was to determine the effect of two extraoral computer-aided design (CAD) and computer-aided manufacturing (CAM) systems, in comparison with conventional techniques, on the marginal fit of monolithic CAD/CAM lithium disilicate ceramic crowns. This is an in vitro interventional study. The study was carried out at the Department of Prosthodontics, School of Dentistry, Prince Sattam Bin Abdul-Aziz University, Saudi Arabia, from December 2015 to April 2016. A marginal gap of 60 lithium disilicate crowns was evaluated by scanning electron microscopy. In total, 20 pressable lithium disilicate (IPS e.max Press [Ivoclar Vivadent]) ceramic crowns were fabricated using the conventional lost-wax technique as a control group. The experimental all-ceramic crowns were produced based on a scan stone model and milled using two extraoral CAD/CAM systems: the Cerec group was fabricated using the Cerec CAD/CAM system, and the Trios group was fabricated using Trios CAD and milled using Wieland Zenotec CAM. One-way analysis of variance (ANOVA) and the Scheffe post hoc test were used for statistical comparison of the groups (α=0.05). The mean (±standard deviation) of the marginal gap of each group was as follows: the Control group was 91.15 (±15.35) µm, the Cerec group was 111.07 (±6.33) µm, and the Trios group was 60.17 (±11.09) µm. One-way ANOVA and the Scheffe post hoc test showed a statistically significant difference in the marginal gap between all groups. It can be concluded from the current study that all-ceramic crowns, fabricated using the CAD/CAM system, show a marginal accuracy that is acceptable in clinical environments. The Trios CAD group displayed the smallest marginal gap.
Min, James K; Shaw, Leslee J; Berman, Daniel S; Gilmore, Amanda; Kang, Ning
2008-09-15
Multidetector coronary computed tomographic angiography (CCTA) demonstrates high accuracy for the detection and exclusion of coronary artery disease (CAD) and predicts adverse prognosis. To date, opportunity costs relating the clinical and economic outcomes of CCTA compared with other methods of diagnosing CAD, such as myocardial perfusion single-photon emission computed tomography (SPECT), remain unknown. An observational, multicenter, patient-level analysis of patients without known CAD who underwent CCTA or SPECT was performed. Patients who underwent CCTA (n = 1,938) were matched to those who underwent SPECT (n = 7,752) on 8 demographic and clinical characteristics and 2 summary measures of cardiac medications and co-morbidities and were evaluated for 9-month expenditures and clinical outcomes. Adjusted total health care and CAD expenditures were 27% (p <0.001) and 33% (p <0.001) lower, respectively, for patients who underwent CCTA compared with those who underwent SPECT, by an average of $467 (95% confidence interval $99 to $984) for CAD expenditures per patient. Despite lower total health care expenditures for CCTA, no differences were observed for rates of adverse cardiovascular events, including CAD hospitalizations (4.2% vs 4.1%, p = NS), CAD outpatient visits (17.4% vs 13.3%, p = NS), myocardial infarction (0.4% vs 0.6%, p = NS), and new-onset angina (3.0% vs 3.5%, p = NS). Patients without known CAD who underwent CCTA, compared with matched patients who underwent SPECT, incurred lower overall health care and CAD expenditures while experiencing similarly low rates of CAD hospitalization, outpatient visits, myocardial infarction, and angina. In conclusion, these data suggest that CCTA may be a cost-efficient alternative to SPECT for the initial coronary evaluation of patients without known CAD.
Nossair, Shereen Ahmed; Aboushelib, Moustafa N; Morsi, Tarek Salah
2015-01-05
To evaluate the fracture mechanics of cemented versus fused CAD-on veneers on customized zirconia implant abutments. Forty-five identical customized CAD/CAM zirconia implant abutments (0.5 mm thick) were prepared and seated on short titanium implant abutments (Ti base). A second scan was made to fabricate 45 CAD-on veneers (IPS Empress CAD, A2). Fifteen CAD-on veneers were cemented on the zirconia abutments (Panavia F2.0). Another 15 were fused to the zirconia abutments using low-fusing glass, while manually layered veneers served as control (n = 15). The restorations were subjected to artificial aging (3.2 million cycles between 5 and 10 kg in a water bath at 37°C) before being axially loaded to failure. Fractured specimens were examined using scanning electron microscopy to detect fracture origin, location, and size of critical crack. Stress at failure was calculated using fractography principles (alpha = 0.05). Cemented CAD-on restorations demonstrated significantly higher (F = 72, p < 0.001) fracture load compared to fused CAD-on and manually layered restorations. Fractographic analysis of fractured specimens indicated that cemented CAD-on veneers failed due to radial cracks originating from the veneer/resin interface. Branching of the critical crack was observed in the bulk of the veneer. Fused CAD-on veneers demonstrated cohesive fracture originating at the thickest part of the veneer ceramic, while manually layered veneers failed due to interfacial fracture at the zirconia/veneer interface. Within the limitations of this study, cemented CAD-on veneers on customized zirconia implant abutments demonstrated higher fracture than fused and manually layered veneers. © 2014 by the American College of Prosthodontists.
Automated melanoma recognition in dermoscopic images based on extreme learning machine (ELM)
NASA Astrophysics Data System (ADS)
Rahman, Md. Mahmudur; Alpaslan, Nuh
2017-03-01
Melanoma is considered a major health problem since it is the deadliest form of skin cancer. The early diagnosis through periodic screening with dermoscopic images can significantly improve the survival rate as well as reduce the treatment cost and consequent suffering of patients. Dermoscopy or skin surface microscopy provides in vivo inspection of color and morphologic structures of pigmented skin lesions (PSLs), rendering higher accuracy for detecting suspicious cases than it is possible via inspecting with naked eye. However, interpretation of dermoscopic images is time consuming and subjective, even for trained dermatologists. Therefore, there is currently a great interest in the development of computeraided diagnosis (CAD) systems for automated melanoma recognition. However, the majority of the CAD systems are still in the early development stage with lack of descriptive feature generation and benchmark evaluation in ground-truth datasets. This work is focusing on by addressing the various issues related to the development of such a CAD system with effective feature extraction from Non-Subsampled Contourlet Transform (NSCT) and Eig(Hess) histogram of oriented gradients (HOG) and lesion classification with efficient Extreme Learning Machine (ELM) due to its good generalization abilities and a high learning efficiency and evaluating its effectiveness in a benchmark data set of dermoscopic images towards the goal of realistic comparison and real clinical integration. The proposed research on melanoma recognition has huge potential for offering powerful services that would significantly benefit the present Biomedical Information Systems.
Komeda, Yoriaki; Handa, Hisashi; Watanabe, Tomohiro; Nomura, Takanobu; Kitahashi, Misaki; Sakurai, Toshiharu; Okamoto, Ayana; Minami, Tomohiro; Kono, Masashi; Arizumi, Tadaaki; Takenaka, Mamoru; Hagiwara, Satoru; Matsui, Shigenaga; Nishida, Naoshi; Kashida, Hiroshi; Kudo, Masatoshi
2017-01-01
Computer-aided diagnosis (CAD) is becoming a next-generation tool for the diagnosis of human disease. CAD for colon polyps has been suggested as a particularly useful tool for trainee colonoscopists, as the use of a CAD system avoids the complications associated with endoscopic resections. In addition to conventional CAD, a convolutional neural network (CNN) system utilizing artificial intelligence (AI) has been developing rapidly over the past 5 years. We attempted to generate a unique CNN-CAD system with an AI function that studied endoscopic images extracted from movies obtained with colonoscopes used in routine examinations. Here, we report our preliminary results of this novel CNN-CAD system for the diagnosis of colon polyps. A total of 1,200 images from cases of colonoscopy performed between January 2010 and December 2016 at Kindai University Hospital were used. These images were extracted from the video of actual endoscopic examinations. Additional video images from 10 cases of unlearned processes were retrospectively assessed in a pilot study. They were simply diagnosed as either an adenomatous or nonadenomatous polyp. The number of images used by AI to learn to distinguish adenomatous from nonadenomatous was 1,200:600. These images were extracted from the videos of actual endoscopic examinations. The size of each image was adjusted to 256 × 256 pixels. A 10-hold cross-validation was carried out. The accuracy of the 10-hold cross-validation is 0.751, where the accuracy is the ratio of the number of correct answers over the number of all the answers produced by the CNN. The decisions by the CNN were correct in 7 of 10 cases. A CNN-CAD system using routine colonoscopy might be useful for the rapid diagnosis of colorectal polyp classification. Further prospective studies in an in vivo setting are required to confirm the effectiveness of a CNN-CAD system in routine colonoscopy. © 2017 S. Karger AG, Basel.
CAD/CAM approach to improving industry productivity gathers momentum
NASA Technical Reports Server (NTRS)
Fulton, R. E.
1982-01-01
Recent results and planning for the NASA/industry Integrated Programs for Aerospace-Vehicle Design (IPAD) program for improving productivity with CAD/CAM methods are outlined. The industrial group work is being mainly done by Boeing, and progress has been made in defining the designer work environment, developing requirements and a preliminary design for a future CAD/CAM system, and developing CAD/CAM technology. The work environment was defined by conducting a detailed study of a reference design process, and key software elements for a CAD/CAM system have been defined, specifically for interactive design or experiment control processes. Further work is proceeding on executive, data management, geometry and graphics, and general utility software, and dynamic aspects of the programs being developed are outlined
Papanastasiou, Giorgos; Williams, Michelle C; Dweck, Marc R; Alam, Shirjel; Cooper, Annette; Mirsadraee, Saeed; Newby, David E; Semple, Scott I
2016-09-13
Mathematical modeling of perfusion cardiovascular magnetic resonance (CMR) data allows absolute quantification of myocardial blood flow and can potentially improve the diagnosis and prognostication of obstructive coronary artery disease (CAD), against the current clinical standard of visual assessments. This study compares the diagnostic performance of distributed parameter modeling (DP) against the standard Fermi model, for the detection of obstructive CAD, in per vessel against per patient analysis. A pilot cohort of 28 subjects (24 included in the final analysis) with known or suspected CAD underwent adenosine stress-rest perfusion CMR at 3T. Data were analysed using Fermi and DP modeling against invasive coronary angiography and fractional flow reserve, acquired in all subjects. Obstructive CAD was defined as luminal stenosis of ≥70 % alone, or luminal stenosis ≥50 % and fractional flow reserve ≤0.80. On ROC analysis, DP modeling outperformed the standard Fermi model, in per vessel and per patient analysis. In per patient analysis, DP modeling-derived myocardial blood flow at stress demonstrated the highest sensitivity and specificity (0.96, 0.92) in detecting obstructive CAD, against Fermi modeling (0.78, 0.88) and visual assessments (0.79, 0.88), respectively. DP modeling demonstrated consistently increased diagnostic performance against Fermi modeling and showed that it may have merit for stratifying patients with at least one vessel with obstructive CAD. Clinicaltrials.gov NCT01368237 Registered 6 of June 2011. URL: https://clinicaltrials.gov/ct2/show/NCT01368237.
Vojdani, Mahroo; Torabi, Kianoosh; Atashkar, Berivan; Heidari, Hossein; Torabi Ardakani, Mahshid
2016-12-01
Marginal fitness is the most important criteria for evaluation of the clinical acceptability of a cast restoration. Marginal gap which is due to cement solubility and plaque retention is potentially detrimental to both tooth and periodontal tissues. This in vitro study aimed to evaluate the marginal and internal fit of cobalt- chromium (Co-Cr) copings fabricated by two different CAD/CAM systems: (CAD/ milling and CAD/ Ceramill Sintron). We prepared one machined standard stainless steel master model with following dimensions: 7 mm height, 5mm diameter, 90˚ shoulder marginal finish line with 1 mm width, 10˚ convergence angle and anti-rotational surface on the buccal aspect of the die. There were 10 copings produced from hard presintered Co-Cr blocks according to CAD/ Milling technique and ten copings from soft non- presintered Co-Cr blocks according to CAD/ Ceramill Sintron technique. Marginal and internal accuracies of copings were documented by the replica technique. Replicas were examined at ten reference points under a digital microscope (230X). The Student's t-test was used for statistical analysis. p < 0.001 was considered significant. Statistically significant differences existed between the groups ( p < 0.001). The CAD/milling group (hard copings) had a mean marginal discrepancy (MD) of 104 µm, axial discrepancy (AD) of 23 µm and occlusal discrepancy of 130 µm. For CAD/ Ceramill Sintron group, these values were 195 µm (MD), 46 µm (AD), and 232 µm (OD). Internal total discrepancy (ITD) for the CAD/milling group was 77 µm, whereas for the CAD/Ceramill Sintron group was 143 µm. Hard presintered Co-Cr copings had significantly higher marginal and internal accuracies compared to the soft non-presintered copings.
Ko, Dennis T; Tu, Jack V; Austin, Peter C; Wijeysundera, Harindra C; Samadashvili, Zaza; Guo, Helen; Cantor, Warren J; Hannan, Edward L
2013-07-10
Prior studies have shown that physicians in New York State (New York) perform twice as many cardiac catheterizations per capita as those in Ontario for stable patients. However, the role of patient selection in these findings and their implications for detection of obstructive coronary artery disease (CAD) are largely unknown. To evaluate the extent of obstructive CAD and to compare the probability of detecting obstructive CAD for patients undergoing cardiac catheterization. An observational study was conducted involving patients without a history of cardiac disease who underwent elective cardiac catheterization between October 1, 2008, and September 30, 2011. Obstructive CAD was defined as diameter stenosis of 50% or more in the left main coronary artery or stenosis of 70% or more in a major epicardial vessel. Observed rates and predicted probabilities of obstructive CAD. Predicted probabilities were estimated using logistic regression models. A total of 18,114 patients from New York and 54,933 from Ontario were included. The observed rate of obstructive CAD was significantly lower in New York at 30.4% (95% CI, 29.7%-31.0%) than in Ontario at 44.8% (95% CI, 44.4%-45.3%; P < .001). The percentage of patients with left main or 3-vessel CAD was also significantly lower in New York than in Ontario (7.0% [95% CI, 6.6%-7.3%] vs 13.0% [95% CI, 12.8%-13.3%]; P < .001). In New York, a substantially higher percentage of patients with low predicted probability of obstructive CAD underwent cardiac catheterization; for example, only 19.3% (95% CI, 18.7%-19.9%) of patients undergoing cardiac catheterization in New York had a greater than 50% predicted probability of having obstructive CAD than those in Ontario at 41% (95% CI, 40.6%-41.4%; P < .001). At 30 days, crude mortality for patients undergoing cardiac catheterization was slightly higher in New York at 0.65% (90 of 13,824; 95% CI, 0.51%-0.78%) than in Ontario at 0.38% (153 of 40,794; 95% CI, 0.32%-0.43%; P < .001). In Ontario compared with New York State, patients undergoing elective cardiac catheterization were significantly more likely to have obstructive CAD. This appears to be related to a higher percentage of patients in New York with low predicted probability of CAD undergoing cardiac catheterization.
Kerkeni, Mohsen; Addad, Faouzi; Chauffert, Maryline; Myara, Anne; Gerhardt, Marie; Chevenne, Didier; Trivin, François; Farhat, Mohamed Ben; Miled, Abdelhedi; Maaroufi, Khira
2006-05-01
Hyperhomocysteinaemia is an independent, graded risk factor for coronary artery disease (CAD). The methylenetetrahydrofolate reductase (MTHFR) polymorphism is associated with hyperhomcysteinaemia and may therefore influence individual susceptibility to CAD. We have investigated this risk factor in a Tunisian Arab population. Polymerase chain reaction-restriction fragment length polymorphism analysis was used to detect the C677T and A1298C variants of the MTHFR gene in 100 patients with CAD and 120 healthy controls. The severity of CAD was expressed as the number of affected vessels. Plasma total homocysteine (tHcy) concentration was determined using a direct chemiluminescence assay. MTHFR CC, CT and TT genotype frequencies in the CAD group were significantly different from those observed in the control group (49%, 35% and 16% versus 48.3%, 45.8% and 5.8%, respectively; P = 0.031). However, MTHFR AA, AC and CC genotypes frequencies in the CAD group were not significantly different from the control group ( P = 0.568). Patients with CAD showed higher plasma tHcy concentrations than patients without CAD (15.86 +/- 8.63 micromol/L versus 11.90 +/- 3.25 micromol/L, P < 0.001). There was no association between the MTHFR polymorphisms and the number of stenosed vessels. Patients with the MTHFR TT genotype had higher plasma tHcy, serum creatinine, cholesterol and triglyceride concentrations than patients with the MTHFR CC genotype. The C677T polymorphism of the MTHFR gene is associated with hyperhomocysteinaemia, lipid dysregulation and the presence of CAD in this Tunisian Arab population.
Jia, Lixin; Fan, Jingyao; Cui, Wei; Liu, Sa; Li, Na; Lau, Wayne Bond; Ma, Xinliang; Du, Jie; Nie, Shaoping; Wei, Yongxiang
2017-01-01
Obstructive sleep apnea hypoxia syndrome (OSAHS) is an independent risk factor for coronary artery disease (CAD). Treatment of OSAHS improves clinical outcome in some CAD patients, but the relationship between OSAHS and CAD is complex. Microparticles (MPs) are shed by the plasma membrane by either physiologic or pathologic stimulation. In the current study, we investigated the role of MPs in the context of OSAHS. 54 patients with both suspected coronary artery stenosis and OSAHS were recruited and underwent both coronary arteriography and polysomnography. Circulating MPs were isolated and analyzed by flow cytometry. CAD+OSAHS patients exhibited greater levels of total MPs (Annexin V+), erythrocyte-derived MPs (CD235+ Annexin V+), platelet-derived MPs (CD41+ Annexin V+), and leukocyte-derived MPs (CD45+ Annexin V+) compared to CAD alone patients or control. CAD+OSAHS patients expressed the greatest level of endothelial-derived MPs of all cellular origin types (CD144+ Annexin V +). Treatment of human aortic endothelial cells (HAECs) with MPs isolated from CAD+OSAHS patients markedly increased HAEC permeability (as detected by FITC-dextran), and significantly upregulated mRNA levels of ICAM-1, VCAM-1, and MCP-1. OSAHS+CAD patients harbor increased levels of MPs, particularly the endothelial cell-derived subtype. When administered to HAECs, OSAHS+CAD patients MPs increase endothelial cell permeability and dysfunction. © 2017 The Author(s). Published by S. Karger AG, Basel.
NASA Astrophysics Data System (ADS)
Chen, Shaobin; Zhang, Xubo; Wang, Wenyuan; Zhou, Chengping; Ding, Mingyue
2007-11-01
Nowadays many Geographic Information System (GIS) have been widely used in many municipal corporations. Water-supplying corporations in many cities developed GIS application system based on SiCAD/Open GIS platform several years ago for their daily management and engineering construction. With the increasing of commercial business, many corporations now need to add the functionality of three dimensional to display to their GIS System without too much financial cost. Because of the expensiveness of updating SiCAD/Open GIS system to the up-to-date version, the introduction of a third-part 3D display technology is considered. In our solution, Visualization Toolkit (VTK) is used to achieve three dimensional display of underground water-supplying network on the basis of an existing SiCAD/Open GIS system. This paper addresses on the system architecture and key implementation technologies of this solution.
Large scale validation of the M5L lung CAD on heterogeneous CT datasets.
Torres, E Lopez; Fiorina, E; Pennazio, F; Peroni, C; Saletta, M; Camarlinghi, N; Fantacci, M E; Cerello, P
2015-04-01
M5L, a fully automated computer-aided detection (CAD) system for the detection and segmentation of lung nodules in thoracic computed tomography (CT), is presented and validated on several image datasets. M5L is the combination of two independent subsystems, based on the Channeler Ant Model as a segmentation tool [lung channeler ant model (lungCAM)] and on the voxel-based neural approach. The lungCAM was upgraded with a scan equalization module and a new procedure to recover the nodules connected to other lung structures; its classification module, which makes use of a feed-forward neural network, is based of a small number of features (13), so as to minimize the risk of lacking generalization, which could be possible given the large difference between the size of the training and testing datasets, which contain 94 and 1019 CTs, respectively. The lungCAM (standalone) and M5L (combined) performance was extensively tested on 1043 CT scans from three independent datasets, including a detailed analysis of the full Lung Image Database Consortium/Image Database Resource Initiative database, which is not yet found in literature. The lungCAM and M5L performance is consistent across the databases, with a sensitivity of about 70% and 80%, respectively, at eight false positive findings per scan, despite the variable annotation criteria and acquisition and reconstruction conditions. A reduced sensitivity is found for subtle nodules and ground glass opacities (GGO) structures. A comparison with other CAD systems is also presented. The M5L performance on a large and heterogeneous dataset is stable and satisfactory, although the development of a dedicated module for GGOs detection could further improve it, as well as an iterative optimization of the training procedure. The main aim of the present study was accomplished: M5L results do not deteriorate when increasing the dataset size, making it a candidate for supporting radiologists on large scale screenings and clinical programs.
Integrated computer-aided design using minicomputers
NASA Technical Reports Server (NTRS)
Storaasli, O. O.
1980-01-01
Computer-Aided Design/Computer-Aided Manufacturing (CAD/CAM), a highly interactive software, has been implemented on minicomputers at the NASA Langley Research Center. CAD/CAM software integrates many formerly fragmented programs and procedures into one cohesive system; it also includes finite element modeling and analysis, and has been interfaced via a computer network to a relational data base management system and offline plotting devices on mainframe computers. The CAD/CAM software system requires interactive graphics terminals operating at a minimum of 4800 bits/sec transfer rate to a computer. The system is portable and introduces 'interactive graphics', which permits the creation and modification of models interactively. The CAD/CAM system has already produced designs for a large area space platform, a national transonic facility fan blade, and a laminar flow control wind tunnel model. Besides the design/drafting element analysis capability, CAD/CAM provides options to produce an automatic program tooling code to drive a numerically controlled (N/C) machine. Reductions in time for design, engineering, drawing, finite element modeling, and N/C machining will benefit productivity through reduced costs, fewer errors, and a wider range of configuration.
Computer-aided detection of early cancer in the esophagus using HD endoscopy images
NASA Astrophysics Data System (ADS)
van der Sommen, Fons; Zinger, Svitlana; Schoon, Erik J.; de With, Peter H. N.
2013-02-01
Esophageal cancer is the fastest rising type of cancer in the Western world. The recent development of High-Definition (HD) endoscopy has enabled the specialist physician to identify cancer at an early stage. Nevertheless, it still requires considerable effort and training to be able to recognize these irregularities associated with early cancer. As a first step towards a Computer-Aided Detection (CAD) system that supports the physician in finding these early stages of cancer, we propose an algorithm that is able to identify irregularities in the esophagus automatically, based on HD endoscopic images. The concept employs tile-based processing, so our system is not only able to identify that an endoscopic image contains early cancer, but it can also locate it. The identification is based on the following steps: (1) preprocessing, (2) feature extraction with dimensionality reduction, (3) classification. We evaluate the detection performance in RGB, HSI and YCbCr color space using the Color Histogram (CH) and Gabor features and we compare with other well-known features to describe texture. For classification, we employ a Support Vector Machine (SVM) and evaluate its performance using different parameters and kernel functions. In experiments, our system achieves a classification accuracy of 95.9% on 50×50 pixel tiles of tumorous and normal tissue and reaches an Area Under the Curve (AUC) of 0.990. In 22 clinical examples our algorithm was able to identify all (pre-)cancerous regions and annotate those regions reasonably well. The experimental and clinical validation are considered promising for a CAD system that supports the physician in finding early stage cancer.
Pulmonary nodule detection using a cascaded SVM classifier
NASA Astrophysics Data System (ADS)
Bergtholdt, Martin; Wiemker, Rafael; Klinder, Tobias
2016-03-01
Automatic detection of lung nodules from chest CT has been researched intensively over the last decades resulting also in several commercial products. However, solutions are adopted only slowly into daily clinical routine as many current CAD systems still potentially miss true nodules while at the same time generating too many false positives (FP). While many earlier approaches had to rely on rather few cases for development, larger databases become now available and can be used for algorithmic development. In this paper, we address the problem of lung nodule detection via a cascaded SVM classifier. The idea is to sequentially perform two classification tasks in order to select from an extremely large pool of potential candidates the few most likely ones. As the initial pool is allowed to contain thousands of candidates, very loose criteria could be applied during this pre-selection. In this way, the chances that a true nodule is falsely rejected as a candidate are reduced significantly. The final algorithm is trained and tested on the full LIDC/IDRI database. Comparison is done against two previously published CAD systems. Overall, the algorithm achieved sensitivity of 0.859 at 2.5 FP/volume where the other two achieved sensitivity values of 0.321 and 0.625, respectively. On low dose data sets, only slight increase in the number of FP/volume was observed, while the sensitivity was not affected.
Du, Guo-Qing; Xue, Jing-Yi; Guo, Yanhui; Chen, Shuang; Du, Pei; Wu, Yan; Wang, Yu-Hang; Zong, Li-Qiu; Tian, Jia-Wei
2015-09-01
Proper evaluation of myocardial microvascular perfusion and assessment of infarct size is critical for clinicians. We have developed a novel computer-aided diagnosis (CAD) approach for myocardial contrast echocardiography (MCE) to measure myocardial perfusion and infarct size. Rabbits underwent 15 min of coronary occlusion followed by reperfusion (group I, n = 15) or 60 min of coronary occlusion followed by reperfusion (group II, n = 15). Myocardial contrast echocardiography was performed before and 7 d after ischemia/reperfusion, and images were analyzed with the CAD system on the basis of eliminating particle swarm optimization clustering analysis. The myocardium was quickly and accurately detected using contrast-enhanced images, myocardial perfusion was quantitatively calibrated and a color-coded map calibrated by contrast intensity and automatically produced by the CAD system was used to outline the infarction region. Calibrated contrast intensity was significantly lower in infarct regions than in non-infarct regions, allowing differentiation of abnormal and normal myocardial perfusion. Receiver operating characteristic curve analysis documented that -54-pixel contrast intensity was an optimal cutoff point for the identification of infarcted myocardium with a sensitivity of 95.45% and specificity of 87.50%. Infarct sizes obtained using myocardial perfusion defect analysis of original contrast images and the contrast intensity-based color-coded map in computerized images were compared with infarct sizes measured using triphenyltetrazolium chloride staining. Use of the proposed CAD approach provided observers with more information. The infarct sizes obtained with myocardial perfusion defect analysis, the contrast intensity-based color-coded map and triphenyltetrazolium chloride staining were 23.72 ± 8.41%, 21.77 ± 7.8% and 18.21 ± 4.40% (% left ventricle) respectively (p > 0.05), indicating that computerized myocardial contrast echocardiography can accurately measure infarct size. On the basis of the results, we believe the CAD method can quickly and automatically measure myocardial perfusion and infarct size and will, it is hoped, be very helpful in clinical therapeutics. Copyright © 2015 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.
Nakao, Kazuhiro; Noguchi, Teruo; Asaumi, Yasuhide; Morita, Yoshiaki; Kanaya, Tomoaki; Fujino, Masashi; Hosoda, Hayato; Yoneda, Shuichi; Kawakami, Shoji; Nagai, Toshiyuki; Nishihira, Kensaku; Nakashima, Takahiro; Kumasaka, Reon; Arakawa, Tetsuo; Otsuka, Fumiyuki; Nakanishi, Michio; Kataoka, Yu; Tahara, Yoshio; Goto, Yoichi; Yamamoto, Haruko; Hamasaki, Toshimitsu; Yasuda, Satoshi
2018-01-08
Despite the success of HMG-CoA reductase inhibitor (statin) therapy in reducing atherosclerotic cardiovascular events, a residual risk for cardiovascular events in patients with coronary artery disease (CAD) remains. Long-chain n-3 polyunsaturated fatty acids (LC n-3 PUFAs), especially eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA), are promising anti-atherosclerosis agents that might reduce the residual CAD risk. Non-contrast T1-weighted imaging (T1WI) with cardiac magnetic resonance (CMR) less invasively identifies high-risk coronary plaques as high-intensity signals. These high-intensity plaques (HIPs) are quantitatively assessed using the plaque-to-myocardium signal intensity ratio (PMR). Our goal is to assess the effect of EPA/DHA on coronary HIPs detected with T1WI in patients with CAD on statin treatment. This prospective, controlled, randomized, open-label study examines the effect of 12 months of EPA/DHA therapy and statin treatment on PMR of HIPs detected with CMR and computed tomography angiography (CTA) in patients with CAD. The primary endpoint is the change in PMR after EPA/DHA treatment. Secondary endpoints include changes in Hounsfield units, plaque volume, vessel area, and plaque area measured using CTA. Subjects are randomly assigned to either of three groups: the 2 g/day EPA/DHA group, the 4 g/day EPA/DHA group, or the no-treatment group. This trial will help assess whether EPA/DHA has an anti-atherosclerotic effect using PMR of HIPs detected by CMR. The trial outcomes will provide novel insights into the effect of EPA/DHA on high-risk coronary plaques and may provide new strategies for lowering the residual risk in patients with CAD on statin therapy. The University Hospital Medical Information Network (UMIN) Clinical Trials Registry, ID: UMIN000015316 . Registered on 2 October 2014.
Computing Mass Properties From AutoCAD
NASA Technical Reports Server (NTRS)
Jones, A.
1990-01-01
Mass properties of structures computed from data in drawings. AutoCAD to Mass Properties (ACTOMP) computer program developed to facilitate quick calculations of mass properties of structures containing many simple elements in such complex configurations as trusses or sheet-metal containers. Mathematically modeled in AutoCAD or compatible computer-aided design (CAD) system in minutes by use of three-dimensional elements. Written in Microsoft Quick-Basic (Version 2.0).
Liou, Kevin; Negishi, Kazuaki; Ho, Suyen; Russell, Elizabeth A; Cranney, Greg; Ooi, Sze-Yuan
2016-08-01
Global longitudinal strain (GLS) is well validated and has important applications in contemporary clinical practice. The aim of this analysis was to evaluate the accuracy of resting peak GLS in the diagnosis of obstructive coronary artery disease (CAD). A systematic literature search was performed through July 2015 using four databases. Data were extracted independently by two authors and correlated before analyses. Using a random-effect model, the pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio, and summary area under the curve for GLS were estimated with their respective 95% CIs. Screening of 1,669 articles yielded 10 studies with 1,385 patients appropriate for inclusion in the analysis. The mean age and left ventricular ejection fraction were 59.9 years and 61.1%. On the whole, 54.9% and 20.9% of the patients had hypertension and diabetes, respectively. Overall, abnormal GLS detected moderate to severe CAD with a pooled sensitivity, specificity, positive likelihood ratio, and negative likelihood ratio of 74.4%, 72.1%, 2.9, and 0.35 respectively. The area under the curve and diagnostic odds ratio were 0.81 and 8.5. The mean values of GLS for those with and without CAD were -16.5% (95% CI, -15.8% to -17.3%) and -19.7% (95% CI, -18.8% to -20.7%), respectively. Subgroup analyses for patients with severe CAD and normal left ventricular ejection fractions yielded similar results. Current evidence supports the use of GLS in the detection of moderate to severe obstructive CAD in symptomatic patients. GLS may complement existing diagnostic algorithms and act as an early adjunctive marker of cardiac ischemia. Crown Copyright © 2016. Published by Elsevier Inc. All rights reserved.
NASA Astrophysics Data System (ADS)
Aghaei, Faranak; Ross, Stephen R.; Wang, Yunzhi; Wu, Dee H.; Cornwell, Benjamin O.; Ray, Bappaditya; Zheng, Bin
2017-03-01
Aneurysmal subarachnoid hemorrhage (aSAH) is a form of hemorrhagic stroke that affects middle-aged individuals and associated with significant morbidity and/or mortality especially those presenting with higher clinical and radiologic grades at the time of admission. Previous studies suggested that blood extravasated after aneurysmal rupture was a potentially clinical prognosis factor. But all such studies used qualitative scales to predict prognosis. The purpose of this study is to develop and test a new interactive computer-aided detection (CAD) tool to detect, segment and quantify brain hemorrhage and ventricular cerebrospinal fluid on non-contrasted brain CT images. First, CAD segments brain skull using a multilayer region growing algorithm with adaptively adjusted thresholds. Second, CAD assigns pixels inside the segmented brain region into one of three classes namely, normal brain tissue, blood and fluid. Third, to avoid "black-box" approach and increase accuracy in quantification of these two image markers using CT images with large noise variation in different cases, a graphic User Interface (GUI) was implemented and allows users to visually examine segmentation results. If a user likes to correct any errors (i.e., deleting clinically irrelevant blood or fluid regions, or fill in the holes inside the relevant blood or fluid regions), he/she can manually define the region and select a corresponding correction function. CAD will automatically perform correction and update the computed data. The new CAD tool is now being used in clinical and research settings to estimate various quantitatively radiological parameters/markers to determine radiological severity of aSAH at presentation and correlate the estimations with various homeostatic/metabolic derangements and predict clinical outcome.
Jribi, Hela; Sellami, Hanen; Hassena, Amal Ben; Gdoura, Radhouane
2017-10-01
Campylobacter and Arcobacter spp. are common causes of gastroenteritis in humans; these infections are commonly due to undercooked poultry. However, their virulence mechanism is still poorly understood. The aim of this study was to evaluate the presence of genotypic virulence markers in Campylobacter and Arcobacter species using PCR. The prevalence of virulence and cytolethal distending toxin (CDT) genes was estimated in 71 Campylobacteraceae isolates. PCR was used to detect the presence of virulence genes (iam, cadF, virB1, flaA, cdtA, cdtB, and cdtC) using specific primers for a total of 45 Campylobacter isolates, including 37 C. jejuni and 8 C. coli. All the Campylobacter isolates were positive for the cadF gene. The plasmid gene virB11 was not detected in any strain. The invasion associated marker was not detected in C. jejuni. Lower detection rates were observed for flaA, cdtA, cdtB, and cdtC. The presence of nine putative Arcobacter virulence genes (cadF, ciaB, cj1349, mviN, pldA, tlyA, irgA, hecA, and hecB) was checked in a set of 22 Arcobacter butzleri and 4 Arcobacter cryaerophilus isolates. The pldA and mviN genes were predominant (88.64%). Lower detection rates were observed for tlyA (84.76%), ciaB (84.61%), cadF and cj1349 (76.92%), IrgA and hecA (61.53%), and hecB (57.69%). The findings revealed that a majority of the Campylobacteraceae strains have these putative virulence genes that may lead to pathogenic effects in humans.
Local pulmonary structure classification for computer-aided nodule detection
NASA Astrophysics Data System (ADS)
Bahlmann, Claus; Li, Xianlin; Okada, Kazunori
2006-03-01
We propose a new method of classifying the local structure types, such as nodules, vessels, and junctions, in thoracic CT scans. This classification is important in the context of computer aided detection (CAD) of lung nodules. The proposed method can be used as a post-process component of any lung CAD system. In such a scenario, the classification results provide an effective means of removing false positives caused by vessels and junctions thus improving overall performance. As main advantage, the proposed solution transforms the complex problem of classifying various 3D topological structures into much simpler 2D data clustering problem, to which more generic and flexible solutions are available in literature, and which is better suited for visualization. Given a nodule candidate, first, our solution robustly fits an anisotropic Gaussian to the data. The resulting Gaussian center and spread parameters are used to affine-normalize the data domain so as to warp the fitted anisotropic ellipsoid into a fixed-size isotropic sphere. We propose an automatic method to extract a 3D spherical manifold, containing the appropriate bounding surface of the target structure. Scale selection is performed by a data driven entropy minimization approach. The manifold is analyzed for high intensity clusters, corresponding to protruding structures. Techniques involve EMclustering with automatic mode number estimation, directional statistics, and hierarchical clustering with a modified Bhattacharyya distance. The estimated number of high intensity clusters explicitly determines the type of pulmonary structures: nodule (0), attached nodule (1), vessel (2), junction (>3). We show accurate classification results for selected examples in thoracic CT scans. This local procedure is more flexible and efficient than current state of the art and will help to improve the accuracy of general lung CAD systems.
KHATAMI, Mehri; HEIDARI, Mohammad Mehdi; HADADZADEH, Mehdi; SCHEIBER-MOJDEHKAR, Barbara; BITARAF SANI, Morteza; HOUSHMAND, Massoud
2017-01-01
Background: A significant role of Renin-angiotensin system (RAS) genetic variants in the pathogenesis of essential hypertension and cardiovascular diseases has been proved. This study aimed to develop a new, fast and cheap method for the simultaneous detection of two missense single nucleotide polymorphisms (T207M or rs4762 and M268T orrs699) of angiotensinogen (AGT) in single-step Multiplex Hexa-Primer Amplification Refractory Mutation System - polymerase chain reaction (H-ARMS-PCR). Methods: In this case-control study, 148 patients with coronary artery disease (CAD) and 135 controls were included. The patients were referred to cardiac centers in Afshar Hospital (Yazd, Iran) from 2012 to 2015. Two sets of inner primer (for each SNP) and one set outer primer pairs were designed for genotyping of rs4762 and rs699 in single tube H-ARMS-PCR. Direct sequencing of all samples was also performed to assess the accuracy of this method. DNA sequencing method validated the results of single tube H-ARMS-PCR. Results: We found full accordance for genotype adscription by sequencing method. The frequency of the AGT T521 and C702 alleles was significantly higher in CAD patients than in the control group (OR: 0.551, 95% CI: 0.359–0.846, P=0.008 and OR: 0.629, 95% CI: 0.422–0.936, P=0.028, respectively). Conclusion: This is the first work describing a rapid, low-cost, high-throughput simultaneous detection of rs4762 and rs699 polymorphisms in AGT gene, used in large clinical studies. PMID:28828324
Application of computer-aided dispatch in law enforcement: An introductory planning guide
NASA Technical Reports Server (NTRS)
Sohn, R. L.; Gurfield, R. M.; Garcia, E. A.; Fielding, J. E.
1975-01-01
A set of planning guidelines for the application of computer-aided dispatching (CAD) to law enforcement is presented. Some essential characteristics and applications of CAD are outlined; the results of a survey of systems in the operational or planning phases are summarized. Requirements analysis, system concept design, implementation planning, and performance and cost modeling are described and demonstrated with numerous examples. Detailed descriptions of typical law enforcement CAD systems, and a list of vendor sources, are given in appendixes.
TopoCad - A unified system for geospatial data and services
NASA Astrophysics Data System (ADS)
Felus, Y. A.; Sagi, Y.; Regev, R.; Keinan, E.
2013-10-01
"E-government" is a leading trend in public sector activities in recent years. The Survey of Israel set as a vision to provide all of its services and datasets online. The TopoCad system is the latest software tool developed in order to unify a number of services and databases into one on-line and user friendly system. The TopoCad system is based on Web 1.0 technology; hence the customer is only a consumer of data. All data and services are accessible for the surveyors and geo-information professional in an easy and comfortable way. The future lies in Web 2.0 and Web 3.0 technologies through which professionals can upload their own data for quality control and future assimilation with the national database. A key issue in the development of this complex system was to implement a simple and easy (comfortable) user experience (UX). The user interface employs natural language dialog box in order to understand the user requirements. The system then links spatial data with alpha-numeric data in a flawless manner. The operation of the TopoCad requires no user guide or training. It is intuitive and self-taught. The system utilizes semantic engines and machine understanding technologies to link records from diverse databases in a meaningful way. Thus, the next generation of TopoCad will include five main modules: users and projects information, coordinates transformations and calculations services, geospatial data quality control, linking governmental systems and databases, smart forms and applications. The article describes the first stage of the TopoCad system and gives an overview of its future development.
NASA Astrophysics Data System (ADS)
Mori, Shintaro; Hara, Takeshi; Tagami, Motoki; Muramatsu, Chicako; Kaneda, Takashi; Katsumata, Akitoshi; Fujita, Hiroshi
2013-02-01
Inflammation in paranasal sinus sometimes becomes chronic to take long terms for the treatment. The finding is important for the early treatment, but general dentists may not recognize the findings because they focus on teeth treatments. The purpose of this study was to develop a computer-aided detection (CAD) system for the inflammation in paranasal sinus on dental panoramic radiographs (DPRs) by using the mandible contour and to demonstrate the potential usefulness of the CAD system by means of receiver operating characteristic analysis. The detection scheme consists of 3 steps: 1) Contour extraction of mandible, 2) Contralateral subtraction, and 3) Automated detection. The Canny operator and active contour model were applied to extract the edge at the first step. At the subtraction step, the right region of the extracted contour image was flipped to compare with the left region. Mutual information between two selected regions was obtained to estimate the shift parameters of image registration. The subtraction images were generated based on the shift parameter. Rectangle regions of left and right paranasal sinus on the subtraction image were determined based on the size of mandible. The abnormal side of the regions was determined by taking the difference between the averages of each region. Thirteen readers were responded to all cases without and with the automated results. The averaged AUC of all readers was increased from 0.69 to 0.73 with statistical significance (p=0.032) when the automated detection results were provided. In conclusion, the automated detection method based on contralateral subtraction technique improves readers' interpretation performance of inflammation in paranasal sinus on DPRs.
Bybee, Kevin A; Lee, John; Markiewicz, Richard; Longmore, Ryan; McGhie, A Iain; O'Keefe, James H; Hsu, Bai-Ling; Kennedy, Kevin; Thompson, Randall C; Bateman, Timothy M
2010-04-01
A limitation of stress myocardial perfusion imaging (MPI) is the inability to detect non-obstructive coronary artery disease (CAD). One advantage of MPI with a hybrid CT device is the ability to obtain same-setting measurement of the coronary artery calcium score (CACS). Utilizing our single-center nuclear database, we identified 760 consecutive patients with: (1) no CAD history; (2) a normal clinically indicated Rb-82 PET/CT stress perfusion study; and (3) a same-setting CAC scan. 487 of 760 patients (64.1%) had subclinical CAD based on an abnormal CACS. Of those with CAC, the CACS was > or =100, > or =400, and > or =1000 in 47.0%, 22.4%, and 8.4% of patients, respectively. Less than half of the patients with CAC were receiving aspirin or statin medications prior to PET/CT imaging. Patients with CAC were more likely to be initiated or optimized on proven medical therapy for CAD immediately following PET/CT MPI compared to those without CAC. Subclinical CAD is common in patients without known CAD and normal myocardial perfusion assessed by hybrid PET/CT imaging. Identification of CAC influences subsequent physician prescribing patterns such that those with CAC are more likely to be treated with proven medical therapy for the treatment of CAD.
Baucher, M.; Chabbert, B.; Pilate, G.; Van Doorsselaere, J.; Tollier, M. T.; Petit-Conil, M.; Cornu, D.; Monties, B.; Van Montagu, M.; Inze, D.; Jouanin, L.; Boerjan, W.
1996-12-01
Cinnamyl alcohol dehydrogenase (CAD) catalyzes the last step in the biosynthesis of the lignin precursors, the monolignols. We have down-regulated CAD in transgenic poplar (Populus tremula X Populus alba) by both antisense and co-suppression strategies. Several antisense and sense CAD transgenic poplars had an approximately 70% reduced CAD activity that was associated with a red coloration of the xylem tissue. Neither the lignin amount nor the lignin monomeric composition (syringyl/guaiacyl) were significantly modified. However, phloroglucinol-HCl staining was different in the down-regulated CAD plants, suggesting changes in the number of aldehyde units in the lignin. Furthermore, the reactivity of the cell wall toward alkali treatment was altered: a lower amount of lignin was found in the insoluble, saponified residue and more lignin could be precipitated from the soluble alkali fraction. Moreover, large amounts of phenolic compounds, vanillin and especially syringaldehyde, were detected in the soluble alkali fraction of the CAD down-regulated poplars. Alkaline pulping experiments on 3-month-old trees showed a reduction of the kappa number without affecting the degree of cellulose degradation. These results indicate that reducing the CAD activity in trees might be a valuable strategy to optimize certain processes of the wood industry, especially those of the pulp and paper industry.
Sekhar, M Soma; Tumati, S R; Chinnam, B K; Kothapalli, V S; Sharif, N Mohammad
2017-06-01
This study aimed to detect putative virulence genes in Arcobacter species of animal and human origin. A total of 41 Arcobacter isolates (16 Arcobacter butzleri , 13 Arcobacter cryaerophilus , and 12 Arcobacter skirrowii ) isolated from diverse sources such as fecal swabs of livestock (21), raw foods of animal origin (13), and human stool samples (7) were subjected to a set of six uniplex polymerase chain reaction assays targeting Arcobacter putative virulence genes ( ciaB , pldA , tlyA , mviN , cadF , and cj1349 ). All the six virulence genes were detected among all the 16 A. butzleri isolates. Among the 13 A. cryaerophilus isolates, cadF, ciaB , cj1349, mviN , pldA , and tlyA genes were detected in 61.5, 84.6, 76.9, 76.9, 61.5, and 61.5% of isolates, respectively. Among the 12 A. skirrowii isolates, cadF, ciaB , cj1349, mviN , pldA , and tlyA genes were detected in 50.0, 91.6, 83.3, 66.6, 50, and 50% of isolates, respectively. Putative virulence genes were detected in majority of the Arcobacter isolates examined. The results signify the potential of Arcobacter species as an emerging foodborne pathogen.
Different CAD/CAM-processing routes for zirconia restorations: influence on fitting accuracy.
Kohorst, Philipp; Junghanns, Janet; Dittmer, Marc P; Borchers, Lothar; Stiesch, Meike
2011-08-01
The aim of the present in vitro study was to evaluate the influence of different processing routes on the fitting accuracy of four-unit zirconia fixed dental prostheses (FDPs) fabricated by computer-aided design/computer-aided manufacturing (CAD/CAM). Three groups of zirconia frameworks with ten specimens each were fabricated. Frameworks of one group (CerconCAM) were produced by means of a laboratory CAM-only system. The other frameworks were made with different CAD/CAM systems; on the one hand by in-laboratory production (CerconCAD/CAM) and on the other hand by centralized production in a milling center (Compartis) after forwarding geometrical data. Frameworks were then veneered with the recommended ceramics, and marginal accuracy was determined using a replica technique. Horizontal marginal discrepancy, vertical marginal discrepancy, absolute marginal discrepancy, and marginal gap were evaluated. Statistical analyses were performed by one-way analysis of variance (ANOVA), with the level of significance chosen at 0.05. Mean horizontal discrepancies ranged between 22 μm (CerconCAM) and 58 μm (Compartis), vertical discrepancies ranged between 63 μm (CerconCAD/CAM) and 162 μm (CerconCAM), and absolute marginal discrepancies ranged between 94 μm (CerconCAD/CAM) and 181 μm (CerconCAM). The marginal gap varied between 72 μm (CerconCAD/CAM) and 112 μm (CerconCAM, Compartis). Statistical analysis revealed that, with all measurements, the marginal accuracy of the zirconia FDPs was significantly influenced by the processing route used (p < 0.05). Within the limitations of this study, all restorations showed a clinically acceptable marginal accuracy; however, the results suggest that the CAD/CAM systems are more precise than the CAM-only system for the manufacture of four-unit FDPs.
Cebe, Fatma; Aktan, Ali Murat; Ozsevik, Abdul Semih; Ciftci, Mehmet Ertugrul; Surmelioglu, Hatice Derya
2017-03-01
The aim of this study was to investigate the influence of artifacts produced by different restorative materials on the detection of approximal caries in cone-beam computed tomography (CBCT) scans with and without the application of an artifact-reduction (AR) option. Ninety-eight noncavitated premolar and molar teeth were placed with approximal contacts consisting of 2 sound or carious teeth and 1 mesial-occlusal-distal restored tooth with resin-modified glass-ionomer cement (RMGIC), amalgam, composite, ceramic-based composite (CBC), or computer-aided design-computer-aided manufacturing (CAD-CAM) zirconia materials in between. The teeth were scanned with a CBCT system with and without the AR option. Images were evaluated by 2 observers. The teeth were histologically evaluated, and sensitivity, specificity, and areas under the receiver operating characteristic (ROC) curve were calculated according to the appropriate threshold. Specificity and sensitivity values for contact surfaces ranged from 0-48.39 and 82.93-98.40, respectively. The AR option affected (P < .05) approximal caries detection of the amalgam, composite, CAD-CAM, and CBC groups in contact surfaces and composite and RMGIC groups in noncontact surfaces. Artifacts produced by different restorative materials could affect approximal caries detection in CBCT scans. Use of the AR option with CBCT scans increases the accuracy of approximal caries detection. Copyright © 2016 Elsevier Inc. All rights reserved.
2010-01-01
Background Cinnamyl Alcohol Dehydrogenase (CAD) proteins function in lignin biosynthesis and play a critical role in wood development and plant defense against stresses. Previous phylogenetic studies did not include genes from seedless plants and did not reflect the deep evolutionary history of this gene family. We reanalyzed the phylogeny of CAD and CAD-like genes using a representative dataset including lycophyte and bryophyte sequences. Many CAD/CAD-like genes do not seem to be associated with wood development under normal growth conditions. To gain insight into the functional evolution of CAD/CAD-like genes, we analyzed their expression in Populus plant tissues in response to feeding damage by gypsy moth larvae (Lymantria dispar L.). Expression of CAD/CAD-like genes in Populus tissues (xylem, leaves, and barks) was analyzed in herbivore-treated and non-treated plants by real time quantitative RT-PCR. Results CAD family genes were distributed in three classes based on sequence conservation. All the three classes are represented by seedless as well as seed plants, including the class of bona fide lignin pathway genes. The expression of some CAD/CAD-like genes that are not associated with xylem development were induced following herbivore damage in leaves, while other genes were induced in only bark or xylem tissues. Five of the CAD/CAD-like genes, however, showed a shift in expression from one tissue to another between non-treated and herbivore-treated plants. Systemic expression of the CAD/CAD-like genes was generally suppressed. Conclusions Our results indicated a correlation between the evolution of the CAD gene family and lignin and that the three classes of genes may have evolved in the ancestor of land plants. Our results also suggest that the CAD/CAD-like genes have evolved a diversity of expression profiles and potentially different functions, but that they are nonetheless co-regulated under stress conditions. PMID:20509918
Hou, Zhi-hui; Lu, Bin; Gao, Yang; Yu, Fang-fang; Cao, Hui-li; Jiang, Shi-liang; Roy, Sion K; Budoff, Matthew J
2012-11-01
To document the prevalence of coronary artery disease (CAD) and major adverse cardiac events (MACE) in patients younger than 45 years of age with intermediate pretest likelihood of CAD, and to determine whether coronary computed tomography angiography (cCTA) is useful for risk stratification of this cohort. We followed 452 intermediate pretest likelihood (according to Diamond and Forrester) outpatients who were suspected of CAD and underwent cCTA. They were all younger than 45 years old. The endpoint was MACE, defined as composite cardiac death, nonfatal myocardial infarction, or coronary revascularization. Follow-up was completed in 427 patients (94.5%) with a median follow-up period of 1081 days. No plaque was noted in 357 (83.6%) patients. Nonsignificant CAD was noted in 33 (7.7%) individuals and 37 (8.7%) patients with significant CAD. At the end of the follow-up period, 12 (2.8%) patients experienced MACE. The annualized event rate was 0.2% in patients with no plaque, 2.0% in patients with nonsignificant CAD, and 7.3% in patients with significant CAD. Hypertension, smoking, and significant CAD in cCTA were significant predictors of MACE in univariate analysis. Moreover, cCTA remained a predictor (P < .001) of events after multivariate correction (hazard ratio: 8.345, 95% CI: 3.438-17.823, P < .001). The prevalence of CAD and MACE in young adults with an intermediate pretest likelihood of CAD was considerable. cCTA is effective in restratifying patients into either a low or high posttest risk group. These results further emphasize the usefulness of cCTA in this cohort. Copyright © 2012 AUR. Published by Elsevier Inc. All rights reserved.
Cury, Ricardo C; Abbara, Suhny; Achenbach, Stephan; Agatston, Arthur; Berman, Daniel S; Budoff, Matthew J; Dill, Karin E; Jacobs, Jill E; Maroules, Christopher D; Rubin, Geoffrey D; Rybicki, Frank J; Schoepf, U Joseph; Shaw, Leslee J; Stillman, Arthur E; White, Charles S; Woodard, Pamela K; Leipsic, Jonathon A
2016-09-01
The intent of CAD-RADS - Coronary Artery Disease Reporting and Data System is to create a standardized method to communicate findings of coronary CT angiography (coronary CTA) in order to facilitate decision-making regarding further patient management. The suggested CAD-RADS classification is applied on a per-patient basis and represents the highest-grade coronary artery lesion documented by coronary CTA. It ranges from CAD-RADS 0 (Zero) for the complete absence of stenosis and plaque to CAD-RADS 5 for the presence of at least one totally occluded coronary artery and should always be interpreted in conjunction with the impression found in the report. Specific recommendations are provided for further management of patients with stable or acute chest pain based on the CAD-RADS classification. The main goal of CAD-RADS is to standardize reporting of coronary CTA results and to facilitate communication of test results to referring physicians along with suggestions for subsequent patient management. In addition, CAD-RADS will provide a framework of standardization that may benefit education, research, peer-review and quality assurance with the potential to ultimately result in improved quality of care. Copyright © 2016 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.
CAD/CAM interface design of excimer laser micro-processing system
NASA Astrophysics Data System (ADS)
Jing, Liang; Chen, Tao; Zuo, Tiechuan
2005-12-01
Recently CAD/CAM technology has been gradually used in the field of laser processing. The excimer laser micro-processing system just identified G instruction before CAD/CAM interface was designed. However the course of designing a part with G instruction for users is too hard. The efficiency is low and probability of making errors is high. By secondary development technology of AutoCAD with Visual Basic, an application was developed to pick-up each entity's information in graph and convert them to each entity's processing parameters. Also an additional function was added into former controlling software to identify these processing parameters of each entity and realize continue processing of graphic. Based on the above CAD/CAM interface, Users can design a part in AutoCAD instead of using G instruction. The period of designing a part is sharply shortened. This new way of design greatly guarantees the processing parameters of the part is right and exclusive. The processing of complex novel bio-chip has been realized by this new function.
Short-Term Outcomes of Screening Mammography Using Computer-Aided Detection
Fenton, Joshua J.; Xing, Guibo; Elmore, Joann G.; Bang, Heejung; Chen, Steven L.; Lindfors, Karen K.; Baldwin, Laura-Mae
2013-01-01
Background Computer-aided detection (CAD) has rapidly diffused into screening mammography practice despite limited and conflicting data on its clinical effect. Objective To determine associations between CAD use during screening mammography and the incidence of ductal carcinoma in situ (DCIS) and invasive breast cancer, invasive cancer stage, and diagnostic testing. Design Retrospective cohort study. Setting Medicare program. Participants Women aged 67 to 89 years having screening mammography between 2001 and 2006 in U.S. SEER (Surveillance, Epidemiology and End Results) regions (409 459 mammograms from 163 099 women). Measurements Incident DCIS and invasive breast cancer within 1 year after mammography, invasive cancer stage, and diagnostic testing within 90 days after screening among women without breast cancer. Results From 2001 to 2006, CAD prevalence increased from 3.6% to 60.5%. Use of CAD was associated with greater DCIS incidence (adjusted odds ratio [OR], 1.17 [95% CI, 1.11 to 1.23]) but no difference in invasive breast cancer incidence (adjusted OR, 1.00 [CI, 0.97 to 1.03]). Among women with invasive cancer, CAD was associated with greater likelihood of stage I to II versus III to IV cancer (adjusted OR, 1.27 [CI, 1.14 to 1.41]). In women without breast cancer, CAD was associated with increased odds of diagnostic mammography (adjusted OR, 1.28 [CI, 1.27 to 1.29]), breast ultrasonography (adjusted OR, 1.07 [CI, 1.06 to 1.09]), and breast biopsy (adjusted OR, 1.10 [CI, 1.08 to 1.12]). Limitation Short follow-up for cancer stage, potential unmeasured confounding, and uncertain generalizability to younger women. Conclusion Use of CAD during screening mammography among Medicare enrollees is associated with increased DCIS incidence, the diagnosis of invasive breast cancer at earlier stages, and increased diagnostic testing among women without breast cancer. Primary Funding Source Center for Healthcare Policy and Research, University of California, Davis. PMID:23588746
NASA Astrophysics Data System (ADS)
Melendez, Jaime; Sánchez, Clara I.; Philipsen, Rick H. H. M.; Maduskar, Pragnya; Dawson, Rodney; Theron, Grant; Dheda, Keertan; van Ginneken, Bram
2016-04-01
Lack of human resources and radiological interpretation expertise impair tuberculosis (TB) screening programmes in TB-endemic countries. Computer-aided detection (CAD) constitutes a viable alternative for chest radiograph (CXR) reading. However, no automated techniques that exploit the additional clinical information typically available during screening exist. To address this issue and optimally exploit this information, a machine learning-based combination framework is introduced. We have evaluated this framework on a database containing 392 patient records from suspected TB subjects prospectively recruited in Cape Town, South Africa. Each record comprised a CAD score, automatically computed from a CXR, and 12 clinical features. Comparisons with strategies relying on either CAD scores or clinical information alone were performed. Our results indicate that the combination framework outperforms the individual strategies in terms of the area under the receiving operating characteristic curve (0.84 versus 0.78 and 0.72), specificity at 95% sensitivity (49% versus 24% and 31%) and negative predictive value (98% versus 95% and 96%). Thus, it is believed that combining CAD and clinical information to estimate the risk of active disease is a promising tool for TB screening.
Den Harder, Annemarie M; Willemink, Martin J; van Hamersvelt, Robbert W; Vonken, Evert-Jan P A; Milles, Julien; Schilham, Arnold M R; Lammers, Jan-Willem; de Jong, Pim A; Leiner, Tim; Budde, Ricardo P J
2016-02-01
To evaluate the effect of radiation dose reduction and iterative reconstruction (IR) on the performance of computer-aided detection (CAD) for pulmonary nodules. In this prospective study twenty-five patients were included who were scanned for pulmonary nodule follow-up. Image acquisition was performed at routine dose and three reduced dose levels in a single session by decreasing mAs-values with 45%, 60% and 75%. Tube voltage was fixed at 120 kVp for patients ≥ 80 kg and 100 kVp for patients < 80 kg. Data were reconstructed with filtered back projection (FBP), iDose(4) (levels 1,4,6) and IMR (levels 1-3). All noncalcified solid pulmonary nodules ≥ 4 mm identified by two radiologists in consensus served as the reference standard. Subsequently, nodule volume was measured with CAD software and compared to the reference consensus. The numbers of true-positives, false-positives and missed pulmonary nodules were evaluated as well as the sensitivity. Median effective radiation dose was 2.2 mSv at routine dose and 1.2, 0.9 and 0.6 mSv at respectively 45%, 60% and 75% reduced dose. A total of 28 pulmonary nodules were included. With FBP at routine dose, 89% (25/28) of the nodules were correctly identified by CAD. This was similar at reduced dose levels with FBP, iDose(4) and IMR. CAD resulted in a median number of false-positives findings of 11 per scan with FBP at routine dose (93% of the CAD marks) increasing to 15 per scan with iDose(4) (95% of the CAD marks) and 26 per scan (96% of the CAD marks) with IMR at the lowest dose level. CAD can identify pulmonary nodules at submillisievert dose levels with FBP, hybrid and model-based IR. However, the number of false-positive findings increased using hybrid and especially model-based IR at submillisievert dose while dose reduction did not affect the number of false-positives with FBP. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.
Emami, Hamed; Takx, Richard A P; Mayrhofer, Thomas; Janjua, Sumbal; Park, Jakob; Pursnani, Amit; Tawakol, Ahmed; Lu, Michael T; Ferencik, Maros; Hoffmann, Udo
2017-09-01
This study sought to determine prognostic value of nonobstructive coronary artery disease (CAD) for atherosclerotic cardiovascular disease (ASCVD) events and to determine whether incorporation of this information into the pooled cohort equation reclassifies recommendations for statin therapy as defined by the 2013 guidelines for cholesterol management of the American College of Cardiology and American Heart Association (ACC/AHA). Detection of nonobstructive CAD by coronary computed tomography angiography may improve risk stratification and permit individualized and more appropriate allocation of statin therapy. This study determined the pooled hazard ratio of nonobstructive CAD for ASCVD events from published studies and incorporated this information into the ACC/AHA pooled cohort equation. The study calculated revised sex- and ethnicity-based 10-year ASCVD risk and determined boundaries corresponding to the original 7.5% risk for ASCVD events. It also assessed reclassification for statin eligibility by incorporating the results from meta-analysis to individual patients from a separate cohort. This study included 2 studies (2,295 subjects; 66% male; prevalence of nonobstructive CAD, 47%; median follow-up, 49 months; 67 ASCVD events). The hazard ratio of nonobstructive CAD for ASCVD events was 3.2 (95% confidence interval: 1.5 to 6.7). Incorporation of this information into the pooled cohort equation resulted in reclassification toward statin eligibility in individuals with nonobstructive CAD, with an original ASCVD score of 3.0% and 5.9% or higher in African-American women and men and a score of 4.4% and 4.6% or higher in Caucasian women and men, respectively. The absence of nonobstructive CAD resulted in reclassification toward statin ineligibility if the original ASCVD score was as 10.0% and 17.9% or lower in African-American women and men and 13.7% and 14.3% or lower in Caucasian women and men, respectively. Reclassification is observed in 14% of patients. Detection of nonobstructive CAD by coronary computed tomography angiography improves risk stratification and permits individualized and more appropriate allocation of statin therapy across sex and ethnicity groups. Copyright © 2017 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.
Xie, Joe X; Cury, Ricardo C; Leipsic, Jonathon; Crim, Matthew T; Berman, Daniel S; Gransar, Heidi; Budoff, Matthew J; Achenbach, Stephan; Ó Hartaigh, Bríain; Callister, Tracy Q; Marques, Hugo; Rubinshtein, Ronen; Al-Mallah, Mouaz H; Andreini, Daniele; Pontone, Gianluca; Cademartiri, Filippo; Maffei, Erica; Chinnaiyan, Kavitha; Raff, Gilbert; Hadamitzky, Martin; Hausleiter, Joerg; Feuchtner, Gudrun; Dunning, Allison; DeLago, Augustin; Kim, Yong-Jin; Kaufmann, Philipp A; Villines, Todd C; Chow, Benjamin J W; Hindoyan, Niree; Gomez, Millie; Lin, Fay Y; Jones, Erica; Min, James K; Shaw, Leslee J
2018-01-01
This study sought to assess clinical outcomes associated with the novel Coronary Artery Disease-Reporting and Data System (CAD-RADS) scores used to standardize coronary computed tomography angiography (CTA) reporting and their potential utility in guiding post-coronary CTA care. Clinical decision support is a major focus of health care policies aimed at improving guideline-directed care. Recently, CAD-RADS was developed to standardize coronary CTA reporting and includes clinical recommendations to facilitate patient management after coronary CTA. In the multinational CONFIRM (COronary CT Angiography EvaluatioN For Clinical Outcomes: An InteRnational Multicenter) registry, 5,039 patients without known coronary artery disease (CAD) underwent coronary CTA and were stratified by CAD-RADS scores, which rank CAD stenosis severity as 0 (0%), 1 (1% to 24%), 2 (25% to 49%), 3 (50% to 69%), 4A (70% to 99% in 1 to 2 vessels), 4B (70% to 99% in 3 vessels or ≥50% left main), or 5 (100%). Kaplan-Meier and multivariable Cox models were used to estimate all-cause mortality or myocardial infarction (MI). Receiver-operating characteristic (ROC) curves were used to compare CAD-RADS to the Duke CAD Index and traditional CAD classification. Referrals to invasive coronary angiography (ICA) after coronary CTA were also assessed. Cumulative 5-year event-free survival ranged from 95.2% to 69.3% for CAD-RADS 0 to 5 (p < 0.0001). Higher scores were associated with elevations in event risk (hazard ratio: 2.46 to 6.09; p < 0.0001). The ROC curve for prediction of death or MI was 0.7052 for CAD-RADS, which was noninferior to the Duke Index (0.7073; p = 0.893) and traditional CAD classification (0.7095; p = 0.783). ICA rates were 13% for CAD-RADS 0 to 2, 66% for CAD-RADS 3, and 84% for CAD-RADS ≥4A. For CAD-RADS 3, 58% of all catheterizations occurred within the first 30 days of follow-up. In a patient subset with available medication data, 57% of CAD-RADS 3 patients who received 30-day ICA were either asymptomatic or not receiving antianginal therapy at baseline, whereas only 32% had angina and were receiving medical therapy. CAD-RADS effectively identified patients at risk for adverse events. Frequent ICA use was observed among patients without severe CAD, many of whom were asymptomatic or not taking antianginal drugs. Incorporating CAD-RADS into coronary CTA reports may provide a novel opportunity to promote evidence-based care post-coronary CTA. Copyright © 2018 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.
CAD-Based Aerodynamic Design of Complex Configurations using a Cartesian Method
NASA Technical Reports Server (NTRS)
Nemec, Marian; Aftosmis, Michael J.; Pulliam, Thomas H.
2003-01-01
A modular framework for aerodynamic optimization of complex geometries is developed. By working directly with a parametric CAD system, complex-geometry models are modified nnd tessellated in an automatic fashion. The use of a component-based Cartesian method significantly reduces the demands on the CAD system, and also provides for robust and efficient flowfield analysis. The optimization is controlled using either a genetic or quasi-Newton algorithm. Parallel efficiency of the framework is maintained even when subject to limited CAD resources by dynamically re-allocating the processors of the flow solver. Overall, the resulting framework can explore designs incorporating large shape modifications and changes in topology.
Zhao, Linping; Patel, Pravin K; Cohen, Mimis
2012-07-01
Computer aided design and manufacturing (CAD/CAM) technology today is the standard in manufacturing industry. The application of the CAD/CAM technology, together with the emerging 3D medical images based virtual surgical planning (VSP) technology, to craniomaxillofacial reconstruction has been gaining increasing attention to reconstructive surgeons. This article illustrates the components, system and clinical management of the VSP and CAD/CAM technology including: data acquisition, virtual surgical and treatment planning, individual implant design and fabrication, and outcome assessment. It focuses primarily on the technical aspects of the VSP and CAD/CAM system to improve the predictability of the planning and outcome.
CT versus MR Techniques in the Detection of Cervical Artery Dissection.
Hanning, Uta; Sporns, Peter B; Schmiedel, Meilin; Ringelstein, Erich B; Heindel, Walter; Wiendl, Heinz; Niederstadt, Thomas; Dittrich, Ralf
2017-11-01
Spontaneous cervical artery dissection (sCAD) is an important etiology of juvenile stroke. The gold standard for the diagnosis of sCAD is convential angiography. However, magnetic resonance imaging (MRI)/MR angiography (MRA) and computed tomography (CT)/CT angiography (CTA) are frequently used alternatives. New developments such as multislice CT/CTA have enabled routine acquisition of thinner sections with rapid imaging times. The goal of this study was to compare the capability of recent developed 128-slice CT/CTA to MRI/MRA to detect radiologic features of sCAD. Retrospective review of patients with suspected sCAD (n = 188) in a database of our Stroke center (2008-2014), who underwent CT/CTA and MRI/MRA on initial clinical work-up. A control group of 26 patients was added. All Images were evaluated concerning specific and sensitive radiological features for dissection by two experienced neuroradiologists. Imaging features were compared between the two modalities. Forty patients with 43 dissected arteries received both modalities (29 internal carotid arteries [ICAs] and 14 vertebral arteries [VAs]). All CADs were identified in CT/CTA and MRI/MRA. The features intimal flap, stenosis, and lumen irregularity appeared in both modalities. One high-grade stenosis was identified by CT/CTA that was expected occluded on MRI/MRA. Two MRI/MRA-confirmed pseudoaneurysms were missed by CT/CTA. None of the controls evidenced specific imaging signs for dissection. CT/CTA is a reliable and better available alternative to MRI/MRA for diagnosis of sCAD. CT/CTA should be used to complement MRI/MRA in cases where MRI/MRA suggests occlusion. Copyright © 2017 by the American Society of Neuroimaging.
Napp, Adriane E; Haase, Robert; Laule, Michael; Schuetz, Georg M; Rief, Matthias; Dreger, Henryk; Feuchtner, Gudrun; Friedrich, Guy; Špaček, Miloslav; Suchánek, Vojtěch; Fuglsang Kofoed, Klaus; Engstroem, Thomas; Schroeder, Stephen; Drosch, Tanja; Gutberlet, Matthias; Woinke, Michael; Maurovich-Horvat, Pál; Merkely, Béla; Donnelly, Patrick; Ball, Peter; Dodd, Jonathan D; Quinn, Martin; Saba, Luca; Porcu, Maurizio; Francone, Marco; Mancone, Massimo; Erglis, Andrejs; Zvaigzne, Ligita; Jankauskas, Antanas; Sakalyte, Gintare; Harań, Tomasz; Ilnicka-Suckiel, Malgorzata; Bettencourt, Nuno; Gama-Ribeiro, Vasco; Condrea, Sebastian; Benedek, Imre; Čemerlić Adjić, Nada; Adjić, Oto; Rodriguez-Palomares, José; Garcia Del Blanco, Bruno; Roditi, Giles; Berry, Colin; Davis, Gershan; Thwaite, Erica; Knuuti, Juhani; Pietilä, Mikko; Kępka, Cezary; Kruk, Mariusz; Vidakovic, Radosav; Neskovic, Aleksandar N; Díez, Ignacio; Lecumberri, Iñigo; Geleijns, Jacob; Kubiak, Christine; Strenge-Hesse, Anke; Do, The-Hoang; Frömel, Felix; Gutiérrez-Ibarluzea, Iñaki; Benguria-Arrate, Gaizka; Keiding, Hans; Katzer, Christoph; Müller-Nordhorn, Jacqueline; Rieckmann, Nina; Walther, Mario; Schlattmann, Peter; Dewey, Marc
2017-07-01
More than 3.5 million invasive coronary angiographies (ICA) are performed in Europe annually. Approximately 2 million of these invasive procedures might be reduced by noninvasive tests because no coronary intervention is performed. Computed tomography (CT) is the most accurate noninvasive test for detection and exclusion of coronary artery disease (CAD). To investigate the comparative effectiveness of CT and ICA, we designed the European pragmatic multicentre DISCHARGE trial funded by the 7th Framework Programme of the European Union (EC-GA 603266). In this trial, patients with a low-to-intermediate pretest probability (10-60 %) of suspected CAD and a clinical indication for ICA because of stable chest pain will be randomised in a 1-to-1 ratio to CT or ICA. CT and ICA findings guide subsequent management decisions by the local heart teams according to current evidence and European guidelines. Major adverse cardiovascular events (MACE) defined as cardiovascular death, myocardial infarction and stroke as a composite endpoint will be the primary outcome measure. Secondary and other outcomes include cost-effectiveness, radiation exposure, health-related quality of life (HRQoL), socioeconomic status, lifestyle, adverse events related to CT/ICA, and gender differences. The DISCHARGE trial will assess the comparative effectiveness of CT and ICA. • Coronary artery disease (CAD) is a major cause of morbidity and mortality. • Invasive coronary angiography (ICA) is the reference standard for detection of CAD. • Noninvasive computed tomography angiography excludes CAD with high sensitivity. • CT may effectively reduce the approximately 2 million negative ICAs in Europe. • DISCHARGE addresses this hypothesis in patients with low-to-intermediate pretest probability for CAD.
[The study on fabrication of dental restoration using PMMA-ZrO2 composites via CAD/CAM].
Li, Shi-bao; Wang, Zhong-yi; Chen, Zhao-hui; Hu, Hai-feng; Tang, Li-hui; Ma, Chu-fan
2005-01-01
To obtain dental restorations by machining PMMA-ZrO2 organic-inorganic composites with the dental CAD/CAM system. Partially sintered Zirconia compacts (PSZC) were prepared via isostatic pressing and partially sintering, with Zirconia nanopowder as raw materials. PMMA-Zirconia organic-inorganic composites were prepared by vacuum infiltrating the prepolymerized MMA into the PSZC, followed by in-situ polymerization. The mechanical properties and machinability of composites were studied. The composites were machined on the dental CAD/CAM system to obtain dental restoration. At 71.44% TD of PSZC, the composite had a 3-point bending strength of (202.56 +/- 3.09) MPa, fracture toughness of (4.30 +/- 0.16) MPa.m(1/2), elasticity modulus of (58.71 +/- 1.98) GPa, and Vickers hardness of (3.82 +/- 0.34) GPa, respectively. A premolar crown was fabricated by CAD/CAM system in 16 mins, and was verisimilitude, without any cracks. The composite at 71.44% TD of PSZC has good mechanical properties and dental restorations can be manufactured by PMMA-Zirconia composites via dental CAD/CAM system.
NASA Technical Reports Server (NTRS)
Panczak, Tim; Ring, Steve; Welch, Mark
1999-01-01
Thermal engineering has long been left out of the concurrent engineering environment dominated by CAD (computer aided design) and FEM (finite element method) software. Current tools attempt to force the thermal design process into an environment primarily created to support structural analysis, which results in inappropriate thermal models. As a result, many thermal engineers either build models "by hand" or use geometric user interfaces that are separate from and have little useful connection, if any, to CAD and FEM systems. This paper describes the development of a new thermal design environment called the Thermal Desktop. This system, while fully integrated into a neutral, low cost CAD system, and which utilizes both FEM and FD methods, does not compromise the needs of the thermal engineer. Rather, the features needed for concurrent thermal analysis are specifically addressed by combining traditional parametric surface based radiation and FD based conduction modeling with CAD and FEM methods. The use of flexible and familiar temperature solvers such as SINDA/FLUINT (Systems Improved Numerical Differencing Analyzer/Fluid Integrator) is retained.
Effect of segmentation algorithms on the performance of computerized detection of lung nodules in CT
Guo, Wei; Li, Qiang
2014-01-01
Purpose: The purpose of this study is to reveal how the performance of lung nodule segmentation algorithm impacts the performance of lung nodule detection, and to provide guidelines for choosing an appropriate segmentation algorithm with appropriate parameters in a computer-aided detection (CAD) scheme. Methods: The database consisted of 85 CT scans with 111 nodules of 3 mm or larger in diameter from the standard CT lung nodule database created by the Lung Image Database Consortium. The initial nodule candidates were identified as those with strong response to a selective nodule enhancement filter. A uniform viewpoint reformation technique was applied to a three-dimensional nodule candidate to generate 24 two-dimensional (2D) reformatted images, which would be used to effectively distinguish between true nodules and false positives. Six different algorithms were employed to segment the initial nodule candidates in the 2D reformatted images. Finally, 2D features from the segmented areas in the 24 reformatted images were determined, selected, and classified for removal of false positives. Therefore, there were six similar CAD schemes, in which only the segmentation algorithms were different. The six segmentation algorithms included the fixed thresholding (FT), Otsu thresholding (OTSU), fuzzy C-means (FCM), Gaussian mixture model (GMM), Chan and Vese model (CV), and local binary fitting (LBF). The mean Jaccard index and the mean absolute distance (Dmean) were employed to evaluate the performance of segmentation algorithms, and the number of false positives at a fixed sensitivity was employed to evaluate the performance of the CAD schemes. Results: For the segmentation algorithms of FT, OTSU, FCM, GMM, CV, and LBF, the highest mean Jaccard index between the segmented nodule and the ground truth were 0.601, 0.586, 0.588, 0.563, 0.543, and 0.553, respectively, and the corresponding Dmean were 1.74, 1.80, 2.32, 2.80, 3.48, and 3.18 pixels, respectively. With these segmentation results of the six segmentation algorithms, the six CAD schemes reported 4.4, 8.8, 3.4, 9.2, 13.6, and 10.4 false positives per CT scan at a sensitivity of 80%. Conclusions: When multiple algorithms are available for segmenting nodule candidates in a CAD scheme, the “optimal” segmentation algorithm did not necessarily lead to the “optimal” CAD detection performance. PMID:25186393
Integrated Computer-Aided Drafting Instruction (ICADI).
ERIC Educational Resources Information Center
Chen, C. Y.; McCampbell, David H.
Until recently, computer-aided drafting and design (CAD) systems were almost exclusively operated on mainframes or minicomputers and their cost prohibited many schools from offering CAD instruction. Today, many powerful personal computers are capable of performing the high-speed calculation and analysis required by the CAD application; however,…
Alqahtani, Fawaz
2017-01-01
Objective The purpose of this study was to determine the effect of two extraoral computer-aided design (CAD) and computer-aided manufacturing (CAM) systems, in comparison with conventional techniques, on the marginal fit of monolithic CAD/CAM lithium disilicate ceramic crowns. Study design This is an in vitro interventional study. Place and duration of study The study was carried out at the Department of Prosthodontics, School of Dentistry, Prince Sattam Bin Abdul-Aziz University, Saudi Arabia, from December 2015 to April 2016. Methodology A marginal gap of 60 lithium disilicate crowns was evaluated by scanning electron microscopy. In total, 20 pressable lithium disilicate (IPS e.max Press [Ivoclar Vivadent]) ceramic crowns were fabricated using the conventional lost-wax technique as a control group. The experimental all-ceramic crowns were produced based on a scan stone model and milled using two extraoral CAD/CAM systems: the Cerec group was fabricated using the Cerec CAD/CAM system, and the Trios group was fabricated using Trios CAD and milled using Wieland Zenotec CAM. One-way analysis of variance (ANOVA) and the Scheffe post hoc test were used for statistical comparison of the groups (α=0.05). Results The mean (±standard deviation) of the marginal gap of each group was as follows: the Control group was 91.15 (±15.35) µm, the Cerec group was 111.07 (±6.33) µm, and the Trios group was 60.17 (±11.09) µm. One-way ANOVA and the Scheffe post hoc test showed a statistically significant difference in the marginal gap between all groups. Conclusion It can be concluded from the current study that all-ceramic crowns, fabricated using the CAD/CAM system, show a marginal accuracy that is acceptable in clinical environments. The Trios CAD group displayed the smallest marginal gap. PMID:28352204
Accurate Classification of Diminutive Colorectal Polyps Using Computer-Aided Analysis.
Chen, Peng-Jen; Lin, Meng-Chiung; Lai, Mei-Ju; Lin, Jung-Chun; Lu, Henry Horng-Shing; Tseng, Vincent S
2018-02-01
Narrow-band imaging is an image-enhanced form of endoscopy used to observed microstructures and capillaries of the mucosal epithelium which allows for real-time prediction of histologic features of colorectal polyps. However, narrow-band imaging expertise is required to differentiate hyperplastic from neoplastic polyps with high levels of accuracy. We developed and tested a system of computer-aided diagnosis with a deep neural network (DNN-CAD) to analyze narrow-band images of diminutive colorectal polyps. We collected 1476 images of neoplastic polyps and 681 images of hyperplastic polyps, obtained from the picture archiving and communications system database in a tertiary hospital in Taiwan. Histologic findings from the polyps were also collected and used as the reference standard. The images and data were used to train the DNN. A test set of images (96 hyperplastic and 188 neoplastic polyps, smaller than 5 mm), obtained from patients who underwent colonoscopies from March 2017 through August 2017, was then used to test the diagnostic ability of the DNN-CAD vs endoscopists (2 expert and 4 novice), who were asked to classify the images of the test set as neoplastic or hyperplastic. Their classifications were compared with findings from histologic analysis. The primary outcome measures were diagnostic accuracy, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and diagnostic time. The accuracy, sensitivity, specificity, PPV, NPV, and diagnostic time were compared among DNN-CAD, the novice endoscopists, and the expert endoscopists. The study was designed to detect a difference of 10% in accuracy by a 2-sided McNemar test. In the test set, the DNN-CAD identified neoplastic or hyperplastic polyps with 96.3% sensitivity, 78.1% specificity, a PPV of 89.6%, and a NPV of 91.5%. Fewer than half of the novice endoscopists classified polyps with a NPV of 90% (their NPVs ranged from 73.9% to 84.0%). DNN-CAD classified polyps as neoplastic or hyperplastic in 0.45 ± 0.07 seconds-shorter than the time required by experts (1.54 ± 1.30 seconds) and nonexperts (1.77 ± 1.37 seconds) (both P < .001). DNN-CAD classified polyps with perfect intra-observer agreement (kappa score of 1). There was a low level of intra-observer and inter-observer agreement in classification among endoscopists. We developed a system called DNN-CAD to identify neoplastic or hyperplastic colorectal polyps less than 5 mm. The system classified polyps with a PPV of 89.6%, and a NPV of 91.5%, and in a shorter time than endoscopists. This deep-learning model has potential for not only endoscopic image recognition but for other forms of medical image analysis, including sonography, computed tomography, and magnetic resonance images. Copyright © 2018 AGA Institute. Published by Elsevier Inc. All rights reserved.
Lanktree, Matthew B; Hegele, Robert A
2009-02-26
Despite the recent success of genome-wide association studies (GWASs) in identifying loci consistently associated with coronary artery disease (CAD), a large proportion of the genetic components of CAD and its metabolic risk factors, including plasma lipids, type 2 diabetes and body mass index, remain unattributed. Gene-gene and gene-environment interactions might produce a meaningful improvement in quantification of the genetic determinants of CAD. Testing for gene-gene and gene-environment interactions is thus a new frontier for large-scale GWASs of CAD. There are several anecdotal examples of monogenic susceptibility to CAD in which the phenotype was worsened by an adverse environment. In addition, small-scale candidate gene association studies with functional hypotheses have identified gene-environment interactions. For future evaluation of gene-gene and gene-environment interactions to achieve the same success as the single gene associations reported in recent GWASs, it will be important to pre-specify agreed standards of study design and statistical power, environmental exposure measurement, phenomic characterization and analytical strategies. Here we discuss these issues, particularly in relation to the investigation and potential clinical utility of gene-gene and gene-environment interactions in CAD.
Cardiovascular Risk Assessment and Management in Prerenal Transplantation Candidates.
Lindley, Eric M; Hall, Amanda K; Hess, Jordan; Abraham, Jo; Smith, Brigham; Hopkins, Paul N; Shihab, Fuad; Welt, Frederick; Owan, Theophilus; Fang, James C
2016-01-01
Cardiovascular (CV) assessment in prerenal transplant patients varies by center. Current guidelines recommend stress testing for candidates if ≥ 3 CV risk factors exist. We evaluated the CV assessment and management in 685 patients referred for kidney transplant over a 7-year period. All patients had CV risk factors, and the most common cause of end-stage renal disease was diabetes. Thirty-three percent (n = 229) underwent coronary angiography. The sensitivity of stress testing to detect obstructive coronary artery disease (CAD) was poor (0.26). Patients who had no CAD, nonobstructive CAD, or CAD with intervention had significantly higher event-free survival compared with patients with obstructive CAD without intervention. There were no adverse clinical events (death, myocardial infarction, stroke, revascularization, and graft failure) within 30 days post-transplant in patients who had preoperative angiography (n = 77). Of the transplanted patients who did not have an angiogram (n = 289), there were 8 clinical events (6 myocardial infarctions) in the first 30 days. In conclusion, our results indicate that stress testing and usual risk factors were poor predictors of obstructive CAD and that revascularization may prove beneficial in these patients. Copyright © 2016 Elsevier Inc. All rights reserved.
Chen, Zhang-wei; Qian, Ju-ying; Jian, Ying; Ge, Lei; Liu, Xue-bo; Shu, Xian-hong; Ge, Junbo
2011-02-01
Aortic valve calcification (AVC) is common in the elderly and associated with increased cardiovascular mortality, while diabetes is one of the confirmed risk factors for coronary artery disease (CAD). In this study, we aimed to evaluate the prevalence and severity of CAD in type-2 diabetic patients with AVC. From June to December in 2007, a total of 325 consecutive patients with chest pain or chest distress were admitted for coronary angiography. The severity of CAD was evaluated by the Gensini score and the number of stenosed vessels. All patients underwent transthoracic echocardiography for detecting AVC. Compared with the patients without diabetes (n = 221), the type-2 diabetic patients (n = 104) had a similar prevalence of CAD (66.5% vs. 72.1%, P = 0.312). Further classified by the presence of AVC, patients with AVC had a higher prevalence of CAD, average Gensini score and the number of stenosed vessels, both in the group with and without diabetes. It was also demonstrated that the odds ratio (OR) of AVC for CAD in the diabetic patients was higher than in the non-diabetic ones (3.405 vs 2.515) after chi-square analysis (single-variable). However, at multivariable logistic regression analysis for CAD, the OR of AVC was 3.757 (P = 0.03) in diabetic group, while it did not achieve statistical significance in the non-diabetic group (OR = 2.130, P= 0.074). Type-2 diabetic patients with AVC had a higher prevalence of and more severe CAD.
Vojdani, Mahroo; Torabi, Kianoosh; Atashkar, Berivan; Heidari, Hossein; Torabi Ardakani, Mahshid
2016-01-01
Statement of the Problem: Marginal fitness is the most important criteria for evaluation of the clinical acceptability of a cast restoration. Marginal gap which is due to cement solubility and plaque retention is potentially detrimental to both tooth and periodontal tissues. Purpose: This in vitro study aimed to evaluate the marginal and internal fit of cobalt- chromium (Co-Cr) copings fabricated by two different CAD/CAM systems: (CAD/ milling and CAD/ Ceramill Sintron). Materials and Method: We prepared one machined standard stainless steel master model with following dimensions: 7 mm height, 5mm diameter, 90˚ shoulder marginal finish line with 1 mm width, 10˚ convergence angle and anti-rotational surface on the buccal aspect of the die. There were 10 copings produced from hard presintered Co-Cr blocks according to CAD/ Milling technique and ten copings from soft non- presintered Co-Cr blocks according to CAD/ Ceramill Sintron technique. Marginal and internal accuracies of copings were documented by the replica technique. Replicas were examined at ten reference points under a digital microscope (230X). The Student's t-test was used for statistical analysis. p< 0.001 was considered significant. Results: Statistically significant differences existed between the groups (p< 0.001). The CAD/milling group (hard copings) had a mean marginal discrepancy (MD) of 104 µm, axial discrepancy (AD) of 23 µm and occlusal discrepancy of 130 µm. For CAD/ Ceramill Sintron group, these values were 195 µm (MD), 46 µm (AD), and 232 µm (OD). Internal total discrepancy (ITD) for the CAD/milling group was 77 µm, whereas for the CAD/Ceramill Sintron group was 143 µm. Conclusion: Hard presintered Co-Cr copings had significantly higher marginal and internal accuracies compared to the soft non-presintered copings. PMID:27942545
Li, Wei; Cao, Peng; Zhao, Dazhe; Wang, Junbo
2016-01-01
Computer aided detection (CAD) systems can assist radiologists by offering a second opinion on early diagnosis of lung cancer. Classification and feature representation play critical roles in false-positive reduction (FPR) in lung nodule CAD. We design a deep convolutional neural networks method for nodule classification, which has an advantage of autolearning representation and strong generalization ability. A specified network structure for nodule images is proposed to solve the recognition of three types of nodules, that is, solid, semisolid, and ground glass opacity (GGO). Deep convolutional neural networks are trained by 62,492 regions-of-interest (ROIs) samples including 40,772 nodules and 21,720 nonnodules from the Lung Image Database Consortium (LIDC) database. Experimental results demonstrate the effectiveness of the proposed method in terms of sensitivity and overall accuracy and that it consistently outperforms the competing methods.
Computer-aided diagnosis of liver tumors on computed tomography images.
Chang, Chin-Chen; Chen, Hong-Hao; Chang, Yeun-Chung; Yang, Ming-Yang; Lo, Chung-Ming; Ko, Wei-Chun; Lee, Yee-Fan; Liu, Kao-Lang; Chang, Ruey-Feng
2017-07-01
Liver cancer is the tenth most common cancer in the USA, and its incidence has been increasing for several decades. Early detection, diagnosis, and treatment of the disease are very important. Computed tomography (CT) is one of the most common and robust imaging techniques for the detection of liver cancer. CT scanners can provide multiple-phase sequential scans of the whole liver. In this study, we proposed a computer-aided diagnosis (CAD) system to diagnose liver cancer using the features of tumors obtained from multiphase CT images. A total of 71 histologically-proven liver tumors including 49 benign and 22 malignant lesions were evaluated with the proposed CAD system to evaluate its performance. Tumors were identified by the user and then segmented using a region growing algorithm. After tumor segmentation, three kinds of features were obtained for each tumor, including texture, shape, and kinetic curve. The texture was quantified using 3 dimensional (3-D) texture data of the tumor based on the grey level co-occurrence matrix (GLCM). Compactness, margin, and an elliptic model were used to describe the 3-D shape of the tumor. The kinetic curve was established from each phase of tumor and represented as variations in density between each phase. Backward elimination was used to select the best combination of features, and binary logistic regression analysis was used to classify the tumors with leave-one-out cross validation. The accuracy and sensitivity for the texture were 71.82% and 68.18%, respectively, which were better than for the shape and kinetic curve under closed specificity. Combining all of the features achieved the highest accuracy (58/71, 81.69%), sensitivity (18/22, 81.82%), and specificity (40/49, 81.63%). The Az value of combining all features was 0.8713. Combining texture, shape, and kinetic curve features may be able to differentiate benign from malignant tumors in the liver using our proposed CAD system. Copyright © 2017 Elsevier B.V. All rights reserved.
ΤND: a thyroid nodule detection system for analysis of ultrasound images and videos.
Keramidas, Eystratios G; Maroulis, Dimitris; Iakovidis, Dimitris K
2012-06-01
In this paper, we present a computer-aided-diagnosis (CAD) system prototype, named TND (Thyroid Nodule Detector), for the detection of nodular tissue in ultrasound (US) thyroid images and videos acquired during thyroid US examinations. The proposed system incorporates an original methodology that involves a novel algorithm for automatic definition of the boundaries of the thyroid gland, and a novel approach for the extraction of noise resilient image features effectively representing the textural and the echogenic properties of the thyroid tissue. Through extensive experimental evaluation on real thyroid US data, its accuracy in thyroid nodule detection has been estimated to exceed 95%. These results attest to the feasibility of the clinical application of TND, for the provision of a second more objective opinion to the radiologists by exploiting image evidences.
Alderazi, Ahmed Ali; Lynch, Mary
2017-01-01
In response to growing concerns regarding the overuse of coronary computed tomography angiography (CCTA) in the clinical setting, multiple societies, including the American College of Cardiology Foundation, have jointly published revised criteria regarding the appropriate use of this imaging modality. However, previous research indicates significant discrepancies in the rate of adherence to these guidelines. To assess the appropriateness of CCTA referrals in a tertiary cardiac center in Bahrain. This retrospective clinical audit examined the records of patients referred to CCTA between the April 1, 2015 and December 31, 2015 in Mohammed bin Khalifa Cardiac Center. Using information from medical records, each case was meticulously audited against guidelines to categorize it as appropriate, inappropriate, or uncertain. Of the 234 records examined, 176 (75.2%) were appropriate, 47 (20.1%) were uncertain, and 11 (4.7%) were inappropriate. About 74.4% of all referrals were to investigate coronary artery disease (CAD). The most common indication that was deemed appropriate was the detection of CAD in the setting of suspected ischemic equivalent in patients with an intermediate pretest probability of CAD (65.9%). Most referrals deemed inappropriate were requested to detect CAD in asymptomatic patients at low or intermediate risk of CAD (63.6%). This audit demonstrates a relatively low rate of inappropriate CCTA referrals, indicating the appropriate and efficient use of this resource in the Mohammed bin Khalifa Cardiac Center. Agreement on and reclassification of "uncertain" cases by guideline authorities would facilitate a deeper understanding of referral appropriateness.
A hybrid deep learning approach to predict malignancy of breast lesions using mammograms
NASA Astrophysics Data System (ADS)
Wang, Yunzhi; Heidari, Morteza; Mirniaharikandehei, Seyedehnafiseh; Gong, Jing; Qian, Wei; Qiu, Yuchen; Zheng, Bin
2018-03-01
Applying deep learning technology to medical imaging informatics field has been recently attracting extensive research interest. However, the limited medical image dataset size often reduces performance and robustness of the deep learning based computer-aided detection and/or diagnosis (CAD) schemes. In attempt to address this technical challenge, this study aims to develop and evaluate a new hybrid deep learning based CAD approach to predict likelihood of a breast lesion detected on mammogram being malignant. In this approach, a deep Convolutional Neural Network (CNN) was firstly pre-trained using the ImageNet dataset and serve as a feature extractor. A pseudo-color Region of Interest (ROI) method was used to generate ROIs with RGB channels from the mammographic images as the input to the pre-trained deep network. The transferred CNN features from different layers of the CNN were then obtained and a linear support vector machine (SVM) was trained for the prediction task. By applying to a dataset involving 301 suspicious breast lesions and using a leave-one-case-out validation method, the areas under the ROC curves (AUC) = 0.762 and 0.792 using the traditional CAD scheme and the proposed deep learning based CAD scheme, respectively. An ensemble classifier that combines the classification scores generated by the two schemes yielded an improved AUC value of 0.813. The study results demonstrated feasibility and potentially improved performance of applying a new hybrid deep learning approach to develop CAD scheme using a relatively small dataset of medical images.
Huang, P J; Chieng, P U; Lee, Y T; Chiang, F T; Tseng, Y Z; Liau, C S; Tseng, C D; Su, C T; Lien, W P
1992-11-01
Exercise thallium-201 imaging using single-photon emission computed tomography (SPECT) was evaluated in 154 patients with angiographically documented coronary artery disease (CAD) and in 25 normal subjects. Of the 154 patients with CAD, 134 (87%) had abnormal thallium images. By contrast, only 77 (50%) patients had ischemic ST-segment depression (p < 0.001). Among 25 normal subjects, 20 had normal exercise SPECT images. The specificity of exercise SPECT imaging (80% or 20/25) in excluding patients with CAD was not significantly higher than that of exercise electrocardiography (76% or 19/25). For the detection of individual vessel involvement by analysis of territories of perfusion abnormalities, the sensitivity and specificity of exercise SPECT were 72% and 96% for the left anterior descending, 78% and 85% for the right coronary, and 47% and 98% for the left circumflex artery. Ninety (group 1) of the 154 patients with CAD achieved adequate exercise end points (ischemic ST-segment depression or > 85% of maximal predicted heart rate) and 64 (group 2) did not. Exercise SPECT showed significantly more perfusion abnormalities in group 1 than in group 2 (96% vs 75%, p < 0.001). We conclude that: (1) exercise SPECT thallium imaging is more sensitive than exercise electrocardiography for detecting patients with CAD; (2) the sensitivity of the test is affected by the level of exercise; and (3) it is valuable in the identification of individual vessel involvement.
Cardiac Magnetic Resonance Imaging for the Diagnosis of Coronary Artery Disease
2010-01-01
Executive Summary In July 2009, the Medical Advisory Secretariat (MAS) began work on Non-Invasive Cardiac Imaging Technologies for the Diagnosis of Coronary Artery Disease (CAD), an evidence-based review of the literature surrounding different cardiac imaging modalities to ensure that appropriate technologies are accessed by patients suspected of having CAD. This project came about when the Health Services Branch at the Ministry of Health and Long-Term Care asked MAS to provide an evidentiary platform on effectiveness and cost-effectiveness of non-invasive cardiac imaging modalities. After an initial review of the strategy and consultation with experts, MAS identified five key non-invasive cardiac imaging technologies for the diagnosis of CAD. Evidence-based analyses have been prepared for each of these five imaging modalities: cardiac magnetic resonance imaging, single photon emission computed tomography, 64-slice computed tomographic angiography, stress echocardiography, and stress echocardiography with contrast. For each technology, an economic analysis was also completed (where appropriate). A summary decision analytic model was then developed to encapsulate the data from each of these reports (available on the OHTAC and MAS website). The Non-Invasive Cardiac Imaging Technologies for the Diagnosis of Coronary Artery Disease series is made up of the following reports, which can be publicly accessed at the MAS website at: www.health.gov.on.ca/mas or at www.health.gov.on.ca/english/providers/program/mas/mas_about.html Single Photon Emission Computed Tomography for the Diagnosis of Coronary Artery Disease: An Evidence-Based Analysis Stress Echocardiography for the Diagnosis of Coronary Artery Disease: An Evidence-Based Analysis Stress Echocardiography with Contrast for the Diagnosis of Coronary Artery Disease: An Evidence-Based Analysis 64-Slice Computed Tomographic Angiography for the Diagnosis of Coronary Artery Disease: An Evidence-Based Analysis Cardiac Magnetic Resonance Imaging for the Diagnosis of Coronary Artery Disease: An Evidence-Based Analysis Pease note that two related evidence-based analyses of non-invasive cardiac imaging technologies for the assessment of myocardial viability are also available on the MAS website: Positron Emission Tomography for the Assessment of Myocardial Viability: An Evidence-Based Analysis Magnetic Resonance Imaging for the Assessment of Myocardial Viability: an Evidence-Based Analysis The Toronto Health Economics and Technology Assessment Collaborative has also produced an associated economic report entitled: The Relative Cost-effectiveness of Five Non-invasive Cardiac Imaging Technologies for Diagnosing Coronary Artery Disease in Ontario [Internet]. Available from: http://theta.utoronto.ca/reports/?id=7 Objective The objective of this analysis was to determine the diagnostic accuracy of cardiac magnetic resonance imaging (MRI) for the diagnosis of patients with known/suspected coronary artery disease (CAD) compared to coronary angiography. Cardiac MRI Stress cardiac MRI is a non-invasive, x-ray free imaging technique that takes approximately 30 to 45 minutes to complete and can be performed using to two different methods, a) perfusion imaging following a first pass of an intravenous bolus of gadolinium contrast, or b) wall motion imaging. Stress is induced pharmacologically with either dobutamine, dipyridamole, or adenosine, as physical exercise is difficult to perform within the magnet bore and often induces motion artifacts. Alternatives to stress cardiac perfusion MRI include stress single-photon emission computed tomography (SPECT) and stress echocardiography (ECHO). The advantage of cardiac MRI is that it does not pose the radiation burden associated with SPECT. During the same sitting, cardiac MRI can also assess left and right ventricular dimensions, viability, and cardiac mass. It may also mitigate the need for invasive diagnostic coronary angiography in patients with intermediate risk factors for CAD. Evidence-Based Analysis Literature Search A literature search was performed on October 9, 2009 using OVID MEDLINE, MEDLINE In-Process and Other Non-Indexed Citations, EMBASE, the Cumulative Index to Nursing & Allied Health Literature (CINAHL), the Cochrane Library, and the International Agency for Health Technology Assessment (INAHTA) for studies published from January 1, 2005 to October 9, 2008. Abstracts were reviewed by a single reviewer and, for those studies meeting the eligibility criteria, full-text articles were obtained. Reference lists were also examined for any relevant studies not identified through the search. Articles with unknown eligibility were reviewed with a second clinical epidemiologist and then a group of epidemiologists until consensus was established. The quality of evidence was assessed as high, moderate, low or very low according to GRADE methodology. Given the large amount of clinical heterogeneity of the articles meeting the inclusion criteria, as well as suggestions from an Expert Advisory Panel Meeting held on October 5, 2009, the inclusion criteria were revised to examine the effectiveness of cardiac MRI for the detection of CAD. Inclusion Criteria Exclusion Criteria Heath technology assessments, systematic reviews, randomized controlled trials, observational studies ≥20 adult patients enrolled. Published 2004-2009 Licensed by Health Canada For diagnosis of CAD: Reference standard is coronary angiography Significant CAD defined as ≥ 50% coronary stenosis Patients with suspected or known CAD Reported results by patient, not segment Non-English studies Grey literature Planar imaging MUGA Patients with recent MI (i.e., within 1 month) Patients with non-ischemic heart disease Studies done exclusively in special populations (e.g., women, diabetics) Outcomes of Interest Sensitivity and specificity Area under the curve (AUC) Diagnostic odds ratio (DOR) Summary of Findings Stress cardiac MRI using perfusion analysis yielded a pooled sensitivity of 0.91 (95% CI: 0.89 to 0.92) and specificity of 0.79 (95% CI: 0.76 to 0.82) for the detection of CAD. Stress cardiac MRI using wall motion analysis yielded a pooled sensitivity of 0.81 (95% CI: 0.77 to 0.84) and specificity of 0.85 (95% CI: 0.81 to 0.89) for the detection of CAD. Based on DORs, there was no significant difference between pooled stress cardiac MRI using perfusion analysis and pooled stress cardiac MRI using wall motion analysis (P=0.26) for the detection of CAD. Pooled subgroup analysis of stress cardiac MRI using perfusion analysis showed no significant difference in the DORs between 1.5T and 3T MRI (P=0.72) for the detection of CAD. One study (N=60) was identified that examined stress cardiac MRI using wall motion analysis with a 3T MRI. The sensitivity and specificity of 3T MRI were 0.64 (95% CI: 0.44 to 0.81) and 1.00 (95% CI: 0.89 to 1.00), respectively, for the detection of CAD. The effectiveness of stress cardiac MRI for the detection of CAD in unstable patients with acute coronary syndrome was reported in only one study (N=35). Using perfusion analysis, the sensitivity and specificity were 0.72 (95% CI: 0.53 to 0.87) and 1.00 (95% CI: 0.54 to 1.00), respectively, for the detection of CAD. Ontario Health System Impact Analysis According to an expert consultant, in Ontario: Stress first pass perfusion is currently performed in small numbers in London (London Health Sciences Centre) and Toronto (University Health Network at the Toronto General Hospital site and Sunnybrook Health Sciences Centre). Stress wall motion is only performed as part of research protocols and not very often. Cardiac MRI machines use 1.5T almost exclusively, with 3T used in research for first pass perfusion. On November 25 2009, the Cardiac Imaging Expert Advisory Panel met and made the following comments about stress cardiac MRI for perfusion analysis: Accessibility to cardiac MRI is limited and generally used to assess structural abnormalities. Most MRIs in Ontario are already in 24–hour, constant use and it would thus be difficult to add cardiac MRI for CAD diagnosis as an additional indication. The performance of cardiac MRI for the diagnosis of CAD can be technically challenging. GRADE Quality of Evidence for Cardiac MRI in the Diagnosis of CAD The quality of the body of evidence was assessed according to the GRADE Working Group criteria for diagnostic tests. For perfusion analysis, the overall quality was determined to be low and for wall motion analysis the overall quality was very low. PMID:23074389
A walk through the planned CS building. M.S. Thesis
NASA Technical Reports Server (NTRS)
Khorramabadi, Delnaz
1991-01-01
Using the architectural plan views of our future computer science building as test objects, we have completed the first stage of a Building walkthrough system. The inputs to our system are AutoCAD files. An AutoCAD converter translates the geometrical information in these files into a format suitable for 3D rendering. Major model errors, such as incorrect polygon intersections and random face orientations, are detected and fixed automatically. Interactive viewing and editing tools are provided to view the results, to modify and clean the model and to change surface attributes. Our display system provides a simple-to-use user interface for interactive exploration of buildings. Using only the mouse buttons, the user can move inside and outside the building and change floors. Several viewing and rendering options are provided, such as restricting the viewing frustum, avoiding wall collisions, and selecting different rendering algorithms. A plan view of the current floor, with the position of the eye point and viewing direction on it, is displayed at all times. The scene illumination can be manipulated, by interactively controlling intensity values for 5 light sources.
Space crew radiation exposure analysis system based on a commercial stand-alone CAD system
NASA Technical Reports Server (NTRS)
Appleby, Matthew H.; Golightly, Michael J.; Hardy, Alva C.
1992-01-01
Major improvements have recently been completed in the approach to spacecraft shielding analysis. A Computer-Aided Design (CAD)-based system has been developed for determining the shielding provided to any point within or external to the spacecraft. Shielding analysis is performed using a commercially available stand-alone CAD system and a customized ray-tracing subroutine contained within a standard engineering modeling software package. This improved shielding analysis technique has been used in several vehicle design projects such as a Mars transfer habitat, pressurized lunar rover, and the redesigned Space Station. Results of these analyses are provided to demonstrate the applicability and versatility of the system.
Hamza, Tamer A; Sherif, Rana M
2017-06-01
Dental laboratories use different computer-aided design and computer-aided manufacturing (CAD-CAM) systems to fabricate fixed prostheses; however, limited evidence is available concerning which system provides the best marginal discrepancy. The purpose of this in vitro study was to evaluate the marginal fit of 5 different monolithic zirconia restorations milled with different CAD-CAM systems. Thirty monolithic zirconia crowns were fabricated on a custom-designed stainless steel die and were divided into 5 groups according to the type of monolithic zirconia crown and the CAD-CAM system used: group TZ, milled with an MCXL milling machine; group CZ, translucent zirconia milled with a motion milling machine; group ZZ, zirconia milled with a dental milling unit; group PZ, translucent zirconia milled with a zirconia milling unit; and group BZ, solid zirconia milled using an S1 VHF milling machine. The marginal fit was measured with a binocular microscope at an original magnification of ×100. The results were tabulated and statistically analyzed with 1-way ANOVA and post hoc surface range test, and pairwise multiple comparisons were made using Bonferroni correction (α=.05). The type of CAD-CAM used affected the marginal fit of the monolithic restoration. The mean (±SD) highest marginal discrepancy was recorded in group TZI at 39.3 ±2.3 μm, while the least mean marginal discrepancy was recorded in group IZ (22.8 ±8.9 μm). The Bonferroni post hoc test showed that group TZI was significantly different from all other groups tested (P<.05). Within the limitation of this in vitro study, all tested CAD-CAM systems produced monolithic zirconia restorations with clinically acceptable marginal discrepancies; however, the CAD-CAM system with the 5-axis milling unit produced the best marginal fit. Copyright © 2016 Editorial Council for the Journal of Prosthetic Dentistry. Published by Elsevier Inc. All rights reserved.
Beheshti, Iman; Demirel, Hasan; Farokhian, Farnaz; Yang, Chunlan; Matsuda, Hiroshi
2016-12-01
This paper presents an automatic computer-aided diagnosis (CAD) system based on feature ranking for detection of Alzheimer's disease (AD) using structural magnetic resonance imaging (sMRI) data. The proposed CAD system is composed of four systematic stages. First, global and local differences in the gray matter (GM) of AD patients compared to the GM of healthy controls (HCs) are analyzed using a voxel-based morphometry technique. The aim is to identify significant local differences in the volume of GM as volumes of interests (VOIs). Second, the voxel intensity values of the VOIs are extracted as raw features. Third, the raw features are ranked using a seven-feature ranking method, namely, statistical dependency (SD), mutual information (MI), information gain (IG), Pearson's correlation coefficient (PCC), t-test score (TS), Fisher's criterion (FC), and the Gini index (GI). The features with higher scores are more discriminative. To determine the number of top features, the estimated classification error based on training set made up of the AD and HC groups is calculated, with the vector size that minimized this error selected as the top discriminative feature. Fourth, the classification is performed using a support vector machine (SVM). In addition, a data fusion approach among feature ranking methods is introduced to improve the classification performance. The proposed method is evaluated using a data-set from ADNI (130 AD and 130 HC) with 10-fold cross-validation. The classification accuracy of the proposed automatic system for the diagnosis of AD is up to 92.48% using the sMRI data. An automatic CAD system for the classification of AD based on feature-ranking method and classification errors is proposed. In this regard, seven-feature ranking methods (i.e., SD, MI, IG, PCC, TS, FC, and GI) are evaluated. The optimal size of top discriminative features is determined by the classification error estimation in the training phase. The experimental results indicate that the performance of the proposed system is comparative to that of state-of-the-art classification models. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
Hatipoglu, Nuh; Bilgin, Gokhan
2017-10-01
In many computerized methods for cell detection, segmentation, and classification in digital histopathology that have recently emerged, the task of cell segmentation remains a chief problem for image processing in designing computer-aided diagnosis (CAD) systems. In research and diagnostic studies on cancer, pathologists can use CAD systems as second readers to analyze high-resolution histopathological images. Since cell detection and segmentation are critical for cancer grade assessments, cellular and extracellular structures should primarily be extracted from histopathological images. In response, we sought to identify a useful cell segmentation approach with histopathological images that uses not only prominent deep learning algorithms (i.e., convolutional neural networks, stacked autoencoders, and deep belief networks), but also spatial relationships, information of which is critical for achieving better cell segmentation results. To that end, we collected cellular and extracellular samples from histopathological images by windowing in small patches with various sizes. In experiments, the segmentation accuracies of the methods used improved as the window sizes increased due to the addition of local spatial and contextual information. Once we compared the effects of training sample size and influence of window size, results revealed that the deep learning algorithms, especially convolutional neural networks and partly stacked autoencoders, performed better than conventional methods in cell segmentation.
NASA Astrophysics Data System (ADS)
Fetita, C.; Chang-Chien, K. C.; Brillet, P. Y.; Pr"teux, F.; Chang, R. F.
2012-03-01
Our study aims at developing a computer-aided diagnosis (CAD) system for fully automatic detection and classification of pathological lung parenchyma patterns in idiopathic interstitial pneumonias (IIP) and emphysema using multi-detector computed tomography (MDCT). The proposed CAD system is based on three-dimensional (3-D) mathematical morphology, texture and fuzzy logic analysis, and can be divided into four stages: (1) a multi-resolution decomposition scheme based on a 3-D morphological filter was exploited to discriminate the lung region patterns at different analysis scales. (2) An additional spatial lung partitioning based on the lung tissue texture was introduced to reinforce the spatial separation between patterns extracted at the same resolution level in the decomposition pyramid. Then, (3) a hierarchic tree structure was exploited to describe the relationship between patterns at different resolution levels, and for each pattern, six fuzzy membership functions were established for assigning a probability of association with a normal tissue or a pathological target. Finally, (4) a decision step exploiting the fuzzy-logic assignments selects the target class of each lung pattern among the following categories: normal (N), emphysema (EM), fibrosis/honeycombing (FHC), and ground glass (GDG). According to a preliminary evaluation on an extended database, the proposed method can overcome the drawbacks of a previously developed approach and achieve higher sensitivity and specificity.
Oral and subcutaneous therapy of canine atopic dermatitis with recombinant feline interferon omega.
Litzlbauer, Petra; Weber, Karin; Mueller, Ralf S
2014-03-01
Canine atopic dermatitis (CAD) is a common allergic skin disease that has been treated with subcutaneously administered interferons (IFN). Recombinant feline IFN-ω (rFeIFN-ω) was reported to be efficacious for CAD. Whether dogs develop neutralizing antibodies against rFeIFN-ω during long-term treatment and whether orally administered IFNs are efficacious in CAD is unknown. The aim of this study was to evaluate the potential development of antibodies against rFeIFN-ω in atopic dogs and to compare subcutaneous and oral IFN therapy. Twenty-six atopic dogs were randomly assigned to two groups. The first group (n=15) received eight subcutaneous injections of rFeIFN-ω (Virbagen® omega, Virbac, Carros, France) over four months, the second group (n=11) received rFeIFN-ω daily orally. Concurrent medication was permitted, except systemically acting glucocorticoids and cyclosporin, which had to be withdrawn at least two weeks prior to the study. Serum samples for antibody detection were collected before and after the study. On days 0, 60 and 120 skin lesions and pruritus were evaluated using a validated lesion score (Canine Atopic Dermatitis Extent and Severity Index=CADESI) and a validated pruritus score. Concurrent medications were recorded. For every visit a total score, consisting of CADESI, pruritus score and medication score was created. For antibody detection an indirect ELISA, using Virbagen® omega as antigen, was performed. Comparison of pruritus scores, CADESI and total scores between days 0 and 120 showed improvement in both groups, however, significant improvement could only be detected in the oral group with CADESI and total scores (61%, P=0.04 and 36%, P=0.02 respectively). Serum antibodies against rFeIFN-ω could not be detected in any of the dogs. In this study antibody production could not be demonstrated. It suggests better efficacy with oral IFN administration, which should be further verified in larger, randomized, controlled studies. Copyright © 2013 Elsevier Ltd. All rights reserved.
CAD-centric Computation Management System for a Virtual TBM
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ramakanth Munipalli; K.Y. Szema; P.Y. Huang
HyPerComp Inc. in research collaboration with TEXCEL has set out to build a Virtual Test Blanket Module (VTBM) computational system to address the need in contemporary fusion research for simulating the integrated behavior of the blanket, divertor and plasma facing components in a fusion environment. Physical phenomena to be considered in a VTBM will include fluid flow, heat transfer, mass transfer, neutronics, structural mechanics and electromagnetics. We seek to integrate well established (third-party) simulation software in various disciplines mentioned above. The integrated modeling process will enable user groups to interoperate using a common modeling platform at various stages of themore » analysis. Since CAD is at the core of the simulation (as opposed to computational meshes which are different for each problem,) VTBM will have a well developed CAD interface, governing CAD model editing, cleanup, parameter extraction, model deformation (based on simulation,) CAD-based data interpolation. In Phase-I, we built the CAD-hub of the proposed VTBM and demonstrated its use in modeling a liquid breeder blanket module with coupled MHD and structural mechanics using HIMAG and ANSYS. A complete graphical user interface of the VTBM was created, which will form the foundation of any future development. Conservative data interpolation via CAD (as opposed to mesh-based transfer), the regeneration of CAD models based upon computed deflections, are among the other highlights of phase-I activity.« less
Takaba, Masayuki; Tanaka, Shinpei; Ishiura, Yuichi; Baba, Kazuyoshi
2013-07-01
Recently, fixed dental prostheses (FDPs) with a hybrid structure of CAD/CAM porcelain crowns adhered to a CAD/CAM zirconia framework (PAZ) have been developed. The aim of this report was to describe the clinical application of a newly developed implant-supported FDP fabrication system, which uses PAZ, and to evaluate the outcome after a maximum application period of 36 months. Implants were placed in three patients with edentulous areas in either the maxilla or mandible. After the implant fixtures had successfully integrated with bone, gold-platinum alloy or zirconia custom abutments were first fabricated. Zirconia framework wax-up was performed on the custom abutments, and the CAD/CAM zirconia framework was prepared using the CAD/CAM system. Next, wax-up was performed on working models for porcelain crown fabrication, and CAD/CAM porcelain crowns were fabricated. The CAD/CAM zirconia frameworks and CAD/CAM porcelain crowns were bonded using adhesive resin cement, and the PAZ was cemented. Cementation of the implant superstructure improved the esthetics and masticatory efficiency in all patients. No undesirable outcomes, such as superstructure chipping, stomatognathic dysfunction, or periimplant bone resorption, were observed in any of the patients. PAZ may be a potential solution for ceramic-related clinical problems such as chipping and fracture and associated complicated repair procedures in implant-supported FDPs. © 2012 by the American College of Prosthodontists.
Cury, Ricardo C; Abbara, Suhny; Achenbach, Stephan; Agatston, Arthur; Berman, Daniel S; Budoff, Matthew J; Dill, Karin E; Jacobs, Jill E; Maroules, Christopher D; Rubin, Geoffrey D; Rybicki, Frank J; Schoepf, U Joseph; Shaw, Leslee J; Stillman, Arthur E; White, Charles S; Woodard, Pamela K; Leipsic, Jonathon A
2016-01-01
The intent of CAD-RADS - Coronary Artery Disease Reporting and Data System is to create a standardized method to communicate findings of coronary CT angiography (coronary CTA) in order to facilitate decision-making regarding further patient management. The suggested CAD-RADS classification is applied on a per-patient basis and represents the highest-grade coronary artery lesion documented by coronary CTA. It ranges from CAD-RADS 0 (Zero) for the complete absence of stenosis and plaque to CAD-RADS 5 for the presence of at least one totally occluded coronary artery and should always be interpreted in conjunction with the impression found in the report. Specific recommendations are provided for further management of patients with stable or acute chest pain based on the CAD-RADS classification. The main goal of CAD-RADS is to standardize reporting of coronary CTA results and to facilitate communication of test results to referring physicians along with suggestions for subsequent patient management. In addition, CAD-RADS will provide a framework of standardization that may benefit education, research, peer-review and quality assurance with the potential to ultimately result in improved quality of care. Copyright © 2016 Society of Cardiovascular Computed Tomography. Published by Elsevier Inc. All rights reserved.
Immunoglobulins against Tyrosine Nitrated Epitopes in Coronary Artery Disease
Thomson, Leonor; Tenopoulou, Margarita; Lightfoot, Richard; Tsika, Epida; Parastatidis, Ioannis; Martinez, Marissa; Greco, Todd M.; Doulias, Paschalis-Thomas; Wu, Yuping; Tang, W. H. Wilson; Hazen, Stanley L.; Ischiropoulos, Harry
2012-01-01
Background Several lines of evidence support a pathophysiological role of immunity in atherosclerosis. Tyrosine nitrated proteins, a footprint of oxygen and nitrogen derived oxidants generated by cells of the immune system, are enriched in atheromatous lesions and in circulation of coronary artery disease (CAD) subjects. However, the consequences of possible immune reactions triggered by the presence of nitrated proteins in subjects with clinically documented atherosclerosis have not been explored. Methods and Results Specific immunoglobulins that recognize 3-nitrotyrosine epitopes were identified in human lesions, as well as in circulation of CAD subjects. The levels of circulating immunoglobulins against 3-nitrotyrosine epitopes were quantified in CAD patients (n=374) and subjects without CAD (non CAD controls, n=313). A ten-fold increase in the mean level of circulating immunoglobulins against protein-bound 3-nitrotyrosine was documented in the CAD subjects (3.75 ± 1.8 μg antibody Eq/mL plasma vs. 0.36 ± 0.8 μg antibody Eq/mL plasma), and was strongly associated with angiographic evidence of significant CAD. Conclusions The results of this cross sectional study suggest that post-translational modification of proteins via nitration within atherosclerotic plaque-laden arteries and in circulation serve as neoepitopes for elaboration of immunoglobulins, thereby providing an association between oxidant production and the activation of the immune system in CAD. PMID:23081989
Representing spatial information in a computational model for network management
NASA Technical Reports Server (NTRS)
Blaisdell, James H.; Brownfield, Thomas F.
1994-01-01
While currently available relational database management systems (RDBMS) allow inclusion of spatial information in a data model, they lack tools for presenting this information in an easily comprehensible form. Computer-aided design (CAD) software packages provide adequate functions to produce drawings, but still require manual placement of symbols and features. This project has demonstrated a bridge between the data model of an RDBMS and the graphic display of a CAD system. It is shown that the CAD system can be used to control the selection of data with spatial components from the database and then quickly plot that data on a map display. It is shown that the CAD system can be used to extract data from a drawing and then control the insertion of that data into the database. These demonstrations were successful in a test environment that incorporated many features of known working environments, suggesting that the techniques developed could be adapted for practical use.
An esthetics rehabilitation with computer-aided design/ computer-aided manufacturing technology.
Mazaro, Josá Vitor Quinelli; de Mello, Caroline Cantieri; Zavanelli, Adriana Cristina; Santiago, Joel Ferreira; Amoroso, Andressa Paschoal; Pellizzer, Eduardo Piza
2014-07-01
This paper describes a case of a rehabilitation involving Computer Aided Design/Computer Aided Manufacturing (CAD-CAM) system in implant supported and dental supported prostheses using zirconia as framework. The CAD-CAM technology has developed considerably over last few years, becoming a reality in dental practice. Among the widely used systems are the systems based on zirconia which demonstrate important physical and mechanical properties of high strength, adequate fracture toughness, biocompatibility and esthetics, and are indicated for unitary prosthetic restorations and posterior and anterior framework. All the modeling was performed by using CAD-CAM system and prostheses were cemented using resin cement best suited for each situation. The rehabilitation of the maxillary arch using zirconia framework demonstrated satisfactory esthetic and functional results after a 12-month control and revealed no biological and technical complications. This article shows the important of use technology CAD/CAM in the manufacture of dental prosthesis and implant-supported.
NASA Astrophysics Data System (ADS)
Qiu, Yuchen; Lu, Xianglan; Yan, Shiju; Tan, Maxine; Cheng, Samuel; Li, Shibo; Liu, Hong; Zheng, Bin
2016-03-01
Automated high throughput scanning microscopy is a fast developing screening technology used in cytogenetic laboratories for the diagnosis of leukemia or other genetic diseases. However, one of the major challenges of using this new technology is how to efficiently detect the analyzable metaphase chromosomes during the scanning process. The purpose of this investigation is to develop a computer aided detection (CAD) scheme based on deep learning technology, which can identify the metaphase chromosomes with high accuracy. The CAD scheme includes an eight layer neural network. The first six layers compose of an automatic feature extraction module, which has an architecture of three convolution-max-pooling layer pairs. The 1st, 2nd and 3rd pair contains 30, 20, 20 feature maps, respectively. The seventh and eighth layers compose of a multiple layer perception (MLP) based classifier, which is used to identify the analyzable metaphase chromosomes. The performance of new CAD scheme was assessed by receiver operation characteristic (ROC) method. A number of 150 regions of interest (ROIs) were selected to test the performance of our new CAD scheme. Each ROI contains either interphase cell or metaphase chromosomes. The results indicate that new scheme is able to achieve an area under the ROC curve (AUC) of 0.886+/-0.043. This investigation demonstrates that applying a deep learning technique may enable to significantly improve the accuracy of the metaphase chromosome detection using a scanning microscopic imaging technology in the future.
Issues in assessing multi-institutional performance of BI-RADS-based CAD systems
NASA Astrophysics Data System (ADS)
Markey, Mia K.; Lo, Joseph Y.
2005-04-01
The purpose of this study was to investigate factors that impact the generalization of breast cancer computer-aided diagnosis (CAD) systems that utilize the Breast Imaging Reporting and Data System (BI-RADS). Data sets from four institutions were analyzed: Duke University Medical Center, University of Pennsylvania Medical Center, Massachusetts General Hospital, and Wake Forest University. The latter two data sets are subsets of the Digital Database for Screening Mammography. Each data set consisted of descriptions of mammographic lesions according to the BI-RADS lexicon, patient age, and pathology status (benign/malignant). Models were developed to predict pathology status from the BI-RADS descriptors and the patient age. Comparisons between the models built on data from the different institutions were made in terms of empirical (non-parametric) receiver operating characteristic (ROC) curves. Results suggest that BI-RADS-based CAD systems focused on specific classes of lesions may be more generally applicable than models that cover several lesion types. However, better generalization was seen in terms of the area under the ROC curve than in the partial area index (>90% sensitivity). Previous studies have illustrated the challenges in translating a BI-RADS-based CAD system from one institution to another. This study provides new insights into possible approaches to improve the generalization of BI-RADS-based CAD systems.
Web-based computer-aided-diagnosis (CAD) system for bone age assessment (BAA) of children
NASA Astrophysics Data System (ADS)
Zhang, Aifeng; Uyeda, Joshua; Tsao, Sinchai; Ma, Kevin; Vachon, Linda A.; Liu, Brent J.; Huang, H. K.
2008-03-01
Bone age assessment (BAA) of children is a clinical procedure frequently performed in pediatric radiology to evaluate the stage of skeletal maturation based on a left hand and wrist radiograph. The most commonly used standard: Greulich and Pyle (G&P) Hand Atlas was developed 50 years ago and exclusively based on Caucasian population. Moreover, inter- & intra-observer discrepancies using this method create a need of an objective and automatic BAA method. A digital hand atlas (DHA) has been collected with 1,400 hand images of normal children from Asian, African American, Caucasian and Hispanic descends. Based on DHA, a fully automatic, objective computer-aided-diagnosis (CAD) method was developed and it was adapted to specific population. To bring DHA and CAD method to the clinical environment as a useful tool in assisting radiologist to achieve higher accuracy in BAA, a web-based system with direct connection to a clinical site is designed as a novel clinical implementation approach for online and real time BAA. The core of the system, a CAD server receives the image from clinical site, processes it by the CAD method and finally, generates report. A web service publishes the results and radiologists at the clinical site can review it online within minutes. This prototype can be easily extended to multiple clinical sites and will provide the foundation for broader use of the CAD system for BAA.
Shah, R; Foldyna, B; Hoffmann, U
2016-08-01
The development of coronary artery disease (CAD) is a major, final common pathway in heart disease worldwide. With a rise in stress testing and increased scrutiny on cost-effectiveness and radiation exposure in medical imaging, a focus on the relative merits of anatomic versus functional characterization of CAD has emerged. In this context, coronary computed tomography angiography (CCTA) is a noninvasive alternative to functional testing as a first-line test for CAD detection but is complimentary in its nature. Here, we discuss the design, results, and implications of the PROMISE trial, a randomized comparative effectiveness study of 10,003 patients across 193 sites in the United States and Canada comparing the prognostic and diagnostic power of CCTA and standard stress testing. Specifically, we discuss the safety (e. g., contrast, radiation exposure) of CCTA versus functional testing in CAD, the need for improved selection for noninvasive testing, the frequency of downstream testing after anatomic or functional imaging, the use of imaging results in clinical management, and novel modalities of CAD risk determination using CCTA. PROMISE demonstrated that in a real-world, low-to-intermediate risk patient population referred to noninvasive testing for CAD, both CCTA and functional testing approaches have similar clinical, economic, and safety-based outcomes. We conclude with open questions in CAD imaging, specifically as they pertain to the utilization of CCTA.
Lee, Sang-Eun; Uhm, Jae-Sun; Kim, Jong-Youn; Pak, Hui-Nam; Lee, Moon-Hyoung; Joung, Boyoung
2015-07-01
Acute coronary lesions commonly trigger out-of-hospital cardiac arrest (OHCA). However, the prevalence of coronary artery disease (CAD) in Asian patients with OHCA and whether electrocardiogram (ECG) and other findings might predict acute myocardial infarction (AMI) have not been fully elucidated. Of 284 consecutive resuscitated OHCA patients seen between January 2006 and July 2013, we enrolled 135 patients who had undergone coronary evaluation. ECGs, echocardiography, and biomarkers were compared between patients with or without CAD. We included 135 consecutive patients aged 54 years (interquartile range 45-65) with sustained return of spontaneous circulation after OHCA between 2006 and 2012. Sixty six (45%) patients had CAD. The initial rhythm was shockable and non-shockable in 110 (81%) and 25 (19%) patients, respectively. ST-segment elevation predicted CAD with 42% sensitivity, 87% specificity, and 65% accuracy. ST elevation and/or regional wall motion abnormality (RWMA) showed 68% sensitivity, 52% specificity, and 70% accuracy in the prediction of CAD. Finally, a combination of ST elevation and/or RWMA and/or troponin T elevation predicted CAD with 94% sensitivity, 17% specificity, and 55% accuracy. In patients with OHCA without obvious non-cardiac causes, selection for coronary angiogram based on the combined criterion could detect 94% of CADs. However, compared with ECG only criteria, the combined criterion failed to improve diagnostic accuracy with a lower specificity.
Huebner, Thomas; Goernig, Matthias; Schuepbach, Michael; Sanz, Ernst; Pilgram, Roland; Seeck, Andrea; Voss, Andreas
2010-01-01
Background: Electrocardiographic methods still provide the bulk of cardiovascular diagnostics. Cardiac ischemia is associated with typical alterations in cardiac biosignals that have to be measured, analyzed by mathematical algorithms and allegorized for further clinical diagnostics. The fast growing fields of biomedical engineering and applied sciences are intensely focused on generating new approaches to cardiac biosignal analysis for diagnosis and risk stratification in myocardial ischemia. Objectives: To present and review the state of the art in and new approaches to electrocardiologic methods for non-invasive detection and risk stratification in coronary artery disease (CAD) and myocardial ischemia; secondarily, to explore the future perspectives of these methods. Methods: In follow-up to the Expert Discussion at the 2008 Workshop on "Biosignal Analysis" of the German Society of Biomedical Engineering in Potsdam, Germany, we comprehensively searched the pertinent literature and databases and compiled the results into this review. Then, we categorized the state-of-the-art methods and selected new approaches based on their applications in detection and risk stratification of myocardial ischemia. Finally, we compared the pros and cons of the methods and explored their future potentials for cardiology. Results: Resting ECG, particularly suited for detecting ST-elevation myocardial infarctions, and exercise ECG, for the diagnosis of stable CAD, are state-of-the-art methods. New exercise-free methods for detecting stable CAD include cardiogoniometry (CGM); methods for detecting acute coronary syndrome without ST elevation are Body Surface Potential Mapping, functional imaging and CGM. Heart rate variability and blood pressure variability analyses, microvolt T-wave alternans and signal-averaged ECG mainly serve in detecting and stratifying the risk for lethal arrythmias in patients with myocardial ischemia or previous myocardial infarctions. Telemedicine and ambient-assisted living support the electrocardiological monitoring of at-risk patients. Conclusions: There are many promising methods for the exercise-free, non-invasive detection of CAD and myocardial ischemia in the stable and acute phases. In the coming years, these new methods will help enhance state-of-the-art procedures in routine diagnostics. The future can expect that equally novel methods for risk stratification and telemedicine will transition into clinical routine. PMID:21063467
Evolution of Geometric Sensitivity Derivatives from Computer Aided Design Models
NASA Technical Reports Server (NTRS)
Jones, William T.; Lazzara, David; Haimes, Robert
2010-01-01
The generation of design parameter sensitivity derivatives is required for gradient-based optimization. Such sensitivity derivatives are elusive at best when working with geometry defined within the solid modeling context of Computer-Aided Design (CAD) systems. Solid modeling CAD systems are often proprietary and always complex, thereby necessitating ad hoc procedures to infer parameter sensitivity. A new perspective is presented that makes direct use of the hierarchical associativity of CAD features to trace their evolution and thereby track design parameter sensitivity. In contrast to ad hoc methods, this method provides a more concise procedure following the model design intent and determining the sensitivity of CAD geometry directly to its respective defining parameters.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Womersley, J.; DiGiacomo, N.; Killian, K.
1990-04-01
Detailed detector design has traditionally been divided between engineering optimization for structural integrity and subsequent physicist evaluation. The availability of CAD systems for engineering design enables the tasks to be integrated by providing tools for particle simulation within the CAD system. We believe this will speed up detector design and avoid problems due to the late discovery of shortcomings in the detector. This could occur because of the slowness of traditional verification techniques (such as detailed simulation with GEANT). One such new particle simulation tool is described. It is being used with the I-DEAS CAD package for SSC detector designmore » at Martin-Marietta Astronautics and is to be released through the SSC Laboratory.« less
Impact of inflammation, gene variants, and cigarette smoking on coronary artery disease risk.
Merhi, Mahmoud; Demirdjian, Sally; Hariri, Essa; Sabbah, Nada; Youhanna, Sonia; Ghassibe-Sabbagh, Michella; Naoum, Joseph; Haber, Marc; Othman, Raed; Kibbani, Samer; Chammas, Elie; Kanbar, Roy; Bayeh, Hamid El; Chami, Youssef; Abchee, Antoine; Platt, Daniel E; Zalloua, Pierre; Khazen, Georges
2015-06-01
The role of inflammation in coronary artery disease (CAD) pathogenesis is well recognized. Moreover, smoking inhalation increases the activity of inflammatory mediators through an increase in leukotriene synthesis essential in atherosclerosis pathogenesis. The aim of this study is to investigate the effect of "selected" genetic variants within the leukotriene (LT) pathway and other variants on the development of CAD. CAD was detected by cardiac catheterization. Logistic regression was performed to investigate the association of smoking and selected susceptibility variants in the LT pathway including ALOX5AP, LTA4H, LTC4S, PON1, and LTA as well as CYP1A1 on CAD risk while controlling for age, gender, BMI, family history, diabetes, hyperlipidemia, and hypertension. rs4769874 (ALOX5AP), rs854560 (PON1), and rs4646903 (CYP1A1 MspI polymorphism) are significantly associated with an increased risk of CAD with respective odds ratios of 1.53703, 1.67710, and 1.35520; the genetic variant rs9579646 (ALOX5AP) is significantly associated with a decreased risk of CAD (OR 0.76163). Moreover, a significant smoking-gene interaction is determined with CYP1A1 MspI polymorphism rs4646903 and is associated with a decreased risk of CAD in current smokers (OR 0.52137). This study provides further evidence that genetic variation of the LT pathway, PON1, and CYP1A1 can modulate the atherogenic processes and eventually increase the risk of CAD in our study population. Moreover, it also shows the effect of smoking-gene interaction on CAD risk, where the CYP1A1 MspI polymorphism revealed a decreased risk in current smokers.
Relationship of dental diseases with coronary artery diseases and diabetes in Bangladesh
Choudhury, Arup Ratan; Choudhury, Kamrun Nahar
2016-01-01
Background Evidence suggests that dental diseases might have a role in the development and progression of coronary artery diseases (CAD) and diabetes mellitus (DM). The objective of this study was to determine the relationship of dental diseases with CAD and DM in Bangladesh. Methods We conducted a cross-sectional study among 216 consecutive patients admitted in a tertiary hospital between March and July 2011. Data were collected on socio-demographic status, smoking, blood pressure (BP), diet, physical activities, and biochemical measurements of lipid profile, glycated hemoglobin (HbA1c), C-reactive protein (CRP), fibrinogen, creatinine kinase MB (CK-MB), troponin, serum creatinine and serum glutamic-pyruvic transaminase (SGPT). CAD was detected using echocardiographic and coronary angiogram (CAG) reports. All patients underwent oral examination for dental disease. Relationship between dental disease with CAD and DM were explored statistically. Results The mean age of the participants was 57.8±12.5 years and almost two-thirds (67.1%) were male. A great majority of the patients had CAD (90.3%) and type 2 DM (83.8%), and only 44% suffered from dental diseases. Less than one-third patients presented with acute myocardial infarction (MI), 23% with old MI, 11% unstable angina (UA) and 26.4% with non-ST elevation MI. Logistic regression results indicated that patients with DM and CAD had approximately 2.6 and 4.6 times more odds of association with dental diseases than those without DM and CAD (both P value <0.001). Conclusions This study suggests a relationship of dental diseases with CAD and DM among Bangladeshi patients. Further studies are required to confirm these relationships in large clinical studies. Screening for CAD and DM should be considered among those with dental diseases and vice-versa. PMID:27054102
Pirat, Bahar; Yildirir, Aylin; Simşek, Vahide; Ozin, Bülent; Müderrisoğlu, Haldun
2008-03-01
We investigated the effect of increased preload through postural changes (leg lifting) on tissue Doppler parameters in patients with and without coronary artery disease (CAD). The study included 42 patients who were scheduled for coronary angiography. All the patients underwent standard two-dimensional, color Doppler and tissue Doppler echocardiography before coronary angiography. Tissue Doppler imaging was performed from septal and lateral mitral annuluses at baseline and during 45 degrees leg lifting followed by two-minute stabilization. Patients were grouped based on coronary angiography findings: those having stenosis greater than 70% were considered to have CAD and those with normal coronary arteries comprised the control group. Echocardiography measurements were compared between the two groups. Angiography showed normal coronary arteries or border irregularities in 22 patients and CAD in 20 patients. The two groups were similar with regard to demographic data and ejection fractions, except for male preponderance in the CAD group. Compared with the control group, patients with CAD exhibited a significantly lower isovolumic acceleration rate (IVA) at the lateral (p=0.007) and septal (p=0.03) mitral annuluses. In the control group, leg lifting resulted in increased systolic velocity (S) compared with baseline at the lateral (p=0.009) and septal (p=0.01) annuluses, whereas S wave augmentation was only significant at the septal annulus (p=0.009) in patients with CAD. No significant change was observed in IVA following leg lifting in both groups. Preload alteration induced by leg lifting resulted in similar changes in tissue Doppler parameters in patients with and without CAD, except for blunted augmentation of S wave at the lateral annulus in CAD. Detection of decreased IVA at baseline may be a useful finding for CAD.
Computer-Aided Design in Further Education.
ERIC Educational Resources Information Center
Ingham, Peter, Ed.
This publication updates the 1982 occasional paper that was intended to foster staff awareness and assist colleges in Great Britain considering the use of computer-aided design (CAD) material in engineering courses. The paper begins by defining CAD and its place in the Integrated Business System with a brief discussion of the effect of CAD on the…
Do CAD/CAM dentures really release less monomer than conventional dentures?
Steinmassl, Patricia-Anca; Wiedemair, Verena; Huck, Christian; Klaunzer, Florian; Steinmassl, Otto; Grunert, Ingrid; Dumfahrt, Herbert
2017-06-01
Computer-aided design (CAD)/computer-aided manufacturing (CAM) dentures are assumed to have more favourable material properties than conventionally fabricated dentures, among them a lower methacrylate monomer release. The aim of this study was to test this hypothesis. CAD/CAM dentures were generated from ten different master casts by using four different CAD/CAM systems. Conventional, heat-polymerised dentures served as control group. Denture weight and volume were measured; the density was calculated, and the denture surface area was assessed digitally. The monomer release after 7 days of water storage was measured by high-performance liquid chromatography. Whole You Nexteeth and Wieland Digital Dentures had significantly lower mean volume and weight than conventional dentures. Baltic Denture System and Whole You Nexteeth had a significantly increased density. Baltic Denture System had a significantly smaller surface area. None of the CAD/CAM dentures released significantly less monomer than the control group. All tested dentures released very low amounts of methacrylate monomer, but not significantly less than conventional dentures. A statistically significant difference might nevertheless exist in comparison to other, less recommendable denture base materials, such as the frequently used autopolymerising resins. CAD/CAM denture fabrication has numerous advantages. It enables the fabrication of dentures with lower resin volume and lower denture weight. Both could increase the patient comfort. Dentures with higher density might exhibit more favourable mechanical properties. The hypothesis that CAD/CAM dentures release less monomer than conventional dentures could, however, not be verified.
A CAD system and quality assurance protocol for bone age assessment utilizing digital hand atlas
NASA Astrophysics Data System (ADS)
Gertych, Arakadiusz; Zhang, Aifeng; Ferrara, Benjamin; Liu, Brent J.
2007-03-01
Determination of bone age assessment (BAA) in pediatric radiology is a task based on detailed analysis of patient's left hand X-ray. The current standard utilized in clinical practice relies on a subjective comparison of the hand with patterns in the book atlas. The computerized approach to BAA (CBAA) utilizes automatic analysis of the regions of interest in the hand image. This procedure is followed by extraction of quantitative features sensitive to skeletal development that are further converted to a bone age value utilizing knowledge from the digital hand atlas (DHA). This also allows providing BAA results resembling current clinical approach. All developed methodologies have been combined into one CAD module with a graphical user interface (GUI). CBAA can also improve the statistical and analytical accuracy based on a clinical work-flow analysis. For this purpose a quality assurance protocol (QAP) has been developed. Implementation of the QAP helped to make the CAD more robust and find images that cannot meet conditions required by DHA standards. Moreover, the entire CAD-DHA system may gain further benefits if clinical acquisition protocol is modified. The goal of this study is to present the performance improvement of the overall CAD-DHA system with QAP and the comparison of the CAD results with chronological age of 1390 normal subjects from the DHA. The CAD workstation can process images from local image database or from a PACS server.
JAMSTEC Compact Arctic Drifter (J-CAD): A new Generation drifting buoy to observe the Arctic Ocean
NASA Astrophysics Data System (ADS)
Hatakeyama, Kiyoshi; Hosono, Masuo; Shimada, Koji; Kikuchi, Takashi; Nishino, Shigeto
The Arctic Ocean is one of the most sensitive regions to the earth environment changes. Japan Marine Science and Technology Center developed a new drift buoy to observe the Arctic Ocean. The name of the buoy is J-CAD (JAMSTEC Compact Arctic Drifter). From 1991 to 1993, JAMSTEC developed Ice-Ocean Environmental Buoy (IOEB) as a buoy to observe the Arctic Ocean in cooperation with Woods Hole Oceanographic Institution. The J-CAD is the buoy, which adopted the latest technology based on the knowledge and experience of IOEB development. The J-CAD was designed and developed by JAMSTEC and made by a Canadian Company MetOcean. JAMSTEC did design and development, and a Canadian company Met-Ocean made the J-CAD. It acquires meteorological and oceanographic data of the Arctic Ocean, and transmits the data that it measured via satellite. It dose also store the data inside its memory. An Inductive Modem system, which was developed by Sea-Bird Electronics, Inc. in the United States, was adopted in the underwater transmission system that data on each ocean sensor were collected. An ORBCOMM communication system was adopted for the satellite data transmission. J-CAD-1 was installed at 89°41'N 130°20'W on April 24, 2000, and the observation was started. August 1st was the day when 100 days have passed since the J-CAD-1 was installed on the North Pole. And now, the distance J-CAD-1 has covered exceeds 400 km, and it has transmitted data more than 500 k byte. A part of the data is introduced to the public in the homepage (http://w3.jamstec.go.jp: 8338) of the Arctic research group of JAMSTEC.
NASA Technical Reports Server (NTRS)
Afjeh, Abdollah A.; Reed, John A.
2003-01-01
Mesh generation has long been recognized as a bottleneck in the CFD process. While much research on automating the volume mesh generation process have been relatively successful,these methods rely on appropriate initial surface triangulation to work properly. Surface discretization has been one of the least automated steps in computational simulation due to its dependence on implicitly defined CAD surfaces and curves. Differences in CAD peometry engines manifest themselves in discrepancies in their interpretation of the same entities. This lack of "good" geometry causes significant problems for mesh generators, requiring users to "repair" the CAD geometry before mesh generation. The problem is exacerbated when CAD geometry is translated to other forms (e.g., IGES )which do not include important topological and construction information in addition to entity geometry. One technique to avoid these problems is to access the CAD geometry directly from the mesh generating software, rather than through files. By accessing the geometry model (not a discretized version) in its native environment, t h s a proach avoids translation to a format which can deplete the model of topological information. Our approach to enable models developed in the Denali software environment to directly access CAD geometry and functions is through an Application Programming Interface (API) known as CAPRI. CAPRI provides a layer of indirection through which CAD-specific data may be accessed by an application program using CAD-system neutral C and FORTRAN language function calls. CAPRI supports a general set of CAD operations such as truth testing, geometry construction and entity queries.
Karabuva, Svjetlana; Carević, Vedran; Radić, Mislav; Fabijanić, Damir
2013-01-01
The aim of study was to: 1) examine the relationship between ABO blood groups and extent of coronary atherosclerosis in patients with chronic coronary artery disease (CAD), 2) compare ABO blood groups distribution in CAD patients and general population, 3) examine possible differences in traditional risk factors frequency in CAD patients with different ABO blood groups. In the 646 chronic CAD patients (72.4% males) coronary angiograms were scored by quantitative assessment using multiple angiographic scoring system, Traditional risk factors were self reported or measured by standard methods. ABO blood distribution of patients was compared with group of 651 healthy blood donors (74.6% males). Among all ABO blood group patients there was no significant difference between the extent of coronary atherosclerosis with regard to all the three scoring systems: number of affected coronary arteries (P = 0.857), Gensini score (P = 0.818), and number of segments narrowed > 50% (P = 0.781). There was no significant difference in ABO blood group distribution between CAD patients and healthy blood donors. Among CAD patients, men with blood group AB were significantly younger than their pairs with non-AB blood groups (P = 0.008). Among CAD patients with AB blood group, males < 50 yrs were significantly overrepresented when compared with the non-AB groups (P = 0.003). No association between ABO blood groups and the extent of coronary atherosclerosis in Croatian CAD patients is observed. Observation that AB blood group might possibly identify Croatian males at risk to develop the premature CAD has to be tested in larger cohort of patients.
Complete Dentures Fabricated with CAD/CAM Technology and a Traditional Clinical Recording Method.
Janeva, Nadica; Kovacevska, Gordana; Janev, Edvard
2017-10-15
The introduction of computer-aided design/computer-aided manufacturing (CAD/CAM) technology into complete denture (CD) fabrication ushered in a new era in removable prosthodontics. Commercially available CAD/CAM denture systems are expected to improve upon the disadvantages associated with conventional fabrication. The purpose of this report is to present the workflow involved in fabricating a CD with a traditional clinical recording method and CAD/CAM technology and to summarize the advantages to the dental practitioner and the patient.
Bahit, Maria Cecilia; Lopes, Renato D; Wojdyla, Daniel M; Hohnloser, Stefan H; Alexander, John H; Lewis, Basil S; Aylward, Philip E; Verheugt, Freek W A; Keltai, Matyas; Diaz, Rafael; Hanna, Michael; Granger, Christopher B; Wallentin, Lars
2013-12-10
A substantial portion of patients with atrial fibrillation (AF) also have coronary artery disease (CAD) and are at risk for coronary events. Warfarin is known to reduce these events, but increase the risk of bleeding. We assessed the effects of apixaban compared with warfarin in AF patients with and without prior CAD. In ARISTOTLE, 18,201 patients with AF were randomized to apixaban or warfarin. History of CAD was defined as documented CAD, prior myocardial infarction, and/or history of coronary revascularization. We analyzed baseline characteristics and clinical outcomes of patients with and without prior CAD and compared outcomes by randomized treatment using Cox models. A total of 6639 (36.5%) patients had prior CAD. These patients were more often male, more likely to have prior stroke, diabetes, and hypertension, and more often received aspirin at baseline (42.2% vs. 24.5%). The effects of apixaban were similar among patients with and without prior CAD on reducing stroke or systemic embolism and death from any cause (hazard ratio [HR] 0.95, 95% confidence interval [CI] 0.71-1.27, P for interaction=0.12; HR 0.96, 95% CI 0.81-1.13, P for interaction=0.28). Rates of myocardial infarction were numerically lower with apixaban than warfarin among patients with and without prior CAD. The effect of apixaban on reducing major bleeding and intracranial hemorrhage was consistent in patients with and without CAD. In patients with AF, apixaban more often prevented stroke or systemic embolism and death and caused less bleeding than warfarin, regardless of the presence of prior CAD. Given the common occurrence of AF and CAD and the higher rates of cardiovascular events and death, our results indicate that apixaban may be a better treatment option than warfarin for these high-risk patients. © 2013.
Improving aircraft conceptual design - A PHIGS interactive graphics interface for ACSYNT
NASA Technical Reports Server (NTRS)
Wampler, S. G.; Myklebust, A.; Jayaram, S.; Gelhausen, P.
1988-01-01
A CAD interface has been created for the 'ACSYNT' aircraft conceptual design code that permits the execution and control of the design process via interactive graphics menus. This CAD interface was coded entirely with the new three-dimensional graphics standard, the Programmer's Hierarchical Interactive Graphics System. The CAD/ACSYNT system is designed for use by state-of-the-art high-speed imaging work stations. Attention is given to the approaches employed in modeling, data storage, and rendering.
Stona, Deborah; Burnett, Luiz Henrique; Mota, Eduardo Gonçalves; Spohr, Ana Maria
2015-07-01
Because no information was found in the dental literature regarding the fracture resistance of all-ceramic crowns using CEREC (Sirona) computer-aided design and computer-aided manufacturing (CAD-CAM) system on solid abutments, the authors conducted a study. Sixty synOcta (Straumann) implant replicas and regular neck solid abutments were embedded in acrylic resin and randomly assigned (n = 20 per group). Three types of ceramics were used: feldspathic, CEREC VITABLOCS Mark II (VITA); leucite, IPS Empress CAD (Ivoclar Vivadent); and lithium disilicate, IPS e.max CAD (Ivoclar Vivadent). The crowns were fabricated by the CEREC CAD-CAM system. After receiving glaze, the crowns were cemented with RelyX U200 (3M ESPE) resin cement under load of 1 kilogram. For each ceramic, one-half of the specimens were subjected to the fracture resistance testing in a universal testing machine with a crosshead speed of 1 millimeter per minute, and the other half were subjected to the fractured resistance testing after 1,000,000 cyclic fatigue loading at 100 newtons. According to a 2-way analysis of variance, the interaction between the material and mechanical cycling was significant (P = .0001). According to a Tukey test (α = .05), the fracture resistance findings with or without cyclic fatigue loading were as follows, respectively: CEREC VITABLOCKS Mark II (405 N/454 N) was statistically lower than IPS Empress CAD (1169 N/1240 N) and IPS e.max CAD (1378 N/1025 N) (P < .05). The IPS Empress CAD and IPS e.max CAD did not differ statistically (P > .05). According to a t test, there was no statistical difference in the fracture resistance with and without cyclic fatigue loading for CEREC VITABLOCS Mark II and IPS Empress CAD (P > .05). For IPS e.max CAD, the fracture resistance without cyclic fatigue loading was statistically superior to that obtained with cyclic fatigue loading (P < .05). The IPS Empress CAD and IPS e.max CAD showed higher fracture resistance compared with CEREC VITABLOCS Mark II. The cyclic fatigue loading negatively influenced only IPS e.max CAD. The CEREC VITABLOCS Mark II, IPS Empress CAD, and IPS e.max CAD ceramic crowns cemented on solid abutments showed sufficient resistance to withstand normal chewing forces. Copyright © 2015 American Dental Association. Published by Elsevier Inc. All rights reserved.
BioNetCAD: design, simulation and experimental validation of synthetic biochemical networks
Rialle, Stéphanie; Felicori, Liza; Dias-Lopes, Camila; Pérès, Sabine; El Atia, Sanaâ; Thierry, Alain R.; Amar, Patrick; Molina, Franck
2010-01-01
Motivation: Synthetic biology studies how to design and construct biological systems with functions that do not exist in nature. Biochemical networks, although easier to control, have been used less frequently than genetic networks as a base to build a synthetic system. To date, no clear engineering principles exist to design such cell-free biochemical networks. Results: We describe a methodology for the construction of synthetic biochemical networks based on three main steps: design, simulation and experimental validation. We developed BioNetCAD to help users to go through these steps. BioNetCAD allows designing abstract networks that can be implemented thanks to CompuBioTicDB, a database of parts for synthetic biology. BioNetCAD enables also simulations with the HSim software and the classical Ordinary Differential Equations (ODE). We demonstrate with a case study that BioNetCAD can rationalize and reduce further experimental validation during the construction of a biochemical network. Availability and implementation: BioNetCAD is freely available at http://www.sysdiag.cnrs.fr/BioNetCAD. It is implemented in Java and supported on MS Windows. CompuBioTicDB is freely accessible at http://compubiotic.sysdiag.cnrs.fr/ Contact: stephanie.rialle@sysdiag.cnrs.fr; franck.molina@sysdiag.cnrs.fr Supplementary information: Supplementary data are available at Bioinformatics online. PMID:20628073
Integrative Genomics Reveals Novel Molecular Pathways and Gene Networks for Coronary Artery Disease
Mäkinen, Ville-Petteri; Civelek, Mete; Meng, Qingying; Zhang, Bin; Zhu, Jun; Levian, Candace; Huan, Tianxiao; Segrè, Ayellet V.; Ghosh, Sujoy; Vivar, Juan; Nikpay, Majid; Stewart, Alexandre F. R.; Nelson, Christopher P.; Willenborg, Christina; Erdmann, Jeanette; Blakenberg, Stefan; O'Donnell, Christopher J.; März, Winfried; Laaksonen, Reijo; Epstein, Stephen E.; Kathiresan, Sekar; Shah, Svati H.; Hazen, Stanley L.; Reilly, Muredach P.; Lusis, Aldons J.; Samani, Nilesh J.; Schunkert, Heribert; Quertermous, Thomas; McPherson, Ruth; Yang, Xia; Assimes, Themistocles L.
2014-01-01
The majority of the heritability of coronary artery disease (CAD) remains unexplained, despite recent successes of genome-wide association studies (GWAS) in identifying novel susceptibility loci. Integrating functional genomic data from a variety of sources with a large-scale meta-analysis of CAD GWAS may facilitate the identification of novel biological processes and genes involved in CAD, as well as clarify the causal relationships of established processes. Towards this end, we integrated 14 GWAS from the CARDIoGRAM Consortium and two additional GWAS from the Ottawa Heart Institute (25,491 cases and 66,819 controls) with 1) genetics of gene expression studies of CAD-relevant tissues in humans, 2) metabolic and signaling pathways from public databases, and 3) data-driven, tissue-specific gene networks from a multitude of human and mouse experiments. We not only detected CAD-associated gene networks of lipid metabolism, coagulation, immunity, and additional networks with no clear functional annotation, but also revealed key driver genes for each CAD network based on the topology of the gene regulatory networks. In particular, we found a gene network involved in antigen processing to be strongly associated with CAD. The key driver genes of this network included glyoxalase I (GLO1) and peptidylprolyl isomerase I (PPIL1), which we verified as regulatory by siRNA experiments in human aortic endothelial cells. Our results suggest genetic influences on a diverse set of both known and novel biological processes that contribute to CAD risk. The key driver genes for these networks highlight potential novel targets for further mechanistic studies and therapeutic interventions. PMID:25033284
Research on AutoCAD secondary development and function expansion based on VBA technology
NASA Astrophysics Data System (ADS)
Zhang, Runmei; Gu, Yehuan
2017-06-01
AutoCAD is the most widely used drawing tool among the similar design drawing products. In the process of drawing different types of design drawings of the same product, there are a lot of repetitive and single work contents. The traditional manual method uses a drawing software AutoCAD drawing graphics with low efficiency, high error rate and high input cost shortcomings and many more. In order to solve these problems, the design of the parametric drawing system of the hot-rolled I-beam (steel beam) cross-section is completed by using the VBA secondary development tool and the Access database software with large-capacity storage data, and the analysis of the functional extension of the plane drawing and the parametric drawing design in this paper. For the secondary development of AutoCAD functions, the system drawing work will be simplified and work efficiency also has been greatly improved. This introduction of parametric design of AutoCAD drawing system to promote the industrial mass production and related industries economic growth rate similar to the standard I-beam hot-rolled products.
Meyer, Carsten; Strach, Katharina; Thomas, Daniel; Litt, Harold; Nähle, Claas P; Tiemann, Klaus; Schwenger, Ulrich; Schild, Hans H; Sommer, Torsten
2008-02-01
To implement a high-resolution first-pass myocardial perfusion imaging protocol (HRPI) at 3 T, and to evaluate the feasibility, image quality and accuracy of this approach prospectively in patients with suspected CAD. We hypothesized that utilizing the gain in SNR at 3 T to increase spatial resolution would reduce partial volume effects and subendocardial dark rim artifacts in comparison to 1.5 T. HRPI studies were performed on 60 patients using a segmented k-space gradient echo sequence (in plane resolution 1.97 x 1.94 mm(2)). Semiquantitative assessment of dark rim artifacts was performed for the stress studies on a slice-by-slice basis. Qualitative visual analysis was compared to quantitative coronary angiography (QCA) results; hemodynamically significant CAD was defined as stenosis >or=70% at QCA. Dark rim artifacts appeared in 108 of 180 slices (average extent 1.3 +/- 1.2 mm representing 11.8 +/- 10.8% of the transmural myocardial thickness). Sensitivity, specifity, and test accuracy for the detection of significant CAD were 89%,79%, and 85%. HRPI studies at 3 T are feasible in a clinical setting, providing good image quality and high accuracy for detection of significant CAD. The presence of dark rim artifacts does not appear to represent a diagnostic problem when using a HRPI approach.
Experimental CAD Course Uses Low-Cost Systems.
ERIC Educational Resources Information Center
Wohlers, Terry
1984-01-01
Describes the outstanding results obtained when a department of industrial sciences used special software on microcomputers to teach computer-aided design (CAD) as an alternative to much more expensive equipment. The systems used and prospects for the future are also considered. (JN)
Systemic inflammation is higher in peripheral artery disease than in stable coronary artery disease.
Rein, Philipp; Saely, Christoph H; Silbernagel, Günther; Vonbank, Alexander; Mathies, Rainer; Drexel, Heinz; Baumgartner, Iris
2015-04-01
The knowledge on the level of systemic inflammation in peripheral artery disease (PAD) is less well established than that in coronary artery disease (CAD). Systemic inflammation frequently coincides with atherosclerosis, but also with various traits of the metabolic syndrome (MetS). The individual contribution of CAD, PAD, and the MetS to inflammation is not known. We enrolled a total of 1396 patients, 460 patients with PAD Fontaine stages IIa-IV verified by duplex ultrasound (PAD group) and 936 patients free of limb claudication undergoing coronary angiography, of whom 507 had significant CAD with coronary stenoses ≥50% (CAD group), and 429 did not have significant CAD at angiography (control group). C-reactive protein (CRP) was significantly higher in the PAD than in the CAD or in the control group (0.86 ± 1.85 mg/dl versus 0.44 ± 0.87 mg/dl and 0.39 ± 0.52 mg/dl, respectively, p < 0.001 for both comparisons). These significant differences were confirmed when patients with and subjects without the MetS were analyzed separately. In particular, within the PAD group, CRP was significantly higher in patients with the MetS than in subjects without the MetS (1.04 ± 2.01 vs. 0.67 ± 1.64 mg/dl; p = 0.001) and both, the presence of PAD and the MetS proved to be independently associated with CRP in analysis of covariance (F = 31.84; p < 0.001 and F = 10.52; p = 0.001, respectively). Inflammatory activity in PAD patients is higher than in CAD patients and is particularly high in PAD patients affected by the MetS. Low grade systemic inflammation is independently associated with both the MetS and PAD. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.
Shen, Qing; Lu, Yanbin; Dai, Zhiyuan; Cheung, Hon-Yeung
2015-01-01
A precursor ion scan (PIS) technique based strategy was developed for rapid screening and semi-determination of caffeoylquinic acid derivatives (CADs) in artichoke (Cynara scolymus L.) using ultra-performance liquid chromatography (UPLC) coupled with tandem mass spectrometry. 1,5-Dicaffeoylquinic acid and 5-caffeoylquinic acid were used for studying the fragmentation behaviour of two classes of CADs, setting m/z 191 as a diagnostic moiety. When it was applied to artichoke sample, ten CADs were detected and elucidated in a single PIS run. Furthermore, method validation was implemented including: specificity (no interference), linearity (≥0.9993), limit of detection (LOD<0.12 ng mL(-1)) and limit of quantification (LOQ<0.25 ng mL(-1)), precision (RSD≤3.6), recovery (91.4-95.9%) and stability (at least 12 h). This approach was proven to be a powerful, selective and sensitive tool for rapid screening and semi-determination of untargeted components in natural products. Copyright © 2014 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Ciany, Charles M.; Zurawski, William; Kerfoot, Ian
2001-10-01
The performance of Computer Aided Detection/Computer Aided Classification (CAD/CAC) Fusion algorithms on side-scan sonar images was evaluated using data taken at the Navy's's Fleet Battle Exercise-Hotel held in Panama City, Florida, in August 2000. A 2-of-3 binary fusion algorithm is shown to provide robust performance. The algorithm accepts the classification decisions and associated contact locations form three different CAD/CAC algorithms, clusters the contacts based on Euclidian distance, and then declares a valid target when a clustered contact is declared by at least 2 of the 3 individual algorithms. This simple binary fusion provided a 96 percent probability of correct classification at a false alarm rate of 0.14 false alarms per image per side. The performance represented a 3.8:1 reduction in false alarms over the best performing single CAD/CAC algorithm, with no loss in probability of correct classification.
Anderson, Daniel R; Duryee, Michael J; Shurmur, Scott W; Um, John Y; Bussey, Walter D; Hunter, Carlos D; Garvin, Robert P; Sayles, Harlan R; Mikuls, Ted R; Klassen, Lynell W; Thiele, Geoffrey M
2014-01-01
Malondialdehyde-acetaldehyde adducts (MAA) have been implicated in atherosclerosis. The purpose of this study was to investigate the role of MAA in atherosclerotic disease. Serum samples from controls (n = 82) and patients with; non-obstructive coronary artery disease (CAD), (n = 40), acute myocardial infarction (AMI) (n = 42), or coronary artery bypass graft (CABG) surgery due to obstructive multi-vessel CAD (n = 72), were collected and tested for antibody isotypes to MAA-modifed human serum albumin (MAA-HSA). CAD patients had elevated relative levels of IgG and IgA anti-MAA, compared to control patients (p<0.001). AMI patients had a significantly increased relative levels of circulating IgG anti-MAA-HSA antibodies as compared to stable angina (p<0.03) or CABG patients (p<0.003). CABG patients had significantly increased relative levels of circulating IgA anti-MAA-HSA antibodies as compared to non-obstructive CAD (p<0.001) and AMI patients (p<0.001). Additionally, MAA-modified proteins were detected in the tissue of human AMI lesions. In conclusion, the IgM, IgG and IgA anti-MAA-HSA antibody isotypes are differentially and significantly associated with non-obstructive CAD, AMI, or obstructive multi-vessel CAD and may serve as biomarkers of atherosclerotic disease.
Anderson, Daniel R.; Duryee, Michael J.; Shurmur, Scott W.; Um, John Y.; Bussey, Walter D.; Hunter, Carlos D.; Garvin, Robert P.; Sayles, Harlan R.; Mikuls, Ted R.; Klassen, Lynell W.; Thiele, Geoffrey M.
2014-01-01
Malondialdehyde-acetaldehyde adducts (MAA) have been implicated in atherosclerosis. The purpose of this study was to investigate the role of MAA in atherosclerotic disease. Serum samples from controls (n = 82) and patients with; non-obstructive coronary artery disease (CAD), (n = 40), acute myocardial infarction (AMI) (n = 42), or coronary artery bypass graft (CABG) surgery due to obstructive multi-vessel CAD (n = 72), were collected and tested for antibody isotypes to MAA-modifed human serum albumin (MAA-HSA). CAD patients had elevated relative levels of IgG and IgA anti-MAA, compared to control patients (p<0.001). AMI patients had a significantly increased relative levels of circulating IgG anti-MAA-HSA antibodies as compared to stable angina (p<0.03) or CABG patients (p<0.003). CABG patients had significantly increased relative levels of circulating IgA anti-MAA-HSA antibodies as compared to non-obstructive CAD (p<0.001) and AMI patients (p<0.001). Additionally, MAA-modified proteins were detected in the tissue of human AMI lesions. In conclusion, the IgM, IgG and IgA anti-MAA-HSA antibody isotypes are differentially and significantly associated with non-obstructive CAD, AMI, or obstructive multi-vessel CAD and may serve as biomarkers of atherosclerotic disease. PMID:25210746
Computer-aided Classification of Mammographic Masses Using Visually Sensitive Image Features
Wang, Yunzhi; Aghaei, Faranak; Zarafshani, Ali; Qiu, Yuchen; Qian, Wei; Zheng, Bin
2017-01-01
Purpose To develop a new computer-aided diagnosis (CAD) scheme that computes visually sensitive image features routinely used by radiologists to develop a machine learning classifier and distinguish between the malignant and benign breast masses detected from digital mammograms. Methods An image dataset including 301 breast masses was retrospectively selected. From each segmented mass region, we computed image features that mimic five categories of visually sensitive features routinely used by radiologists in reading mammograms. We then selected five optimal features in the five feature categories and applied logistic regression models for classification. A new CAD interface was also designed to show lesion segmentation, computed feature values and classification score. Results Areas under ROC curves (AUC) were 0.786±0.026 and 0.758±0.027 when to classify mass regions depicting on two view images, respectively. By fusing classification scores computed from two regions, AUC increased to 0.806±0.025. Conclusion This study demonstrated a new approach to develop CAD scheme based on 5 visually sensitive image features. Combining with a “visual aid” interface, CAD results may be much more easily explainable to the observers and increase their confidence to consider CAD generated classification results than using other conventional CAD approaches, which involve many complicated and visually insensitive texture features. PMID:27911353
Slater, James; Rill, Velisar
2004-04-01
Coronary artery disease (CAD) is the leading cause of morbidity and mortality in the United States and other industrialized countries. In the undeveloped world a similar epidemic is brewing. A new pathophysiologic paradigm has emerged, which assigns the mediators of inflammation a much larger role in the disease process. This paradigm has helped explain the unpredictable nature of many adverse consequences of CAD. The long latent phase of the disease, and often sudden initial presentation, make efforts at early detection extremely important. Considerable work has been devoted to identify, as well as influence, predisposing risk factors for developing arteriosclerosis. Novel markers of inflammation, like C-reactive protein, have been identified and compared to traditional risk factors. In addition, new imaging modalities introduce the possibility of screening for subclinical disease. Electron beam and multidetector computed tomography (CT) scanners, as well as other techniques, are emerging as powerful tools to detect early disease presence and allow intervention to take place before major clinical events occur. Advances in our understanding of the pathophysiology of CAD, and our ability to image the stages of silent disease will go hand in hand to revolutionize our approach to prevention and treatment of this deadly malady.
The MAGIC-5 CAD for nodule detection in low dose and thin slice lung CTs
NASA Astrophysics Data System (ADS)
Cerello, Piergiorgio; MAGIC-5 Collaboration
2010-11-01
Lung cancer is the leading cause of cancer-related mortality in developed countries. Only 10-15% of all men and women diagnosed with lung cancer live 5 years after the diagnosis. However, the 5-year survival rate for patients diagnosed in the early asymptomatic stage of the disease can reach 70%. Early-stage lung cancers can be diagnosed by detecting non-calcified small pulmonary nodules with computed tomography (CT). Computer-aided detection (CAD) could support radiologists in the analysis of the large amount of noisy images generated in screening programs, where low-dose and thin-slice settings are used. The MAGIC-5 project, funded by the Istituto Nazionale di Fisica Nucleare (INFN, Italy) and Ministero dell'Università e della Ricerca (MUR, Italy), developed a multi-method approach based on three CAD algorithms to be used in parallel with a merging of their results: the Channeler Ant Model (CAM), based on Virtual Ant Colonies, the Dot-Enhancement/Pleura Surface Normals/VBNA (DE-PSN-VBNA), and the Region Growing Volume Plateau (RGVP). Preliminary results show quite good performances, to be improved with the refining of the single algorithm and the added value of the results merging.
On the Use of Parmetric-CAD Systems and Cartesian Methods for Aerodynamic Design
NASA Technical Reports Server (NTRS)
Nemec, Marian; Aftosmis, Michael J.; Pulliam, Thomas H.
2004-01-01
Automated, high-fidelity tools for aerodynamic design face critical issues in attempting to optimize real-life geometry arid in permitting radical design changes. Success in these areas promises not only significantly shorter design- cycle times, but also superior and unconventional designs. To address these issues, we investigate the use of a parmetric-CAD system in conjunction with an embedded-boundary Cartesian method. Our goal is to combine the modeling capabilities of feature-based CAD with the robustness and flexibility of component-based Cartesian volume-mesh generation for complex geometry problems. We present the development of an automated optimization frame-work with a focus on the deployment of such a CAD-based design approach in a heterogeneous parallel computing environment.
Rendenbach, Carsten; Sellenschloh, Kay; Gerbig, Lucca; Morlock, Michael M; Beck-Broichsitter, Benedicta; Smeets, Ralf; Heiland, Max; Huber, Gerd; Hanken, Henning
2017-11-01
CAD/CAM reconstruction plates have become a viable option for mandible reconstruction. The aim of this study was to determine whether CAD/CAM plates provide higher fatigue strength compared with conventional fixation systems. 1.0 mm miniplates, 2.0 mm conventional locking plates (DePuy Synthes, Umkirch, Germany), and 2.0 mm CAD/CAM plates (Materialise, Leuven, Belgium/DePuy Synthes) were used to reconstruct a polyurethane mandible model (Synbone, Malans, CH) with cortical and cancellous bone equivalents. Mastication was simulated via cyclic dynamic testing using a universal testing machine (MTS, Bionix, Eden Prairie, MN, USA) until material failure reached a rate of 1 Hz with increasing loads on the left side. No significant difference was found between the groups until a load of 300 N. At higher loads, vertical displacement differed increasingly, with a poorer performance of miniplates (p = 0.04). Plate breakage occurred in miniplates and conventional locking plates. Screw breakage was recorded as the primary failure mechanism in CAD/CAM plates. Stiffness was significantly higher with the CAD/CAM plates (p = 0.04). CAD/CAM plates and reconstruction plates provide higher fatigue strength than miniplates, and stiffness is highest in CAD/CAM systems. All tested fixation methods seem sufficiently stable for mandible reconstruction. Copyright © 2017 European Association for Cranio-Maxillo-Facial Surgery. Published by Elsevier Ltd. All rights reserved.
Cury, Ricardo C; Abbara, Suhny; Achenbach, Stephan; Agatston, Arthur; Berman, Daniel S; Budoff, Matthew J; Dill, Karin E; Jacobs, Jill E; Maroules, Christopher D; Rubin, Geoffrey D; Rybicki, Frank J; Schoepf, U Joseph; Shaw, Leslee J; Stillman, Arthur E; White, Charles S; Woodard, Pamela K; Leipsic, Jonathon A
2016-12-01
The intent of CAD-RADS - Coronary Artery Disease Reporting and Data System is to create a standardized method to communicate findings of coronary CT angiography (coronary CTA) in order to facilitate decision-making regarding further patient management. The suggested CAD-RADS classification is applied on a per-patient basis and represents the highest-grade coronary artery lesion documented by coronary CTA. It ranges from CAD-RADS 0 (Zero) for the complete absence of stenosis and plaque to CAD-RADS 5 for the presence of at least one totally occluded coronary artery and should always be interpreted in conjunction with the impression found in the report. Specific recommendations are provided for further management of patients with stable or acute chest pain based on the CAD-RADS classification. The main goal of CAD-RADS is to standardize reporting of coronary CTA results and to facilitate communication of test results to referring physicians along with suggestions for subsequent patient management. In addition, CAD-RADS will provide a framework of standardization that may benefit education, research, peer-review and quality assurance with the potential to ultimately result in improved quality of care. Copyright © 2016 Society of Cardiovascular Computed Tomography and the American College of Radiology. Published by Elsevier Inc. All rights reserved.
Al-Meraikhi, Hadi; Yilmaz, Burak; McGlumphy, Edwin; Brantley, William A; Johnston, William M
2018-01-01
Computer-aided design and computer-aided manufacturing (CAD-CAM)-fabricated titanium and zirconia implant-supported fixed dental prostheses have become increasingly popular for restoring patients with complete edentulism. However, the distortion level of these frameworks is not well known. The purpose of this in vitro study was to compare the 3-dimensional (3D) distortion of CAD-CAM zirconia and titanium implant-fixed screw-retained complete dental prostheses. A master edentulous model with 4 implants at the positions of the maxillary first molars and canines was used. Multiunit abutments (Nobel Biocare) secured to the model were digitally scanned using scan bodies and a laboratory scanner (S600 ARTI; Zirkonzahn). Titanium (n=5) and zirconia (n=5) frameworks were milled using a CAD-CAM system (Zirkonzahn M1; Zirkonzahn). All frameworks were scanned using an industrial computed tomography (CT) scanner (Nikon/X-Tek XT H 225kV MCT Micro-Focus). The direct CT scans were reconstructed to generate standard tessellation language (STL) files. To calculate the 3D distortion of the frameworks, STL files of the CT scans were aligned to the CAD model using a sum of the least squares best-fit algorithm. Surface comparison points were placed on the CAD model on the midfacial aspect of all teeth. The 3D distortion of each direct scan to the CAD model was calculated. In addition, color maps of the scan-to-CAD comparison were constructed using a ±0.500 mm color scale range. Both materials exhibited distortion; however, no significant difference was found in the amount of distortion from the CAD model between the materials (P=.747). Absolute values of deviations from the CAD model were evident in the x and y plane and less so in the z direction. Zirconia and titanium frameworks showed similar 3D distortion compared with the CAD model for the tested CAD-CAM and implant systems. The distortion was more pronounced in the horizontal and sagittal plane than in the vertical plane. Copyright © 2017 Editorial Council for the Journal of Prosthetic Dentistry. Published by Elsevier Inc. All rights reserved.
Comparative fracture strength analysis of Lava and Digident CAD/CAM zirconia ceramic crowns.
Kwon, Taek-Ka; Pak, Hyun-Soon; Yang, Jae-Ho; Han, Jung-Suk; Lee, Jai-Bong; Kim, Sung-Hun; Yeo, In-Sung
2013-05-01
All-ceramic crowns are subject to fracture during function. To minimize this common clinical complication, zirconium oxide has been used as the framework for all-ceramic crowns. The aim of this study was to compare the fracture strengths of two computer-aided design/computer-aided manufacturing (CAD/CAM) zirconia crown systems: Lava and Digident. Twenty Lava CAD/CAM zirconia crowns and twenty Digident CAD/CAM zirconia crowns were fabricated. A metal die was also duplicated from the original prepared tooth for fracture testing. A universal testing machine was used to determine the fracture strength of the crowns. THE MEAN FRACTURE STRENGTHS WERE AS FOLLOWS: 54.9 ± 15.6 N for the Lava CAD/CAM zirconia crowns and 87.0 ± 16.0 N for the Digident CAD/CAM zirconia crowns. The difference between the mean fracture strengths of the Lava and Digident crowns was statistically significant (P<.001). Lava CAD/CAM zirconia crowns showed a complete fracture of both the veneering porcelain and the core whereas the Digident CAD/CAM zirconia crowns showed fracture only of the veneering porcelain. The fracture strengths of CAD/CAM zirconia crowns differ depending on the compatibility of the core material and the veneering porcelain.
Xu, X W; Doi, K; Kobayashi, T; MacMahon, H; Giger, M L
1997-09-01
Lung cancer is the leading cause of cancer deaths in men and women in the United States, with a 5-year survival rate of only about 13%. However, this survival rate can be improved to 47% if the disease is diagnosed and treated at an early stage. In this study, we developed an improved computer-aided diagnosis (CAD) scheme for the automated detection of lung nodules in digital chest images to assist radiologists, who could miss up to 30% of the actually positive cases in their daily practice. Two hundred PA chest radiographs, 100 normals and 100 abnormals, were used as the database for our study. The presence of nodules in the 100 abnormal cases was confirmed by two experienced radiologists on the basis of CT scans or radiographic follow-up. In our CAD scheme, nodule candidates were selected initially by multiple gray-level thresholding of the difference image (which corresponds to the subtraction of a signal-enhanced image and a signal-suppressed image) and then classified into six groups. A large number of false positives were eliminated by adaptive rule-based tests and an artificial neural network (ANN). The CAD scheme achieved, on average, a sensitivity of 70% with 1.7 false positives per chest image, a performance which was substantially better as compared with other studies. The CPU time for the processing of one chest image was about 20 seconds on an IBM RISC/6000 Powerstation 590. We believe that the CAD scheme with the current performance is ready for initial clinical evaluation.
NASA Astrophysics Data System (ADS)
Ma, Kevin C.; Zhang, Aifeng; Moin, Paymann; Fleshman, Mariam; Vachon, Linda; Liu, Brent; Huang, H. K.
2009-02-01
Bone age assessment is a radiological procedure to evaluate a child's bone age based on his or her left-hand x-ray image. The current standard is to match patient's hand with Greulich & Pyle hand atlas, which is outdated by 50 years and only uses subjects from one region and one ethnicity. To improve bone age assessment accuracy for today's children, an automated race- and gender-specific bone age assessment (BAA) system has been developed in IPILab. 1390 normal left-hand x-ray images have been collected at Children's Hospital of Los Angeles (CHLA) to form the digital hand atlas (DHA). DHA includes both male and female children of ages one to eighteen and of four ethnic groups: African American, Asian American, Caucasian, and Hispanic. In order to apply DHA and BAA CAD into a clinical environment, a web-based BAA CAD system and graphical user interface (GUI) has been implemented in Women and Children's Hospital at Los Angeles County (WCH-LAC). A CAD server has been integrated in WCH's PACS environment, and a clinical validation workflow has been designed for radiologists, who compare CAD readings with G&P readings and determine which reading is more suited for a certain case. Readings are logged in database and analyzed to assess BAA CAD performance in a clinical setting. The result is a successful installation of web-based BAA CAD system in a clinical setting.
A hybrid lung and vessel segmentation algorithm for computer aided detection of pulmonary embolism
NASA Astrophysics Data System (ADS)
Raghupathi, Laks; Lakare, Sarang
2009-02-01
Advances in multi-detector technology have made CT pulmonary angiography (CTPA) a popular radiological tool for pulmonary emboli (PE) detection. CTPA provide rich detail of lung anatomy and is a useful diagnostic aid in highlighting even very small PE. However analyzing hundreds of slices is laborious and time-consuming for the practicing radiologist which may also cause misdiagnosis due to the presence of various PE look-alike. Computer-aided diagnosis (CAD) can be a potential second reader in providing key diagnostic information. Since PE occurs only in vessel arteries, it is important to mark this region of interest (ROI) during CAD preprocessing. In this paper, we present a new lung and vessel segmentation algorithm for extracting contrast-enhanced vessel ROI in CTPA. Existing approaches to segmentation either provide only the larger lung area without highlighting the vessels or is computationally prohibitive. In this paper, we propose a hybrid lung and vessel segmentation which uses an initial lung ROI and determines the vessels through a series of refinement steps. We first identify a coarse vessel ROI by finding the "holes" from the lung ROI. We then use the initial ROI as seed-points for a region-growing process while carefully excluding regions which are not relevant. The vessel segmentation mask covers 99% of the 259 PE from a real-world set of 107 CTPA. Further, our algorithm increases the net sensitivity of a prototype CAD system by 5-9% across all PE categories in the training and validation data sets. The average run-time of algorithm was only 100 seconds on a standard workstation.
Raghavendra, U; Gudigar, Anjan; Maithri, M; Gertych, Arkadiusz; Meiburger, Kristen M; Yeong, Chai Hong; Madla, Chakri; Kongmebhol, Pailin; Molinari, Filippo; Ng, Kwan Hoong; Acharya, U Rajendra
2018-04-01
Ultrasound imaging is one of the most common visualizing tools used by radiologists to identify the location of thyroid nodules. However, visual assessment of nodules is difficult and often affected by inter- and intra-observer variabilities. Thus, a computer-aided diagnosis (CAD) system can be helpful to cross-verify the severity of nodules. This paper proposes a new CAD system to characterize thyroid nodules using optimized multi-level elongated quinary patterns. In this study, higher order spectral (HOS) entropy features extracted from these patterns appropriately distinguished benign and malignant nodules under particle swarm optimization (PSO) and support vector machine (SVM) frameworks. Our CAD algorithm achieved a maximum accuracy of 97.71% and 97.01% in private and public datasets respectively. The evaluation of this CAD system on both private and public datasets confirmed its effectiveness as a secondary tool in assisting radiological findings. Copyright © 2018 Elsevier Ltd. All rights reserved.
Reduction of bias and variance for evaluation of computer-aided diagnostic schemes.
Li, Qiang; Doi, Kunio
2006-04-01
Computer-aided diagnostic (CAD) schemes have been developed to assist radiologists in detecting various lesions in medical images. In addition to the development, an equally important problem is the reliable evaluation of the performance levels of various CAD schemes. It is good to see that more and more investigators are employing more reliable evaluation methods such as leave-one-out and cross validation, instead of less reliable methods such as resubstitution, for assessing their CAD schemes. However, the common applications of leave-one-out and cross-validation evaluation methods do not necessarily imply that the estimated performance levels are accurate and precise. Pitfalls often occur in the use of leave-one-out and cross-validation evaluation methods, and they lead to unreliable estimation of performance levels. In this study, we first identified a number of typical pitfalls for the evaluation of CAD schemes, and conducted a Monte Carlo simulation experiment for each of the pitfalls to demonstrate quantitatively the extent of bias and/or variance caused by the pitfall. Our experimental results indicate that considerable bias and variance may exist in the estimated performance levels of CAD schemes if one employs various flawed leave-one-out and cross-validation evaluation methods. In addition, for promoting and utilizing a high standard for reliable evaluation of CAD schemes, we attempt to make recommendations, whenever possible, for overcoming these pitfalls. We believe that, with the recommended evaluation methods, we can considerably reduce the bias and variance in the estimated performance levels of CAD schemes.
Buchner, Sophie; Schlundt, Andreas; Lassak, Jürgen; Sattler, Michael; Jung, Kirsten
2015-07-31
The pH-responsive one-component signaling system CadC in Escherichia coli belongs to the family of ToxR-like proteins, whose members share a conserved modular structure, with an N-terminal cytoplasmic winged helix-turn-helix DNA-binding domain being followed by a single transmembrane helix and a C-terminal periplasmic pH-sensing domain. In E. coli CadC, a cytoplasmic linker comprising approximately 50 amino acids is essential for transmission of the signal from the sensor to the DNA-binding domain. However, the mechanism of transduction is poorly understood. Using NMR spectroscopy, we demonstrate here that the linker region is intrinsically disordered in solution. Furthermore, mutational analyses showed that it tolerates a range of amino acid substitutions (altering polarity, rigidity and α-helix-forming propensity), is robust to extension but is sensitive to truncation. Indeed, truncations either reversed the expression profile of the target operon cadBA or decoupled expression from external pH altogether. CadC dimerizes via its periplasmic domain, but light-scattering analysis provided no evidence for dimerization of the isolated DNA-binding domain, with or without the linker region. However, bacterial two-hybrid analysis revealed that CadC forms stable dimers in a stimulus- and linker-dependent manner, interacting only at pH<6.8. Strikingly, a variant with inversed cadBA expression profile, which lacks most of the linker, dimerizes preferentially at higher pH. Thus, we propose that the disordered CadC linker is required for transducing the pH-dependent response of the periplasmic sensor into a structural rearrangement that facilitates dimerization of the cytoplasmic CadC DNA-binding domain. Copyright © 2015 Elsevier Ltd. All rights reserved.
Elsaka, Shaymaa E
2014-12-01
To evaluate the effect of different surface treatments on the microtensile bond strength (μTBS) of novel CAD/CAM restorative materials to self-adhesive resin cement. Two types of CAD/CAM restorative materials (Vita Enamic [VE] and Lava Ultimate [LU]) were used. The specimens were divided into five groups in each test according to the surface treatment performed; Gr 1 (control; no treatment), Gr 2 (sandblasted [SB]), Gr 3 (SB+silane [S]), Gr 4 (hydrofluoric acid [HF]), and Gr 5 (HF+S). A dual-curing self-adhesive resin cement (Bifix SE [BF]) was applied to each group for testing the adhesion after 24 h of storage in distilled water or after 30 days using the μTBS test. Following fracture testing, specimens were examined with a stereomicroscope and SEM. Surface roughness and morphology of the CAD/CAM restorative materials were characterized after treatment. Data were analyzed using ANOVA and Tukey's test. The surface treatment, type of CAD/CAM restorative material, and water storage periods showed a significant effect on the μTBS (p<0.001). For the LU/BF system, there was no significant difference in the bond strength values between different surface treatments (p>0.05). On the other hand, for the VE/BF system, surface treatment with HF+S showed higher bond strength values compared with SB and HF surface treatments (p<0.05). Surface roughness and SEM analyses showed that the surface topography of CAD/CAM restorative materials was modified after treatments. The effect of surface treatments on the bond strength of novel CAD/CAM restorative materials to resin cement is material dependent. The VE/BF CAD/CAM material provided higher bond strength values compared with the LU/BF CAD/CAM material.
NASA Technical Reports Server (NTRS)
Benyo, Theresa L.
2002-01-01
Integration of a supersonic inlet simulation with a computer aided design (CAD) system is demonstrated. The integration is performed using the Project Integration Architecture (PIA). PIA provides a common environment for wrapping many types of applications. Accessing geometry data from CAD files is accomplished by incorporating appropriate function calls from the Computational Analysis Programming Interface (CAPRI). CAPRI is a CAD vendor neutral programming interface that aids in acquiring geometry data directly from CAD files. The benefits of wrapping a supersonic inlet simulation into PIA using CAPRI are; direct access of geometry data, accurate capture of geometry data, automatic conversion of data units, CAD vendor neutral operation, and on-line interactive history capture. This paper describes the PIA and the CAPRI wrapper and details the supersonic inlet simulation demonstration.
NASA Astrophysics Data System (ADS)
Liu, Xiaonan; Chen, Kewei; Wu, Teresa; Weidman, David; Lure, Fleming; Li, Jing
2018-02-01
Alzheimer's Disease (AD) is the most common cause of dementia and currently has no cure. Treatments targeting early stages of AD such as Mild Cognitive Impairment (MCI) may be most effective to deaccelerate AD, thus attracting increasing attention. However, MCI has substantial heterogeneity in that it can be caused by various underlying conditions, not only AD. To detect MCI due to AD, NIA-AA published updated consensus criteria in 2011, in which the use of multi-modality images was highlighted as one of the most promising methods. It is of great interest to develop a CAD system based on automatic, quantitative analysis of multi-modality images and machine learning algorithms to help physicians more adequately diagnose MCI due to AD. The challenge, however, is that multi-modality images are not universally available for many patients due to cost, access, safety, and lack of consent. We developed a novel Missing Modality Transfer Learning (MMTL) algorithm capable of utilizing whatever imaging modalities are available for an MCI patient to diagnose the patient's likelihood of MCI due to AD. Furthermore, we integrated MMTL with radiomics steps including image processing, feature extraction, and feature screening, and a post-processing for uncertainty quantification (UQ), and developed a CAD system called "ADMultiImg" to assist clinical diagnosis of MCI due to AD using multi-modality images together with patient demographic and genetic information. Tested on ADNI date, our system can generate a diagnosis with high accuracy even for patients with only partially available image modalities (AUC=0.94), and therefore may have broad clinical utility.
Incorporation of CAD/CAM Restoration Into Navy Dentistry
2017-09-26
CAD/CAM Computer-aided design /Computer-assisted manufacturing CDT Common Dental Terminology DENCAS Dental Common Access System DTF Dental...to reduce avoidable dental emergencies for deployed sailors and marines. Dental Computer-aided design /Computer-assisted manufacturing (CAD/CAM...report will review and evaluate the placement rate by Navy dentists of digitally fabricated in-office ceramic restorations compared to traditional direct
Nonobstructive coronary artery disease and risk of myocardial infarction.
Maddox, Thomas M; Stanislawski, Maggie A; Grunwald, Gary K; Bradley, Steven M; Ho, P Michael; Tsai, Thomas T; Patel, Manesh R; Sandhu, Amneet; Valle, Javier; Magid, David J; Leon, Benjamin; Bhatt, Deepak L; Fihn, Stephan D; Rumsfeld, John S
2014-11-05
Little is known about cardiac adverse events among patients with nonobstructive coronary artery disease (CAD). To compare myocardial infarction (MI) and mortality rates between patients with nonobstructive CAD, obstructive CAD, and no apparent CAD in a national cohort. Retrospective cohort study of all US veterans undergoing elective coronary angiography for CAD between October 2007 and September 2012 in the Veterans Affairs health care system. Patients with prior CAD events were excluded. Angiographic CAD extent, defined by degree (no apparent CAD: no stenosis >20%; nonobstructive CAD: ≥1 stenosis ≥20% but no stenosis ≥70%; obstructive CAD: any stenosis ≥70% or left main [LM] stenosis ≥50%) and distribution (1, 2, or 3 vessel). The primary outcome was 1-year hospitalization for nonfatal MI after the index angiography. Secondary outcomes included 1-year all-cause mortality and combined 1-year MI and mortality. Among 37,674 patients, 8384 patients (22.3%) had nonobstructive CAD and 20,899 patients (55.4%) had obstructive CAD. Within 1 year, 845 patients died and 385 were rehospitalized for MI. Among patients with no apparent CAD, the 1-year MI rate was 0.11% (n = 8, 95% CI, 0.10%-0.20%) and increased progressively by 1-vessel nonobstructive CAD, 0.24% (n = 10, 95% CI, 0.10%-0.40%); 2-vessel nonobstructive CAD, 0.56% (n = 13, 95% CI, 0.30%-1.00%); 3-vessel nonobstructive CAD, 0.59% (n = 6, 95% CI, 0.30%-1.30%); 1-vessel obstructive CAD, 1.18% (n = 101, 95% CI, 1.00%-1.40%); 2-vessel obstructive CAD, 2.18% (n = 110, 95% CI, 1.80%-2.60%); and 3-vessel or LM obstructive CAD, 2.47% (n = 137, 95% CI, 2.10%-2.90%). After adjustment, 1-year MI rates increased with increasing CAD extent. Relative to patients with no apparent CAD, patients with 1-vessel nonobstructive CAD had a hazard ratio (HR) for 1-year MI of 2.0 (95% CI, 0.8-5.1); 2-vessel nonobstructive HR, 4.6 (95% CI, 2.0-10.5); 3-vessel nonobstructive HR, 4.5 (95% CI, 1.6-12.5); 1-vessel obstructive HR, 9.0 (95% CI, 4.2-19.0); 2-vessel obstructive HR, 16.5 (95% CI, 8.1-33.7); and 3-vessel or LM obstructive HR, 19.5 (95% CI, 9.9-38.2). One-year mortality rates were associated with increasing CAD extent, ranging from 1.38% among patients without apparent CAD to 4.30% with 3-vessel or LM obstructive CAD. After risk adjustment, there was no significant association between 1- or 2-vessel nonobstructive CAD and mortality, but there were significant associations with mortality for 3-vessel nonobstructive CAD (HR, 1.6; 95% CI, 1.1-2.5), 1-vessel obstructive CAD (HR, 1.9; 95% CI, 1.4-2.6), 2-vessel obstructive CAD (HR, 2.8; 95% CI, 2.1-3.7), and 3-vessel or LM obstructive CAD (HR, 3.4; 95% CI, 2.6-4.4). Similar associations were noted with the combined outcome. In this cohort of patients undergoing elective coronary angiography, nonobstructive CAD, compared with no apparent CAD, was associated with a significantly greater 1-year risk of MI and all-cause mortality. These findings suggest clinical importance of nonobstructive CAD and warrant further investigation of interventions to improve outcomes among these patients.
Design of Complete Dentures by Adopting CAD Developed for Fixed Prostheses.
Li, Yanfeng; Han, Weili; Cao, Jing; Iv, Yuan; Zhang, Yue; Han, Yishi; Shen, Yi; Ma, Zheng; Liu, Huanyue
2018-02-01
The demand for complete dentures is expected to increase worldwide, but complete dentures are mainly designed and fabricated manually involving a broad series of clinical and laboratory procedures. Therefore, the quality of complete dentures largely depends on the skills of the dentist and technician, leading to difficulty in quality control. Computer-aided design and manufacturing (CAD/CAM) has been used to design and fabricate various dental restorations including dental inlays, veneers, crowns, partial crowns, and fixed partial dentures (FPDs). It has been envisioned that the application of CAD/CAM technology could reduce intensive clinical/laboratory work for the fabrication of complete dentures; however, CAD/CAM is seldom used to fabricate complete dentures due to the lack of suitable CAD software to design virtual complete dentures although the CAM techniques are in a much advanced stage. Here we report the successful design of virtual complete dentures using CAD software of 3Shape Dental System 2012, which was developed for designing fixed prostheses instead of complete dentures. Our results demonstrated that complete dentures could be successfully designed by the combination of two modeling processes, single coping and full anatomical FPD, available in the 3Shape Dental System 2012. © 2016 by the American College of Prosthodontists.
1991-03-21
sectional representation of the spatial figure can be correctly determined. 6 The AutoLisp language system in the AutoCAD software provides the most...softwares are developed on the 32-bit machines and little progress has been reported for the 16-bit machines. Even the AutoCAD is a two-ard-a-half... AutoCAD software as the basis, developed the design package of 3-D cartridge valve blocks on IM PC/AT. To realize the 3-D displaying of cartridge valves
Schultheis, Stefan; Strub, Joerg R; Gerds, Thomas A; Guess, Petra C
2013-06-01
The authors analyzed the effect of fatigue on the survival rate and fracture load of monolithic and bi-layer CAD/CAM lithium-disilicate posterior three-unit fixed dental prostheses (FDPs) in comparison to the metal-ceramic gold standard. The authors divided 96 human premolars and molars into three equal groups. Lithium-disilicate ceramic (IPS-e.max-CAD) was milled with the CEREC-3-system in full-anatomic FDP dimensions (monolithic: M-LiCAD) or as framework (Bi-layer: BL-LiCAD) with subsequent hand-layer veneering. Metal-ceramic FDPs (MC) served as control. Single-load-to-failure tests were performed before and after mouth-motion fatigue. No fracture failures occurred during fatigue. Median fracture loads in [N], before and after fatigue were, respectively, as follows: M-LiCAD, 1,298/1,900; BL-LiCAD, 817/699; MC, 1,966/1,818. M-LiCAD and MC FPDs revealed comparable fracture loads and were both significantly higher than BL-LiCAD. M-LiCAD and BL-LiCAD both failed from core/veneer bulk fracture within the connector area. MC failures were limited to ceramic veneer fractures exposing the metal core. Fatigue had no significant effect on any group. Posterior monolithic CAD/CAM fabricated lithium-disilicate FPDs were shown to be fracture resistant with failure load results comparable to the metal-ceramic gold standard. Clinical investigations are needed to confirm these promising laboratory results. Monolithic CAD/CAM fabricated lithium-disilicate FDPs appeared to be a reliable treatment alternative for the posterior load-bearing area, whereas FDPs in bi-layer configuration were susceptible to low load fracture failure.
Hannukainen, J C; Lautamäki, R; Mari, A; Pärkkä, J P; Bucci, M; Guzzardi, M A; Kajander, S; Tuokkola, T; Knuuti, J; Iozzo, P
2016-07-01
Insulin resistance, β-cell dysfunction, and ectopic fat deposition have been implicated in the pathogenesis of coronary artery disease (CAD) and type 2 diabetes, which is common in CAD patients. We investigated whether CAD is an independent predictor of these metabolic abnormalities and whether this interaction is influenced by superimposed myocardial ischemia. We studied CAD patients with (n = 8) and without (n = 14) myocardial ischemia and eight non-CAD controls. Insulin sensitivity and secretion and substrate oxidation were measured during fasting and oral glucose tolerance testing. We used magnetic resonance imaging/spectroscopy, positron emission and computerized tomography to characterize CAD, cardiac function, pericardial and abdominal adipose tissue, and myocardial, liver, and pancreatic triglyceride contents. Ischemic CAD was characterized by elevated oxidative glucose metabolism and a proportional decline in β-cell insulin secretion and reduction in lipid oxidation. Cardiac function was preserved in CAD groups, whereas cardiac fat depots were elevated in ischemic CAD compared to non-CAD subjects. Liver and pancreatic fat contents were similar in all groups and related with surrounding adipose masses or systemic insulin sensitivity. In ischemic CAD patients, glucose oxidation is enhanced and correlates inversely with insulin secretion. This can be seen as a mechanism to prevent glucose lowering because glucose is required in oxygen-deprived tissues. On the other hand, the accumulation of cardiac triglycerides may be a physiological adaptation to the limited fatty acid oxidative capacity. Our results underscore the urgent need of clinical trials that define the optimal/safest glycemic range in situations of myocardial ischemia.
Hannukainen, J. C.; Lautamäki, R.; Mari, A.; Pärkkä, J. P.; Bucci, M.; Guzzardi, M. A.; Kajander, S.; Tuokkola, T.; Knuuti, J.
2016-01-01
Background: Insulin resistance, β-cell dysfunction, and ectopic fat deposition have been implicated in the pathogenesis of coronary artery disease (CAD) and type 2 diabetes, which is common in CAD patients. We investigated whether CAD is an independent predictor of these metabolic abnormalities and whether this interaction is influenced by superimposed myocardial ischemia. Methods and Results: We studied CAD patients with (n = 8) and without (n = 14) myocardial ischemia and eight non-CAD controls. Insulin sensitivity and secretion and substrate oxidation were measured during fasting and oral glucose tolerance testing. We used magnetic resonance imaging/spectroscopy, positron emission and computerized tomography to characterize CAD, cardiac function, pericardial and abdominal adipose tissue, and myocardial, liver, and pancreatic triglyceride contents. Ischemic CAD was characterized by elevated oxidative glucose metabolism and a proportional decline in β-cell insulin secretion and reduction in lipid oxidation. Cardiac function was preserved in CAD groups, whereas cardiac fat depots were elevated in ischemic CAD compared to non-CAD subjects. Liver and pancreatic fat contents were similar in all groups and related with surrounding adipose masses or systemic insulin sensitivity. Conclusions: In ischemic CAD patients, glucose oxidation is enhanced and correlates inversely with insulin secretion. This can be seen as a mechanism to prevent glucose lowering because glucose is required in oxygen-deprived tissues. On the other hand, the accumulation of cardiac triglycerides may be a physiological adaptation to the limited fatty acid oxidative capacity. Our results underscore the urgent need of clinical trials that define the optimal/safest glycemic range in situations of myocardial ischemia. PMID:27045985
Computer-aided detection of initial polyp candidates with level set-based adaptive convolution
NASA Astrophysics Data System (ADS)
Zhu, Hongbin; Duan, Chaijie; Liang, Zhengrong
2009-02-01
In order to eliminate or weaken the interference between different topological structures on the colon wall, adaptive and normalized convolution methods were used to compute the first and second order spatial derivatives of computed tomographic colonography images, which is the beginning of various geometric analyses. However, the performance of such methods greatly depends on the single-layer representation of the colon wall, which is called the starting layer (SL) in the following text. In this paper, we introduce a level set-based adaptive convolution (LSAC) method to compute the spatial derivatives, in which the level set method is employed to determine a more reasonable SL. The LSAC was applied to a computer-aided detection (CAD) scheme to detect the initial polyp candidates, and experiments showed that it benefits the CAD scheme in both the detection sensitivity and specificity as compared to our previous work.
Application programs written by using customizing tools of a computer-aided design system
DOE Office of Scientific and Technical Information (OSTI.GOV)
Li, X.; Huang, R.; Juricic, D.
1995-12-31
Customizing tools of Computer-Aided Design Systems have been developed to such a degree as to become equivalent to powerful higher-level programming languages that are especially suitable for graphics applications. Two examples of application programs written by using AutoCAD`s customizing tools are given in some detail to illustrate their power. One tool uses AutoLISP list-processing language to develop an application program that produces four views of a given solid model. The other uses AutoCAD Developmental System, based on program modules written in C, to produce an application program that renders a freehand sketch from a given CAD drawing.
GPU-accelerated depth map generation for X-ray simulations of complex CAD geometries
NASA Astrophysics Data System (ADS)
Grandin, Robert J.; Young, Gavin; Holland, Stephen D.; Krishnamurthy, Adarsh
2018-04-01
Interactive x-ray simulations of complex computer-aided design (CAD) models can provide valuable insights for better interpretation of the defect signatures such as porosity from x-ray CT images. Generating the depth map along a particular direction for the given CAD geometry is the most compute-intensive step in x-ray simulations. We have developed a GPU-accelerated method for real-time generation of depth maps of complex CAD geometries. We preprocess complex components designed using commercial CAD systems using a custom CAD module and convert them into a fine user-defined surface tessellation. Our CAD module can be used by different simulators as well as handle complex geometries, including those that arise from complex castings and composite structures. We then make use of a parallel algorithm that runs on a graphics processing unit (GPU) to convert the finely-tessellated CAD model to a voxelized representation. The voxelized representation can enable heterogeneous modeling of the volume enclosed by the CAD model by assigning heterogeneous material properties in specific regions. The depth maps are generated from this voxelized representation with the help of a GPU-accelerated ray-casting algorithm. The GPU-accelerated ray-casting method enables interactive (> 60 frames-per-second) generation of the depth maps of complex CAD geometries. This enables arbitrarily rotation and slicing of the CAD model, leading to better interpretation of the x-ray images by the user. In addition, the depth maps can be used to aid directly in CT reconstruction algorithms.
Alharbi, Amal; Ardu, Stefano; Bortolotto, Tissiana; Krejci, Ivo
2017-04-01
To evaluate the stain susceptibility of CAD/CAM blocks and direct composite after long term exposure to various staining agents. 40 disk-shaped samples were fabricated from each of nine materials; six CAD/CAM (Vitablocs Mark II, Paradigm MZ100, Experimental Vita Hybrid Ceramic, Vita Enamic, Experimental Kerr and Lava Ultimate) and three direct composites (Filtek Supreme, Venus Diamond and Filtek Silorane). Samples were randomly divided into five groups (n = 8) according to different staining solutions (distilled water, tea, red wine, coffee and artificial saliva). Initial L*a*b* values were assessed using a calibrated digital spectrophotometer. Specimens were immersed in staining solutions and stored in an incubator at 37 °C for 120 days. L*a*b* values were assessed again and color change (∆E) was calculated as difference between recorded L*a*b* values. ANOVA, and Duncan test were used to identify differences between groups (α = 0.05). Significant differences in ∆E values were detected between materials (p = 0.000). Among all staining solutions, the highest ∆E value was observed with red wine. The new CAD/CAM blocks (Vita Enamic, Vita Hybrid Ceramic and Lava Ultimate) showed the highest resistance to staining compared to the MZ100 composite resin blocks. Filtek Silorane, a direct composite, showed high stain resistance values compared to CAD/CAM materials and other direct composites. Ceramic and composite CAD/CAM blocks had lower staining susceptibility than methacrylate based direct composite. Staining susceptibility of the new resin based CAD/CAM materials Vita Enamic and Lava Ultimate was comparable to feldspathic ceramic blocks (Vitablocs Mark II). Filtek Silorane showed promising results that were comparable to some CAD/CAM blocks.
A Geometry Based Infra-Structure for Computational Analysis and Design
NASA Technical Reports Server (NTRS)
Haimes, Robert
1998-01-01
The computational steps traditionally taken for most engineering analysis suites (computational fluid dynamics (CFD), structural analysis, heat transfer and etc.) are: (1) Surface Generation -- usually by employing a Computer Assisted Design (CAD) system; (2) Grid Generation -- preparing the volume for the simulation; (3) Flow Solver -- producing the results at the specified operational point; (4) Post-processing Visualization -- interactively attempting to understand the results. For structural analysis, integrated systems can be obtained from a number of commercial vendors. These vendors couple directly to a number of CAD systems and are executed from within the CAD Graphical User Interface (GUI). It should be noted that the structural analysis problem is more tractable than CFD; there are fewer mesh topologies used and the grids are not as fine (this problem space does not have the length scaling issues of fluids). For CFD, these steps have worked well in the past for simple steady-state simulations at the expense of much user interaction. The data was transmitted between phases via files. In most cases, the output from a CAD system could go to Initial Graphics Exchange Specification (IGES) or Standard Exchange Program (STEP) files. The output from Grid Generators and Solvers do not really have standards though there are a couple of file formats that can be used for a subset of the gridding (i.e. PLOT3D data formats). The user would have to patch up the data or translate from one format to another to move to the next step. Sometimes this could take days. Specifically the problems with this procedure are:(1) File based -- Information flows from one step to the next via data files with formats specified for that procedure. File standards, when they exist, are wholly inadequate. For example, geometry from CAD systems (transmitted via IGES files) is defined as disjoint surfaces and curves (as well as masses of other information of no interest for the Grid Generator). This is particularly onerous for modern CAD systems based on solid modeling. The part was a proper solid and in the translation to IGES has lost this important characteristic. STEP is another standard for CAD data that exists and supports the concept of a solid. The problem with STEP is that a solid modeling geometry kernel is required to query and manipulate the data within this type of file. (2) 'Good' Geometry. A bottleneck in getting results from a solver is the construction of proper geometry to be fed to the grid generator. With 'good' geometry a grid can be constructed in tens of minutes (even with a complex configuration) using unstructured techniques. Adroit multi-block methods are not far behind. This means that a million node steady-state solution can be computed on the order of hours (using current high performance computers) starting from this 'good' geometry. Unfortunately, the geometry usually transmitted from the CAD system is not 'good' in the grid generator sense. The grid generator needs smooth closed solid geometry. It can take a week (or more) of interaction with the CAD output (sometimes by hand) before the process can begin. One way Communication. (3) One-way Communication -- All information travels on from one phase to the next. This makes procedures like node adaptation difficult when attempting to add or move nodes that sit on bounding surfaces (when the actual surface data has been lost after the grid generation phase). Until this process can be automated, more complex problems such as multi-disciplinary analysis or using the above procedure for design becomes prohibitive. There is also no way to easily deal with this system in a modular manner. One can only replace the grid generator, for example, if the software reads and writes the same files. Instead of the serial approach to analysis as described above, CAPRI takes a geometry centric approach. This makes the actual geometry (not a discretized version) accessible to all phases of the analysis. The connection to the geometry is made through an Application Programming Interface (API) and NOT a file system. This API isolates the top-level applications (grid generators, solvers and visualization components) from the geometry engine. Also this allows the replacement of one geometry kernel with another, without effecting these top-level applications. For example, if UniGraphics is used as the CAD package then Parasolid (UG's own geometry engine) can be used for all geometric queries so that no solid geometry information is lost in a translation. This is much better than STEP because when the data is queried, the same software is executed as used in the CAD system. Therefore, one analyzes the exact part that is in the CAD system. CAPRI uses the same idea as the commercial structural analysis codes but does not specify control. Software components of the CAD system are used, but the analysis suite, not the CAD operator, specifies the control of the software session. This also means that the license issues (may be) minimized and individuals need not have to know how to operate a CAD system in order to run the suite.
CAD-model-based vision for space applications
NASA Technical Reports Server (NTRS)
Shapiro, Linda G.
1988-01-01
A pose acquisition system operating in space must be able to perform well in a variety of different applications including automated guidance and inspections tasks with many different, but known objects. Since the space station is being designed with automation in mind, there will be CAD models of all the objects, including the station itself. The construction of vision models and procedures directly from the CAD models is the goal of this project. The system that is being designed and implementing must convert CAD models to vision models, predict visible features from a given view point from the vision models, construct view classes representing views of the objects, and use the view class model thus derived to rapidly determine the pose of the object from single images and/or stereo pairs.
HDL subfractions and very early CAD: novel findings from untreated patients in a Chinese cohort.
Zhang, Yan; Zhu, Cheng-Gang; Xu, Rui-Xia; Li, Sha; Li, Xiao-Lin; Guo, Yuan-Lin; Wu, Na-Qiong; Gao, Ying; Qing, Ping; Cui, Chuan-Jue; Sun, Jing; Li, Jian-Jun
2016-08-04
Coronary artery disease (CAD) in very young individuals is a rare disease associated with poor prognosis. However, the role of specific lipoprotein subfractions in very young CAD patients (≤45 years) is not established yet. A total of 734 consecutive CAD subjects were enrolled and were classified as very early (n = 81, ≤45), early (n = 304, male: 45-55; female: 45-65), and late (n = 349, male: >55; female: >65) groups. Meanwhile, a group of non-CAD subjects were also enrolled as controls (n = 56, ≤45). The lipoprotein separation was performed using Lipoprint System. As a result, the very early CAD patients have lower large high-density lipoprotein (HDL) subfraction and higher small low-density lipoprotein (LDL) subfraction (p < 0.05). Although body mass index was inversely related to large HDL subfraction, overweight did not influence its association with very early CAD. In the logistic regression analysis, large HDL was inversely [OR 95% CI: 0.872 (0.825-0.922)] while small LDL was positively [1.038 (1.008-1.069)] related to very early CAD. However, after adjusting potential confounders, the association was only significant for large HDL [0.899 (0.848-0.954)]. This study firstly demonstrated that large HDL subfraction was negatively related to very early CAD suggestive of its important role in very early CAD incidence.
Integration of a CAD System Into an MDO Framework
NASA Technical Reports Server (NTRS)
Townsend, J. C.; Samareh, J. A.; Weston, R. P.; Zorumski, W. E.
1998-01-01
NASA Langley has developed a heterogeneous distributed computing environment, called the Framework for Inter-disciplinary Design Optimization, or FIDO. Its purpose has been to demonstrate framework technical feasibility and usefulness for optimizing the preliminary design of complex systems and to provide a working environment for testing optimization schemes. Its initial implementation has been for a simplified model of preliminary design of a high-speed civil transport. Upgrades being considered for the FIDO system include a more complete geometry description, required by high-fidelity aerodynamics and structures codes and based on a commercial Computer Aided Design (CAD) system. This report presents the philosophy behind some of the decisions that have shaped the FIDO system and gives a brief case study of the problems and successes encountered in integrating a CAD system into the FEDO framework.
NASA Astrophysics Data System (ADS)
Ikedo, Yuji; Fukuoka, Daisuke; Hara, Takeshi; Fujita, Hiroshi; Takada, Etsuo; Endo, Tokiko; Morita, Takako
2007-03-01
The comparison of left and right mammograms is a common technique used by radiologists for the detection and diagnosis of masses. In mammography, computer-aided detection (CAD) schemes using bilateral subtraction technique have been reported. However, in breast ultrasonography, there are no reports on CAD schemes using comparison of left and right breasts. In this study, we propose a scheme of false positive reduction based on bilateral subtraction technique in whole breast ultrasound images. Mass candidate regions are detected by using the information of edge directions. Bilateral breast images are registered with reference to the nipple positions and skin lines. A false positive region is detected based on a comparison of the average gray values of a mass candidate region and a region with the same position and same size as the candidate region in the contralateral breast. In evaluating the effectiveness of the false positive reduction method, three normal and three abnormal bilateral pairs of whole breast images were employed. These abnormal breasts included six masses larger than 5 mm in diameter. The sensitivity was 83% (5/6) with 13.8 (165/12) false positives per breast before applying the proposed reduction method. By applying the method, false positives were reduced to 4.5 (54/12) per breast without removing a true positive region. This preliminary study indicates that the bilateral subtraction technique is effective for improving the performance of a CAD scheme in whole breast ultrasound images.
Stojanovic, Anja; Lämmerhofer, Michael; Kogelnig, Daniel; Schiesel, Simone; Sturm, Martin; Galanski, Markus; Krachler, Regina; Keppler, Bernhard K; Lindner, Wolfgang
2008-10-31
Several hydrophobic ionic liquids (ILs) based on long-chain aliphatic ammonium- and phosphonium cations and selected aromatic anions were analyzed by reversed-phase high-performance liquid chromatography (RP-HPLC) employing trifluoroacetic acid as ion-pairing additive to the acetonitrile-containing mobile phase and adopting a step-gradient elution mode. The coupling of charged aerosol detection (CAD) for the non-chromophoric aliphatic cations with diode array detection (DAD) for the aromatic anions allowed their simultaneous analysis in a set of new ILs derived from either tricaprylmethylammonium chloride (Aliquat 336) and trihexyltetradecylphosphonium chloride as precursors. Aliquat 336 is a mix of ammonium cations with distinct aliphatic chain lengths. In the course of the studies it turned out that CAD generates an identical detection response for all the distinct aliphatic cations. Due to lack of single component standards of the individual Aliquat 336 cation species, a unified calibration function was established for the quantitative analysis of the quaternary ammonium cations of the ILs. The developed method was validated according to ICH guidelines, which confirmed the validity of the unified calibration. The application of the method revealed molar ratios of cation to anion close to 1 indicating a quantitative exchange of the chloride ions of the precursors by the various aromatic anions in the course of the synthesis of new ILs. Anomalies of CAD observed for the detection of some aromatic anions (thiosalicylate and benzoate) are discussed.
A framework for development of an intelligent system for design and manufacturing of stamping dies
NASA Astrophysics Data System (ADS)
Hussein, H. M. A.; Kumar, S.
2014-07-01
An integration of computer aided design (CAD), computer aided process planning (CAPP) and computer aided manufacturing (CAM) is required for development of an intelligent system to design and manufacture stamping dies in sheet metal industries. In this paper, a framework for development of an intelligent system for design and manufacturing of stamping dies is proposed. In the proposed framework, the intelligent system is structured in form of various expert system modules for different activities of design and manufacturing of dies. All system modules are integrated with each other. The proposed system takes its input in form of a CAD file of sheet metal part, and then system modules automate all tasks related to design and manufacturing of stamping dies. Modules are coded using Visual Basic (VB) and developed on the platform of AutoCAD software.
Prototypes for Content-Based Image Retrieval in Clinical Practice
Depeursinge, Adrien; Fischer, Benedikt; Müller, Henning; Deserno, Thomas M
2011-01-01
Content-based image retrieval (CBIR) has been proposed as key technology for computer-aided diagnostics (CAD). This paper reviews the state of the art and future challenges in CBIR for CAD applied to clinical practice. We define applicability to clinical practice by having recently demonstrated the CBIR system on one of the CAD demonstration workshops held at international conferences, such as SPIE Medical Imaging, CARS, SIIM, RSNA, and IEEE ISBI. From 2009 to 2011, the programs of CADdemo@CARS and the CAD Demonstration Workshop at SPIE Medical Imaging were sought for the key word “retrieval” in the title. The systems identified were analyzed and compared according to the hierarchy of gaps for CBIR systems. In total, 70 software demonstrations were analyzed. 5 systems were identified meeting the criterions. The fields of application are (i) bone age assessment, (ii) bone fractures, (iii) interstitial lung diseases, and (iv) mammography. Bridging the particular gaps of semantics, feature extraction, feature structure, and evaluation have been addressed most frequently. In specific application domains, CBIR technology is available for clinical practice. While system development has mainly focused on bridging content and feature gaps, performance and usability have become increasingly important. The evaluation must be based on a larger set of reference data, and workflow integration must be achieved before CBIR-CAD is really established in clinical practice. PMID:21892374
Enhancing image classification models with multi-modal biomarkers
NASA Astrophysics Data System (ADS)
Caban, Jesus J.; Liao, David; Yao, Jianhua; Mollura, Daniel J.; Gochuico, Bernadette; Yoo, Terry
2011-03-01
Currently, most computer-aided diagnosis (CAD) systems rely on image analysis and statistical models to diagnose, quantify, and monitor the progression of a particular disease. In general, CAD systems have proven to be effective at providing quantitative measurements and assisting physicians during the decision-making process. As the need for more flexible and effective CADs continues to grow, questions about how to enhance their accuracy have surged. In this paper, we show how statistical image models can be augmented with multi-modal physiological values to create more robust, stable, and accurate CAD systems. In particular, this paper demonstrates how highly correlated blood and EKG features can be treated as biomarkers and used to enhance image classification models designed to automatically score subjects with pulmonary fibrosis. In our results, a 3-5% improvement was observed when comparing the accuracy of CADs that use multi-modal biomarkers with those that only used image features. Our results show that lab values such as Erythrocyte Sedimentation Rate and Fibrinogen, as well as EKG measurements such as QRS and I:40, are statistically significant and can provide valuable insights about the severity of the pulmonary fibrosis disease.
Pombinho, Rita; Camejo, Ana; Vieira, Ana; Reis, Olga; Carvalho, Filipe; Almeida, Maria Teresa; Pinheiro, Jorge Campos; Sousa, Sandra; Cabanes, Didier
2017-05-01
Listeria monocytogenes is a major intracellular human foodborne bacterial pathogen. We previously revealed L. monocytogenes cadC as highly expressed during mouse infection. Here we show that L. monocytogenes CadC is a sequence-specific, DNA-binding and cadmium-dependent regulator of CadA, an efflux pump conferring cadmium resistance. CadC but not CadA is required for L. monocytogenes infection in vivo. Interestingly, CadC also directly represses lspB, a gene encoding a lipoprotein signal peptidase whose expression appears detrimental for infection. lspB overexpression promotes the release of the LpeA lipoprotein to the extracellular medium, inducing tumor necrosis factor α and interleukin 6 expression, thus impairing L. monocytogenes survival in macrophages. We propose that L. monocytogenes uses CadC to repress lspB expression during infection to avoid LpeA exposure to the host immune system, diminishing inflammatory cytokine expression and promoting intramacrophagic survival and virulence. CadC appears as the first metal efflux pump regulator repurposed during infection to fine-tune lipoprotein processing and host responses. © The Author 2017. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail: journals.permissions@oup.com.
Comparative fracture strength analysis of Lava and Digident CAD/CAM zirconia ceramic crowns
Kwon, Taek-Ka; Pak, Hyun-Soon; Han, Jung-Suk; Lee, Jai-Bong; Kim, Sung-Hun
2013-01-01
PURPOSE All-ceramic crowns are subject to fracture during function. To minimize this common clinical complication, zirconium oxide has been used as the framework for all-ceramic crowns. The aim of this study was to compare the fracture strengths of two computer-aided design/computer-aided manufacturing (CAD/CAM) zirconia crown systems: Lava and Digident. MATERIALS AND METHODS Twenty Lava CAD/CAM zirconia crowns and twenty Digident CAD/CAM zirconia crowns were fabricated. A metal die was also duplicated from the original prepared tooth for fracture testing. A universal testing machine was used to determine the fracture strength of the crowns. RESULTS The mean fracture strengths were as follows: 54.9 ± 15.6 N for the Lava CAD/CAM zirconia crowns and 87.0 ± 16.0 N for the Digident CAD/CAM zirconia crowns. The difference between the mean fracture strengths of the Lava and Digident crowns was statistically significant (P<.001). Lava CAD/CAM zirconia crowns showed a complete fracture of both the veneering porcelain and the core whereas the Digident CAD/CAM zirconia crowns showed fracture only of the veneering porcelain. CONCLUSION The fracture strengths of CAD/CAM zirconia crowns differ depending on the compatibility of the core material and the veneering porcelain. PMID:23755332
Jonasson, L; Grauen Larsen, H; Lundberg, A K; Gullstrand, B; Bengtsson, A A; Schiopu, A
2017-12-13
Psychological stress is thought to be an important trigger of cardiovascular events, yet the involved pathways and mediators are largely unknown. Elevated systemic levels of the pro-inflammatory alarmin S100A8/A9 correlate with poor prognosis in coronary artery disease (CAD) patients. Here, we investigated the links between S100A8/A9 release and parameters of anti-inflammatory glucocorticoid secretion in two different cohorts subjected to a psychological stress test. In the first cohort of 60 CAD patients, psychological stress induced a rapid increase of circulating S100A8/A9. This rapid S100A8/A9 response strongly correlated with elevated evening saliva cortisol levels, suggesting an association with a dysregulated hypothalamic-pituitary-adrenal (HPA) axis. In the second cohort of 27 CAD patients and 28 controls, elevated S100A8/A9 levels were still detectable 24 h after stress in 40% of patients and 36% of controls, with a tendency for higher levels in patients. The sustained S100A8/A9 response was associated with a poor rapid cortisol release after stress in patients, but not in the control group. Our findings reveal for the first time that acute psychological stress induces elevated levels of S100A8/A9. We also provide hypothesis-generating evidence that dysregulated cortisol secretion in CAD patients might be associated with an exaggerated pro-inflammatory S100A8/A9 response.
Optical properties of CAD-CAM ceramic systems.
Della Bona, Alvaro; Nogueira, Audrea D; Pecho, Oscar E
2014-09-01
To evaluate the direct transmittance (T%), translucency, opacity and opalescence of CAD-CAM ceramic systems and the correlation between the translucency parameter (TP) and the contrast ratio (CR). Specimens of shades A1, A2 and A3 (n=5) were fabricated from CAD-CAM ceramic blocks (IPS e.max(®) CAD HT and LT, IPS Empress(®) CAD HT and LT, Paradigm™ C, and VITABLOCS(®) Mark II) and polished to 1.0±0.01mm in thickness. A spectrophotometer (Lambda 20) was used to measure T% on the wavelength range of 400-780nm. Another spectrophotometer (VITA Easyshade(®) Advance) was used to measure the CIE L(*)a(*)b(*) coordinates and the reflectance value (Y) of samples on white and black backgrounds. TP, CR and the opalescence parameter (OP) were calculated. Data were statistically analysed using VAF (variance accounting for) coefficient with Cauchy-Schwarz inequality, one-way ANOVA, Tukey's test, Bonferroni correction and Pearson's correlation. T% of some ceramic systems is dependent on the wavelength. The spectral behaviour showed a slight and constant increase in T% up to approximately 550nm, then some ceramics changed the behaviour as the wavelength gets longer. TP and CR values ranged, respectively, from 16.79 to 21.69 and from 0.52 to 0.64 (r(2)=-0.97). OP values ranged from 3.01 to 7.64. The microstructure of CAD-CAM ceramic systems influenced the optical properties. TP and CR showed a strong correlation for all ceramic systems evaluated. Yet, all ceramics showed some degree of light transmittance. In addition to shade, this study showed that other optical properties influence on the natural appearance of dental ceramics. Copyright © 2014 Elsevier Ltd. All rights reserved.
Texture classification of lung computed tomography images
NASA Astrophysics Data System (ADS)
Pheng, Hang See; Shamsuddin, Siti M.
2013-03-01
Current development of algorithms in computer-aided diagnosis (CAD) scheme is growing rapidly to assist the radiologist in medical image interpretation. Texture analysis of computed tomography (CT) scans is one of important preliminary stage in the computerized detection system and classification for lung cancer. Among different types of images features analysis, Haralick texture with variety of statistical measures has been used widely in image texture description. The extraction of texture feature values is essential to be used by a CAD especially in classification of the normal and abnormal tissue on the cross sectional CT images. This paper aims to compare experimental results using texture extraction and different machine leaning methods in the classification normal and abnormal tissues through lung CT images. The machine learning methods involve in this assessment are Artificial Immune Recognition System (AIRS), Naive Bayes, Decision Tree (J48) and Backpropagation Neural Network. AIRS is found to provide high accuracy (99.2%) and sensitivity (98.0%) in the assessment. For experiments and testing purpose, publicly available datasets in the Reference Image Database to Evaluate Therapy Response (RIDER) are used as study cases.
CAD/CAM in dentistry: a historical perspective and view of the future.
Rekow, E D
1992-04-01
What can we look forward too? Lots of fun with new CAD/CAM systems that will enhance dentistry, providing quality restorations quickly. The evolution of an array of new versions of already available systems as well as altogether new systems will provide improved quality, expanded capabilities, and increasing user friendliness. And new materials will be more esthetic, wear more nearly like enamel, and strong enough for full crowns and bridges. We can also look forward to lots of change. Because of the cost of CAD/CAM systems, many clinicians are likely to collaborate by sharing a single system. Laboratories and clinicians may collaborate as well, with data being gathered in the operatory and sent to a laboratory via modem. The fabrication would then be done by the laboratory. Other changes that we cannot even predict are likely to occur in dentistry. Exciting times are here. Automation through dental CAD/CAM systems will, most certainly, change the profession. The impact of that change will only be known in the future. But as the future approaches, the systems and materials available to us will continue to evolve, improve, and enhance dentistry.
Cardiac SPECT/CCTA hybrid imaging : One answer to two questions?
Kaufmann, P A; Buechel, R R
2016-08-01
Noninvasive cardiac imaging has witnessed tremendous advances in the recent past, particularly with regard to coronary computed tomography angiography (CCTA) where substantial improvements in image quality have been achieved while at the same time patients' radiation dose exposure has been reduced to the sub-millisievert range. Similarly, for single-photon emission computed tomography (SPECT) the introduction of novel cadmium-zinc-telluride-based semiconductor detectors has significantly improved system sensitivity and image quality, enabling fast image acquisition within less than 2-3 min or reduction of radiation dose exposure to less than 5 mSv. However, neither imaging modality alone is able to fully cover the two aspects of coronary artery disease (CAD), that is, morphology and function. Both modalities have distinct advantages and shortcomings: While CCTA may prove a superb modality for excluding CAD through its excellent negative predictive value, it does not allow for assessment of hemodynamic relevance if obstructive coronary lesions are detected. Conversely, SPECT myocardial perfusion imaging cannot provide any information on the presence or absence of subclinical coronary atherosclerosis. This article aims to highlight the great potential of cardiac hybrid imaging that allows for a comprehensive evaluation of CAD through combination of both morphological and functional information by fusing SPECT with CCTA.
Computer Aided Design in Engineering Education.
ERIC Educational Resources Information Center
Gobin, R.
1986-01-01
Discusses the use of Computer Aided Design (CAD) and Computer Aided Manufacturing (CAM) systems in an undergraduate engineering education program. Provides a rationale for CAD/CAM use in the already existing engineering program. Describes the methods used in choosing the systems, some initial results, and warnings for first-time users. (TW)
NASA Astrophysics Data System (ADS)
Hoffmann, Sebastian; Shutler, Jamie D.; Lobbes, Marc; Burgeth, Bernhard; Meyer-Bäse, Anke
2013-12-01
Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) represents an established method for the detection and diagnosis of breast lesions. While mass-like enhancing lesions can be easily categorized according to the Breast Imaging Reporting and Data System (BI-RADS) MRI lexicon, a majority of diagnostically challenging lesions, the so called non-mass-like enhancing lesions, remain both qualitatively as well as quantitatively difficult to analyze. Thus, the evaluation of kinetic and/or morphological characteristics of non-masses represents a challenging task for an automated analysis and is of crucial importance for advancing current computer-aided diagnosis (CAD) systems. Compared to the well-characterized mass-enhancing lesions, non-masses have no well-defined and blurred tumor borders and a kinetic behavior that is not easily generalizable and thus discriminative for malignant and benign non-masses. To overcome these difficulties and pave the way for novel CAD systems for non-masses, we will evaluate several kinetic and morphological descriptors separately and a novel technique, the Zernike velocity moments, to capture the joint spatio-temporal behavior of these lesions, and additionally consider the impact of non-rigid motion compensation on a correct diagnosis.
Leal, Ermelindo C.; Martins, João; Voabil, Paula; Liberal, Joana; Chiavaroli, Carlo; Bauer, Jacques; Cunha-Vaz, José; Ambrósio, António F.
2010-01-01
OBJECTIVE Calcium dobesilate (CaD) has been used in the treatment of diabetic retinopathy in the last decades, but its mechanisms of action are not elucidated. CaD is able to correct the excessive vascular permeability in the retina of diabetic patients and in experimental diabetes. We investigated the molecular and cellular mechanisms underlying the protective effects of CaD against the increase in blood–retinal barrier (BRB) permeability induced by diabetes. RESEARCH DESIGN AND METHODS Wistar rats were divided into three groups: controls, streptozotocin-induced diabetic rats, and diabetic rats treated with CaD. The BRB breakdown was evaluated using Evans blue. The content or distribution of tight junction proteins (occludin, claudin-5, and zonula occluden-1 [ZO-1]), intercellular adhesion molecule-1 (ICAM-1), and p38 mitogen-activated protein kinase (p38 MAPK) was evaluated by Western blotting and immunohistochemistry. Leukocyte adhesion was evaluated in retinal vessels and in vitro. Oxidative stress was evaluated by the detection of oxidized carbonyls and tyrosine nitration. NF-κB activation was measured by enzyme-linked immunosorbent assay. RESULTS Diabetes increased the BRB permeability and retinal thickness. Diabetes also decreased occludin and claudin-5 levels and altered the distribution of ZO-1 and occludin in retinal vessels. These changes were inhibited by CaD treatment. CaD also inhibited the increase in leukocyte adhesion to retinal vessels or endothelial cells and in ICAM-1 levels, induced by diabetes or elevated glucose. Moreover, CaD decreased oxidative stress and p38 MAPK and NF-κB activation caused by diabetes. CONCLUSIONS CaD prevents the BRB breakdown induced by diabetes, by restoring tight junction protein levels and organization and decreasing leukocyte adhesion to retinal vessels. The protective effects of CaD are likely to involve the inhibition of p38 MAPK and NF-κB activation, possibly through the inhibition of oxidative/nitrosative stress. PMID:20627932
Chen, H; Ding, S; Zhou, M; Wu, X; Liu, X; Liu, J; Wu, Y; Liu, D
2017-08-23
A decreased plasma high density lipoprotein (HDL) cholesterol level is a strong risk factor for coronary artery disease (CAD). Antioxidant activity of HDL mainly lies in the activity of paraoxonase (PON). This study aimed to investigate the relationships between PON1 L55M and Q192R polymorphisms, and the risks of CAD in patients with hyperlipidemia. From January 2014 to January 2016, 244 patients were divided into hyperlipidemia, hyperlipidemia + CAD, and control groups. The hyperlipidemia and hyperlipidemia + CAD groups were designated as the case group. Serum PON1 concentrations were measured using the enzyme-linked immunosorbent assay. After isolating genomic DNA, the PON1 L55M and Q192R genes were amplified by polymerase chain reaction and sequenced. In the case group, the genotypes LM and LL were detected significantly more often than in the control group, as were the alleles R (33.33%, 42.12%) and L (22.78%, 29.11%). The frequency of QR and RR genotypes was significantly higher in the hyperlipidemia + CAD group than in the hyperlipidemia group; the allele R in the hyperlipidemia + CAD group (42.77%) was more frequent than in the hyperlipidemia group (23.78%). The Q192R polymorphism was associated with low serum PON1 concentrations, and the lowest concentration was observed in the 192QR + 192RR genotype (P = 0.03). Logistic regression analysis showed a significant correlation between the 192R allele and smoking (P = 0.03), body mass index (P = 0.02), systolic blood pressure (P = 0.004), total cholesterol (P = 0.03), triglycerides (P = 0.01), HDL (P = 0.004), and low density lipoprotein (P = 0.02). The PON1 alleles 192R and 55L are associated with CAD, and the Q192R polymorphism may be a risk factor for CAD.
Schulman-Marcus, Joshua; Lin, Fay Y.; Gransar, Heidi; Berman, Daniel; Callister, Tracy; DeLago, Augustin; Hadamitzky, Martin; Hausleiter, Joerg; Al-Mallah, Mouaz; Budoff, Matthew; Kaufmann, Philipp; Achenbach, Stephan; Raff, Gilbert; Chinnaiyan, Kavitha; Cademartiri, Filippo; Maffei, Erica; Villines, Todd; Kim, Yong-Jin; Leipsic, Jonathon; Feuchtner, Gudrun; Rubinshtein, Ronen; Pontone, Gianluca; Andreini, Daniele; Marques, Hugo; Chang, Hyuk-Jae; Chow, Benjamin J.W.; Cury, Ricardo C.; Dunning, Allison; Shaw, Leslee; Min, James K.
2017-01-01
Abstract Aims To identify the effect of early revascularization on 5-year survival in patients with CAD diagnosed by coronary-computed tomographic angiography (CCTA). Methods and results We examined 5544 stable patients with suspected CAD undergoing CCTA who were followed a median of 5.5 years in a large international registry. Patients were categorized as having low-, intermediate-, or high-risk CAD based on CCTA findings. Two treatment groups were defined: early revascularization within 90 days of CCTA (n = 1171) and medical therapy (n = 4373). To account for the non-randomized referral to revascularization, we developed a propensity score by logistic regression. This score was incorporated into Cox proportional hazard models to calculate the effect of revascularization on all-cause mortality. Death occurred in 363 (6.6%) patients and was more frequent in medical therapy. In multivariable models, when compared with medical therapy, the mortality benefit of revascularization varied significantly over time and by CAD risk (P for interaction 0.04). In high-risk CAD, revascularization was significantly associated with lower mortality at 1 year (hazard ratio [HR] 0.22, 95% confidence interval [CI] 0.11–0.47) and 5 years (HR 0.31, 95% CI 0.18–0.54). For intermediate-risk CAD, revascularization was associated with reduced mortality at 1 year (HR 0.45, 95% CI 0.22–0.93) but not 5 years (HR 0.63, 95% CI 0.33–1.20). For low-risk CAD, there was no survival benefit at either time point. Conclusions Early revascularization was associated with reduced 1-year mortality in intermediate- and high-risk CAD detected by CCTA, but this association only persisted for 5-year mortality in high-risk CAD. PMID:28329294
Horsch, Alexander; Hapfelmeier, Alexander; Elter, Matthias
2011-11-01
Breast cancer is globally a major threat for women's health. Screening and adequate follow-up can significantly reduce the mortality from breast cancer. Human second reading of screening mammograms can increase breast cancer detection rates, whereas this has not been proven for current computer-aided detection systems as "second reader". Critical factors include the detection accuracy of the systems and the screening experience and training of the radiologist with the system. When assessing the performance of systems and system components, the choice of evaluation methods is particularly critical. Core assets herein are reference image databases and statistical methods. We have analyzed characteristics and usage of the currently largest publicly available mammography database, the Digital Database for Screening Mammography (DDSM) from the University of South Florida, in literature indexed in Medline, IEEE Xplore, SpringerLink, and SPIE, with respect to type of computer-aided diagnosis (CAD) (detection, CADe, or diagnostics, CADx), selection of database subsets, choice of evaluation method, and quality of descriptions. 59 publications presenting 106 evaluation studies met our selection criteria. In 54 studies (50.9%), the selection of test items (cases, images, regions of interest) extracted from the DDSM was not reproducible. Only 2 CADx studies, not any CADe studies, used the entire DDSM. The number of test items varies from 100 to 6000. Different statistical evaluation methods are chosen. Most common are train/test (34.9% of the studies), leave-one-out (23.6%), and N-fold cross-validation (18.9%). Database-related terminology tends to be imprecise or ambiguous, especially regarding the term "case". Overall, both the use of the DDSM as data source for evaluation of mammography CAD systems, and the application of statistical evaluation methods were found highly diverse. Results reported from different studies are therefore hardly comparable. Drawbacks of the DDSM (e.g. varying quality of lesion annotations) may contribute to the reasons. But larger bias seems to be caused by authors' own decisions upon study design. RECOMMENDATIONS/CONCLUSION: For future evaluation studies, we derive a set of 13 recommendations concerning the construction and usage of a test database, as well as the application of statistical evaluation methods.
Maroules, Christopher D; Hamilton-Craig, Christian; Branch, Kelley; Lee, James; Cury, Roberto C; Maurovich-Horvat, Pál; Rubinshtein, Ronen; Thomas, Dustin; Williams, Michelle; Guo, Yanshu; Cury, Ricardo C
The Coronary Artery Disease Reporting and Data System (CAD-RADS) provides a lexicon and standardized reporting system for coronary CT angiography. To evaluate inter-observer agreement of the CAD-RADS among an panel of early career and expert readers. Four early career and four expert cardiac imaging readers prospectively and independently evaluated 50 coronary CT angiography cases using the CAD-RADS lexicon. All readers assessed image quality using a five-point Likert scale, with mean Likert score ≥4 designating high image quality, and <4 designating moderate/low image quality. All readers were blinded to medical history and invasive coronary angiography findings. Inter-observer agreement for CAD-RADS assessment categories and modifiers were assessed using intra-class correlation (ICC) and Fleiss' Kappa (κ).The impact of reader experience and image quality on inter-observer agreement was also examined. Inter-observer agreement for CAD-RADS assessment categories was excellent (ICC 0.958, 95% CI 0.938-0.974, p < 0.0001). Agreement among expert readers (ICC 0.925, 95% CI 0.884-0.954) was marginally stronger than for early career readers (ICC 0.904, 95% CI 0.852-0.941), both p < 0.0001. High image quality was associated with stronger agreement than moderate image quality (ICC 0.944, 95% CI 0.886-0.974 vs. ICC 0.887, 95% CI 0.775-0.95, both p < 0.0001). While excellent inter-observer agreement was observed for modifiers S (stent) and G (bypass graft) (both κ = 1.0), only fair agreement (κ = 0.40) was observed for modifier V (high risk plaque). Inter-observer reproducibility of CAD-RADS assessment categories and modifiers is excellent, except for high-risk plaque (modifier V) which demonstrates fair agreement. These results suggest CAD-RADS is feasible for clinical implementation. Copyright © 2017. Published by Elsevier Inc.
NASA Technical Reports Server (NTRS)
Rasmussen, John
1990-01-01
Structural optimization has attracted the attention since the days of Galileo. Olhoff and Taylor have produced an excellent overview of the classical research within this field. However, the interest in structural optimization has increased greatly during the last decade due to the advent of reliable general numerical analysis methods and the computer power necessary to use them efficiently. This has created the possibility of developing general numerical systems for shape optimization. Several authors, eg., Esping; Braibant & Fleury; Bennet & Botkin; Botkin, Yang, and Bennet; and Stanton have published practical and successful applications of general optimization systems. Ding and Homlein have produced extensive overviews of available systems. Furthermore, a number of commercial optimization systems based on well-established finite element codes have been introduced. Systems like ANSYS, IDEAS, OASIS, and NISAOPT are widely known examples. In parallel to this development, the technology of computer aided design (CAD) has gained a large influence on the design process of mechanical engineering. The CAD technology has already lived through a rapid development driven by the drastically growing capabilities of digital computers. However, the systems of today are still considered as being only the first generation of a long row of computer integrated manufacturing (CIM) systems. These systems to come will offer an integrated environment for design, analysis, and fabrication of products of almost any character. Thus, the CAD system could be regarded as simply a database for geometrical information equipped with a number of tools with the purpose of helping the user in the design process. Among these tools are facilities for structural analysis and optimization as well as present standard CAD features like drawing, modeling, and visualization tools. The state of the art of structural optimization is that a large amount of mathematical and mechanical techniques are available for the solution of single problems. By implementing collections of the available techniques into general software systems, operational environments for structural optimization have been created. The forthcoming years must bring solutions to the problem of integrating such systems into more general design environments. The result of this work should be CAD systems for rational design in which structural optimization is one important design tool among many others.
Truong, Quynh A; Knaapen, Paul; Pontone, Gianluca; Andreini, Daniele; Leipsic, Jonathon; Carrascosa, Patricia; Lu, Bin; Branch, Kelley; Raman, Subha; Bloom, Stephen; Min, James K
2015-10-01
Dual-energy CT (DECT) has potential to improve myocardial perfusion for physiologic assessment of coronary artery disease (CAD). Diagnostic performance of rest-stress DECT perfusion (DECTP) is unknown. DECIDE-Gold is a prospective multicenter study to evaluate the accuracy of DECT to detect hemodynamic (HD) significant CAD, as compared to fractional flow reserve (FFR) as a reference standard. Eligible participants are subjects with symptoms of CAD referred for invasive coronary angiography (ICA). Participants will undergo DECTP, which will be performed by pharmacological stress, and participants will subsequently proceed to ICA and FFR. HD-significant CAD will be defined as FFR ≤ 0.80. In those undergoing myocardial stress imaging (MPI) by positron emission tomography (PET), single photon emission computed tomography (SPECT) or cardiac magnetic resonance (CMR) imaging, ischemia will be graded by % ischemic myocardium. Blinded core laboratory interpretation will be performed for CCTA, DECTP, MPI, ICA, and FFR. Primary endpoint is accuracy of DECTP to detect ≥1 HD-significant stenosis at the subject level when compared to FFR. Secondary and tertiary endpoints are accuracies of combinations of DECTP at the subject and vessel levels compared to FFR and MPI. DECIDE-Gold will determine the performance of DECTP for diagnosing ischemia.
Castro, Alfonso; Boveda, Carmen; Arcay, Bernardino; Sanjurjo, Pedro
2016-01-01
The detection of pulmonary nodules is one of the most studied problems in the field of medical image analysis due to the great difficulty in the early detection of such nodules and their social impact. The traditional approach involves the development of a multistage CAD system capable of informing the radiologist of the presence or absence of nodules. One stage in such systems is the detection of ROI (regions of interest) that may be nodules in order to reduce the space of the problem. This paper evaluates fuzzy clustering algorithms that employ different classification strategies to achieve this goal. After characterising these algorithms, the authors propose a new algorithm and different variations to improve the results obtained initially. Finally it is shown as the most recent developments in fuzzy clustering are able to detect regions that may be nodules in CT studies. The algorithms were evaluated using helical thoracic CT scans obtained from the database of the LIDC (Lung Image Database Consortium). PMID:27517049
Ma, Heng; Yang, Jun; Liu, Jing; Ge, Lan; An, Jing; Tang, Qing; Li, Han; Zhang, Yu; Chen, David; Wang, Yong; Liu, Jiabin; Liang, Zhigang; Lin, Kai; Jin, Lixin; Bi, Xiaoming; Li, Kuncheng; Li, Debiao
2012-04-15
Myocardial perfusion magnetic resonance imaging (MRI) with sliding-window conjugate-gradient highly constrained back-projection reconstruction (SW-CG-HYPR) allows whole left ventricular coverage, improved temporal and spatial resolution and signal/noise ratio, and reduced cardiac motion-related image artifacts. The accuracy of this technique for detecting coronary artery disease (CAD) has not been determined in a large number of patients. We prospectively evaluated the diagnostic performance of myocardial perfusion MRI with SW-CG-HYPR in patients with suspected CAD. A total of 50 consecutive patients who were scheduled for coronary angiography with suspected CAD underwent myocardial perfusion MRI with SW-CG-HYPR at 3.0 T. The perfusion defects were interpreted qualitatively by 2 blinded observers and were correlated with x-ray angiographic stenoses ≥50%. The prevalence of CAD was 56%. In the per-patient analysis, the sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of SW-CG-HYPR was 96% (95% confidence interval 82% to 100%), 82% (95% confidence interval 60% to 95%), 87% (95% confidence interval 70% to 96%), 95% (95% confidence interval 74% to100%), and 90% (95% confidence interval 82% to 98%), respectively. In the per-vessel analysis, the corresponding values were 98% (95% confidence interval 91% to 100%), 89% (95% confidence interval 80% to 94%), 86% (95% confidence interval 76% to 93%), 99% (95% confidence interval 93% to 100%), and 93% (95% confidence interval 89% to 97%), respectively. In conclusion, myocardial perfusion MRI using SW-CG-HYPR allows whole left ventricular coverage and high resolution and has high diagnostic accuracy in patients with suspected CAD. Copyright © 2012 Elsevier Inc. All rights reserved.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Li Ping; Napel, Sandy; Acar, Burak
2004-10-01
Computed tomography colonography (CTC) is a minimally invasive method that allows the evaluation of the colon wall from CT sections of the abdomen/pelvis. The primary goal of CTC is to detect colonic polyps, precursors to colorectal cancer. Because imperfect cleansing and distension can cause portions of the colon wall to be collapsed, covered with water, and/or covered with retained stool, patients are scanned in both prone and supine positions. We believe that both reading efficiency and computer aided detection (CAD) of CTC images can be improved by accurate registration of data from the supine and prone positions. We developed amore » two-stage approach that first registers the colonic central paths using a heuristic and automated algorithm and then matches polyps or polyp candidates (CAD hits) by a statistical approach. We evaluated the registration algorithm on 24 patient cases. After path registration, the mean misalignment distance between prone and supine identical anatomic landmarks was reduced from 47.08 to 12.66 mm, a 73% improvement. The polyp registration algorithm was specifically evaluated using eight patient cases for which radiologists identified polyps separately for both supine and prone data sets, and then manually registered corresponding pairs. The algorithm correctly matched 78% of these pairs without user input. The algorithm was also applied to the 30 highest-scoring CAD hits in the prone and supine scans and showed a success rate of 50% in automatically registering corresponding polyp pairs. Finally, we computed the average number of CAD hits that need to be manually compared in order to find the correct matches among the top 30 CAD hits. With polyp registration, the average number of comparisons was 1.78 per polyp, as opposed to 4.28 comparisons without polyp registration.« less
Liu, Min; Zhang, Chunsun; Liu, Feifei
2015-09-03
In this work, we first introduce the fabrication of microfluidic cloth-based analytical devices (μCADs) using a wax screen-printing approach that is suitable for simple, inexpensive, rapid, low-energy-consumption and high-throughput preparation of cloth-based analytical devices. We have carried out a detailed study on the wax screen-printing of μCADs and have obtained some interesting results. Firstly, an analytical model is established for the spreading of molten wax in cloth. Secondly, a new wax screen-printing process has been proposed for fabricating μCADs, where the melting of wax into the cloth is much faster (∼5 s) and the heating temperature is much lower (75 °C). Thirdly, the experimental results show that the patterning effects of the proposed wax screen-printing method depend to a certain extent on types of screens, wax melting temperatures and melting time. Under optimized conditions, the minimum printing width of hydrophobic wax barrier and hydrophilic channel is 100 μm and 1.9 mm, respectively. Importantly, the developed analytical model is also well validated by these experiments. Fourthly, the μCADs fabricated by the presented wax screen-printing method are used to perform a proof-of-concept assay of glucose or protein in artificial urine with rapid high-throughput detection taking place on a 48-chamber cloth-based device and being performed by a visual readout. Overall, the developed cloth-based wax screen-printing and arrayed μCADs should provide a new research direction in the development of advanced sensor arrays for detection of a series of analytes relevant to many diverse applications. Copyright © 2015 Elsevier B.V. All rights reserved.
Toutouzas, Konstantinos; Benetos, Georgios; Koutagiar, Iosif; Barampoutis, Nikolaos; Mitropoulou, Fotini; Davlouros, Periklis; Sfikakis, Petros P; Alexopoulos, Dimitrios; Stefanadis, Christodoulos; Siores, Elias; Tousoulis, Dimitris
2017-07-01
Limited prospective data have been reported regarding the impact of carotid inflammation on cardiovascular events in patients with coronary artery disease (CAD). Microwave radiometry (MWR) is a noninvasive, simple method that has been used for evaluation of carotid artery temperature which, when increased, predicts 'inflamed' plaques with vulnerable characteristics. We prospectively tested the hypothesis that increased carotid artery temperature predicts future cerebro- and cardiovascular events in patients with CAD. Consecutive patients from 3 centers, with documented CAD by coronary angiography, were studied. In both carotid arteries, common carotid intima-media thickness and plaque thickness were evaluated by ultrasound. Temperature difference (ΔT), measured by MWR, was considered as the maximal temperature along the carotid artery minus the minimum; ΔT ≥0.90 °C was assigned as high. Major cardiovascular events (MACE, death, stroke, myocardial infarction or revascularization) were recorded during the following year. In total, 250 patients were studied; of them 40 patients (16%) had high ΔT values in both carotid arteries. MACEs occurred in 30% of patients having bilateral high ΔT versus 3.8% in the remaining patients (p<0.001). Bilateral high ΔT was independently associated with increased one-year MACE rate (HR = 6.32, 95% CI 2.42-16.53, p<0.001, by multivariate cox regression hazard model). The addition of ΔT information on a baseline model based on cardiovascular risk factors and extent of CAD significantly increased the prognostic value of the model (c-statistic increase 0.744 to 0.845, p dif = 0.05) CONCLUSIONS: Carotid inflammation, detected by MWR, has an incremental prognostic value in patients with documented CAD. Copyright © 2017 Elsevier B.V. All rights reserved.
NASA Astrophysics Data System (ADS)
Heidari, Morteza; Zargari Khuzani, Abolfazl; Danala, Gopichandh; Qiu, Yuchen; Zheng, Bin
2018-02-01
Objective of this study is to develop and test a new computer-aided detection (CAD) scheme with improved region of interest (ROI) segmentation combined with an image feature extraction framework to improve performance in predicting short-term breast cancer risk. A dataset involving 570 sets of "prior" negative mammography screening cases was retrospectively assembled. In the next sequential "current" screening, 285 cases were positive and 285 cases remained negative. A CAD scheme was applied to all 570 "prior" negative images to stratify cases into the high and low risk case group of having cancer detected in the "current" screening. First, a new ROI segmentation algorithm was used to automatically remove useless area of mammograms. Second, from the matched bilateral craniocaudal view images, a set of 43 image features related to frequency characteristics of ROIs were initially computed from the discrete cosine transform and spatial domain of the images. Third, a support vector machine model based machine learning classifier was used to optimally classify the selected optimal image features to build a CAD-based risk prediction model. The classifier was trained using a leave-one-case-out based cross-validation method. Applying this improved CAD scheme to the testing dataset, an area under ROC curve, AUC = 0.70+/-0.04, which was significantly higher than using the extracting features directly from the dataset without the improved ROI segmentation step (AUC = 0.63+/-0.04). This study demonstrated that the proposed approach could improve accuracy on predicting short-term breast cancer risk, which may play an important role in helping eventually establish an optimal personalized breast cancer paradigm.
Khomri, Bilal; Christodoulidis, Argyrios; Djerou, Leila; Babahenini, Mohamed Chaouki; Cheriet, Farida
2018-05-01
Retinal vessel segmentation plays an important role in the diagnosis of eye diseases and is considered as one of the most challenging tasks in computer-aided diagnosis (CAD) systems. The main goal of this study was to propose a method for blood-vessel segmentation that could deal with the problem of detecting vessels of varying diameters in high- and low-resolution fundus images. We proposed to use the particle swarm optimization (PSO) algorithm to improve the multiscale line detection (MSLD) method. The PSO algorithm was applied to find the best arrangement of scales in the MSLD method and to handle the problem of multiscale response recombination. The performance of the proposed method was evaluated on two low-resolution (DRIVE and STARE) and one high-resolution fundus (HRF) image datasets. The data include healthy (H) and diabetic retinopathy (DR) cases. The proposed approach improved the sensitivity rate against the MSLD by 4.7% for the DRIVE dataset and by 1.8% for the STARE dataset. For the high-resolution dataset, the proposed approach achieved 87.09% sensitivity rate, whereas the MSLD method achieves 82.58% sensitivity rate at the same specificity level. When only the smallest vessels were considered, the proposed approach improved the sensitivity rate by 11.02% and by 4.42% for the healthy and the diabetic cases, respectively. Integrating the proposed method in a comprehensive CAD system for DR screening would allow the reduction of false positives due to missed small vessels, misclassified as red lesions. (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).
NASA Astrophysics Data System (ADS)
Alfano, R.; Soetemans, D.; Bauman, G. S.; Gibson, E.; Gaed, M.; Moussa, M.; Gomez, J. A.; Chin, J. L.; Pautler, S.; Ward, A. D.
2018-02-01
Multi-parametric MRI (mp-MRI) is becoming a standard in contemporary prostate cancer screening and diagnosis, and has shown to aid physicians in cancer detection. It offers many advantages over traditional systematic biopsy, which has shown to have very high clinical false-negative rates of up to 23% at all stages of the disease. However beneficial, mp-MRI is relatively complex to interpret and suffers from inter-observer variability in lesion localization and grading. Computer-aided diagnosis (CAD) systems have been developed as a solution as they have the power to perform deterministic quantitative image analysis. We measured the accuracy of such a system validated using accurately co-registered whole-mount digitized histology. We trained a logistic linear classifier (LOGLC), support vector machine (SVC), k-nearest neighbour (KNN) and random forest classifier (RFC) in a four part ROI based experiment against: 1) cancer vs. non-cancer, 2) high-grade (Gleason score ≥4+3) vs. low-grade cancer (Gleason score <4+3), 3) high-grade vs. other tissue components and 4) high-grade vs. benign tissue by selecting the classifier with the highest AUC using 1-10 features from forward feature selection. The CAD model was able to classify malignant vs. benign tissue and detect high-grade cancer with high accuracy. Once fully validated, this work will form the basis for a tool that enhances the radiologist's ability to detect malignancies, potentially improving biopsy guidance, treatment selection, and focal therapy for prostate cancer patients, maximizing the potential for cure and increasing quality of life.
Dessouky, Mohamed M; Elrashidy, Mohamed A; Taha, Taha E; Abdelkader, Hatem M
2016-05-01
The different discrete transform techniques such as discrete cosine transform (DCT), discrete sine transform (DST), discrete wavelet transform (DWT), and mel-scale frequency cepstral coefficients (MFCCs) are powerful feature extraction techniques. This article presents a proposed computer-aided diagnosis (CAD) system for extracting the most effective and significant features of Alzheimer's disease (AD) using these different discrete transform techniques and MFCC techniques. Linear support vector machine has been used as a classifier in this article. Experimental results conclude that the proposed CAD system using MFCC technique for AD recognition has a great improvement for the system performance with small number of significant extracted features, as compared with the CAD system based on DCT, DST, DWT, and the hybrid combination methods of the different transform techniques. © The Author(s) 2015.
Productivity increase through implementation of CAD/CAE workstation
NASA Technical Reports Server (NTRS)
Bromley, L. K.
1985-01-01
The tracking and communication division computer aided design/computer aided engineering system is now operational. The system is utilized in an effort to automate certain tasks that were previously performed manually. These tasks include detailed test configuration diagrams of systems under certification test in the ESTL, floorplan layouts of future planned laboratory reconfigurations, and other graphical documentation of division activities. The significant time savings achieved with this CAD/CAE system are examined: (1) input of drawings and diagrams; (2) editing of initial drawings; (3) accessibility of the data; and (4) added versatility. It is shown that the Applicon CAD/CAE system, with its ease of input and editing, the accessibility of data, and its added versatility, has made more efficient many of the necessary but often time-consuming tasks associated with engineering design and testing.
Common genetic risk factors for coronary artery disease: new opportunities for prevention?
Hamrefors, Viktor
2017-05-01
Atherosclerotic cardiovascular disease (CVD) is a leading cause of mortality and morbidity worldwide, with coronary artery disease (CAD) being the single leading cause of death. Better control of risk factors, enhanced diagnostic techniques and improved medical therapies have all substantially decreased the mortality of CAD in developed countries. However, CAD and other forms of atherosclerotic CVD are projected to remain the leading cause of death by 2030 and we face a number of challenges if the outcomes of CAD are to be further improved. The fact that a substantial fraction of high-risk subjects do not reach treatment goals for important risk factors is one of these challenges. At the same time, there is also a non-negotiable fraction of 'concealed' high-risk subjects who are not detected by current risk algorithms and diagnostic modalities. In recent years, we have started to rapidly increase our knowledge of the framework of common genetics underlying CAD and atherosclerotic CVD in the population. In conjunction with modern diagnostic and therapeutic options, this new genetic knowledge may provide a valuable tool for further improvements in prevention. This review summarizes the recent findings from the search for common genetic risk factors for CAD. Furthermore, the author discusses how such recent findings could potentially be used in a number of clinical applications within CAD prevention, including in clinical risk stratification, in prediction of drug treatment response and in the search for targets for novel preventive therapies. © 2015 Scandinavian Society of Clinical Physiology and Nuclear Medicine. Published by John Wiley & Sons Ltd.
NASA Astrophysics Data System (ADS)
Ali, Abder-Rahman A.; Deserno, Thomas M.
2012-02-01
Malignant melanoma is the third most frequent type of skin cancer and one of the most malignant tumors, accounting for 79% of skin cancer deaths. Melanoma is highly curable if diagnosed early and treated properly as survival rate varies between 15% and 65% from early to terminal stages, respectively. So far, melanoma diagnosis is depending subjectively on the dermatologist's expertise. Computer-aided diagnosis (CAD) systems based on epiluminescense light microscopy can provide an objective second opinion on pigmented skin lesions (PSL). This work systematically analyzes the evidence of the effectiveness of automated melanoma detection in images from a dermatoscopic device. Automated CAD applications were analyzed to estimate their diagnostic outcome. Searching online databases for publication dates between 1985 and 2011, a total of 182 studies on dermatoscopic CAD were found. With respect to the systematic selection criterions, 9 studies were included, published between 2002 and 2011. Those studies formed databases of 14,421 dermatoscopic images including both malignant "melanoma" and benign "nevus", with 8,110 images being available ranging in resolution from 150 x 150 to 1568 x 1045 pixels. Maximum and minimum of sensitivity and specificity are 100.0% and 80.0% as well as 98.14% and 61.6%, respectively. Area under the receiver operator characteristics (AUC) and pooled sensitivity, specificity and diagnostics odds ratio are respectively 0.87, 0.90, 0.81, and 15.89. So, although that automated melanoma detection showed good accuracy in terms of sensitivity, specificity, and AUC, but diagnostic performance in terms of DOR was found to be poor. This might be due to the lack of dermatoscopic image resources (ground truth) that are needed for comprehensive assessment of diagnostic performance. In future work, we aim at testing this hypothesis by joining dermatoscopic images into a unified database that serves as a standard reference for dermatology related research in PSL classification.
Bohner, Lauren Oliveira Lima; Neto, Pedro Tortamano; Ahmed, Ahad Shahid; Mori, Matsuyoshi; Laganá, Dalva Cruz; Sesma, Newton
2016-07-01
The aim of this review was to update the literature with regard to the digital methods available by CEREC Chairside system to register and design the occlusion, to report their efficacy and technical innovations in the field of Restorative Dentistry. A search strategy was performed using the key-words: "virtual articulator," or "CAD-CAM and occlusal recording," or "CAD-CAM and occlusion register," or "CAD-CAM and occlusal contacts," or "CAD-CAM and prosthesis." Inclusion criteria comprised studies evaluating the use of digital methods available by CEREC System for occlusal registration and design during prosthodontics treatment. PubMed and Cochrane library and reference lists were searched up to January 2016. The search resulted in 280 articles after removing duplicates. Subsequently, 233 records were excluded and 49 studies were selected for reading in full. Eleven articles were considered eligible for the systematic review (4 in vitro and 7 clinical studies). Scientific evidence suggests that digital methods were accurate to register and design the occlusion of dental prostheses. Nevertheless, further clinical studies are required to establish a conclusion with regard to its accuracy in prosthodontics treatment. Digital technologies allow the design of occlusal surfaces of CAD-CAM fabricated prostheses using innovative approaches. This systematic review aimed to update the literature to help dentists determine the most appropriate digital method to register and design the occlusal surface of CAD-CAM crowns. (J Esthet Restor Dent 28:208-220, 2016). © 2016 Wiley Periodicals, Inc.
Young, Stefano; Lo, Pechin; Kim, Grace; Brown, Matthew; Hoffman, John; Hsu, William; Wahi-Anwar, Wasil; Flores, Carlos; Lee, Grace; Noo, Frederic; Goldin, Jonathan; McNitt-Gray, Michael
2017-04-01
Lung cancer screening with low-dose CT has recently been approved for reimbursement, heralding the arrival of such screening services worldwide. Computer-aided detection (CAD) tools offer the potential to assist radiologists in detecting nodules in these screening exams. In lung screening, as in all CT exams, there is interest in further reducing radiation dose. However, the effects of continued dose reduction on CAD performance are not fully understood. In this work, we investigated the effect of reducing radiation dose on CAD lung nodule detection performance in a screening population. The raw projection data files were collected from 481 patients who underwent low-dose screening CT exams at our institution as part of the National Lung Screening Trial (NLST). All scans were performed on a multidetector scanner (Sensation 64, Siemens Healthcare, Forchheim Germany) according to the NLST protocol, which called for a fixed tube current scan of 25 effective mAs for standard-sized patients and 40 effective mAs for larger patients. The raw projection data were input to a reduced-dose simulation software to create simulated reduced-dose scans corresponding to 50% and 25% of the original protocols. All raw data files were reconstructed at the scanner with 1 mm slice thickness and B50 kernel. The lungs were segmented semi-automatically, and all images and segmentations were input to an in-house CAD algorithm trained on higher dose scans (75-300 mAs). CAD findings were compared to a reference standard generated by an experienced reader. Nodule- and patient-level sensitivities were calculated along with false positives per scan, all of which were evaluated in terms of the relative change with respect to dose. Nodules were subdivided based on size and solidity into categories analogous to the LungRADS assessment categories, and sub-analyses were performed. From the 481 patients in this study, 82 had at least one nodule (prevalence of 17%) and 399 did not (83%). A total of 118 nodules were identified. Twenty-seven nodules (23%) corresponded to LungRADS category 4 based on size and composition, while 18 (15%) corresponded to LungRADS category 3 and 73 (61%) corresponded to LungRADS category 2. For solid nodules ≥8 mm, patient-level median sensitivities were 100% at all three dose levels, and mean sensitivities were 72%, 63%, and 63% at original, 50%, and 25% dose, respectively. Overall mean patient-level sensitivities for nodules ranging from 3 to 45 mm were 38%, 37%, and 38% at original, 50%, and 25% dose due to the prevalence of smaller nodules and nonsolid nodules in our reference standard. The mean false-positive rates were 3, 5, and 13 per case. CAD sensitivity decreased very slightly for larger nodules as dose was reduced, indicating that reducing the dose to 50% of original levels may be investigated further for use in CT screening. However, the effect of dose was small relative to the effect of the nodule size and solidity characteristics. The number of false positives per scan increased substantially at 25% dose, illustrating the importance of tuning CAD algorithms to very challenging, high-noise screening exams. © 2017 American Association of Physicists in Medicine.
NASA Astrophysics Data System (ADS)
Uchiyama, Yoshikazu; Asano, Tatsunori; Hara, Takeshi; Fujita, Hiroshi; Kinosada, Yasutomi; Asano, Takahiko; Kato, Hiroki; Kanematsu, Masayuki; Hoshi, Hiroaki; Iwama, Toru
2009-02-01
The detection of cerebrovascular diseases such as unruptured aneurysm, stenosis, and occlusion is a major application of magnetic resonance angiography (MRA). However, their accurate detection is often difficult for radiologists. Therefore, several computer-aided diagnosis (CAD) schemes have been developed in order to assist radiologists with image interpretation. The purpose of this study was to develop a computerized method for segmenting cerebral arteries, which is an essential component of CAD schemes. For the segmentation of vessel regions, we first used a gray level transformation to calibrate voxel values. To adjust for variations in the positioning of patients, registration was subsequently employed to maximize the overlapping of the vessel regions in the target image and reference image. The vessel regions were then segmented from the background using gray-level thresholding and region growing techniques. Finally, rule-based schemes with features such as size, shape, and anatomical location were employed to distinguish between vessel regions and false positives. Our method was applied to 854 clinical cases obtained from two different hospitals. The segmentation of cerebral arteries in 97.1%(829/854) of the MRA studies was attained as an acceptable result. Therefore, our computerized method would be useful in CAD schemes for the detection of cerebrovascular diseases in MRA images.
Analysis of HOM Problems in the C-ADS Main Linac
DOE Office of Scientific and Technical Information (OSTI.GOV)
Huang, Burn; Ng, King Yuen
2017-05-18
Excitation of higher-order modes (HOMs) in superconducting cavities may severely affect the operation of the main linac in the Chinese Accelerator Driven System (CADS). Preliminary analysis is made on the effects of beam dynamic, which includes possible longitudinal and transverse emittance enlargements, as well as the possibility of beam breakup. Suggestions are given for further investigation. Comparison is made between the C-ADS and the Fermilab Project X.
Integrating three-dimensional digital technologies for comprehensive implant dentistry.
Patel, Neal
2010-06-01
The increase in the popularity of and the demand for the use of dental implants to replace teeth has encouraged advancement in clinical technology and materials to improve patients' acceptance and clinical outcomes. Recent advances such as three-dimensional dental radiography with cone-beam computed tomography (CBCT), precision dental implant planning software and clinical execution with guided surgery all play a role in the success of implant dentistry. The author illustrates the technique of comprehensive implant dentistry planning through integration of computer-aided design/computer-aided manufacturing (CAD/CAM) and CBCT data. The technique includes clinical treatment with guided surgery, including the creation of a final restoration with a high-strength ceramic (IPS e.max CAD, Ivoclar Vivadent, Amherst, N.Y.). The author also introduces a technique involving CAD/CAM for fabricating custom implant abutments. The release of software integrating CEREC Acquisition Center with Bluecam (Sirona Dental Systems, Charlotte, N.C.) chairside CAD/CAM and Galileos CBCT imaging (Sirona Dental Systems) allows dentists to plan implant placement, perform implant dentistry with increased precision and provide predictable restorative results by using chairside IPS e.max CAD. The precision of clinical treatment provided by the integration of CAD/CAM and CBCT allows dentists to plan for ideal surgical placement and the appropriate thickness of restorative modalities before placing implants.
Mieres, Jennifer H; Shaw, Leslee J; Hendel, Robert C; Heller, Gary V
2009-01-01
Coronary artery disease remains the leading cause of morbidity and mortality in women. The optimal non-invasive test for evaluation of ischemic heart disease in women is unknown. Although current guidelines support the choice of the exercise tolerance test (ETT) as a first line test for women with a normal baseline ECG and adequate exercise capabilities, supportive data for this recommendation are controversial. The what is the optimal method for ischemia evaluation in women? (WOMEN) study was designed to determine the optimal non-invasive strategy for CAD risk detection of intermediate and high risk women presenting with chest pain or equivalent symptoms suggestive of ischemic heart disease. The study will prospectively compare the 2-year event rates in women capable of performing exercise treadmill testing or Tc-99 m tetrofosmin SPECT myocardial perfusion imaging (MPI). The study will enroll women presenting for the evaluation of chest pain or anginal equivalent symptoms who are capable of performing >5 METs of exercise while at intermediate-high pretest risk for ischemic heart disease who will be randomized to either ETT testing alone or with Tc-99 m tetrofosmin SPECT MPI. The null hypothesis for this project is that the exercise ECG has the same negative predictive value for risk detection as gated myocardial perfusion SPECT in women. The primary aim is to compare 2-year cardiac event rates in women randomized to SPECT MPI to those randomized to ETT. The WOMEN study seeks to provide objective information for guidelines for the evaluation of symptomatic women with an intermediate-high likelihood for CAD.
Variable size computer-aided detection prompts and mammography film reader decisions
Gilbert, Fiona J; Astley, Susan M; Boggis, Caroline RM; McGee, Magnus A; Griffiths, Pamela M; Duffy, Stephen W; Agbaje, Olorunsola F; Gillan, Maureen GC; Wilson, Mary; Jain, Anil K; Barr, Nicola; Beetles, Ursula M; Griffiths, Miriam A; Johnson, Jill; Roberts, Rita M; Deans, Heather E; Duncan, Karen A; Iyengar, Geeta
2008-01-01
Introduction The purpose of the present study was to investigate the effect of computer-aided detection (CAD) prompts on reader behaviour in a large sample of breast screening mammograms by analysing the relationship of the presence and size of prompts to the recall decision. Methods Local research ethics committee approval was obtained; informed consent was not required. Mammograms were obtained from women attending routine mammography at two breast screening centres in 1996. Films, previously double read, were re-read by a different reader using CAD. The study material included 315 cancer cases comprising all screen-detected cancer cases, all subsequent interval cancers and 861 normal cases randomly selected from 10,267 cases. Ground truth data were used to assess the efficacy of CAD prompting. Associations between prompt attributes and tumour features or reader recall decisions were assessed by chi-squared tests. Results There was a highly significant relationship between prompting and a decision to recall for cancer cases and for a random sample of normal cases (P < 0.001). Sixty-four per cent of all cases contained at least one CAD prompt. In cancer cases, larger prompts were more likely to be recalled (P = 0.02) for masses but there was no such association for calcifications (P = 0.9). In a random sample of 861 normal cases, larger prompts were more likely to be recalled (P = 0.02) for both mass and calcification prompts. Significant associations were observed with prompting and breast density (p = 0.009) for cancer cases but not for normal cases (P = 0.05). Conclusions For both normal cases and cancer cases, prompted mammograms were more likely to be recalled and the prompt size was also associated with a recall decision. PMID:18724867
Variable size computer-aided detection prompts and mammography film reader decisions.
Gilbert, Fiona J; Astley, Susan M; Boggis, Caroline Rm; McGee, Magnus A; Griffiths, Pamela M; Duffy, Stephen W; Agbaje, Olorunsola F; Gillan, Maureen Gc; Wilson, Mary; Jain, Anil K; Barr, Nicola; Beetles, Ursula M; Griffiths, Miriam A; Johnson, Jill; Roberts, Rita M; Deans, Heather E; Duncan, Karen A; Iyengar, Geeta
2008-01-01
The purpose of the present study was to investigate the effect of computer-aided detection (CAD) prompts on reader behaviour in a large sample of breast screening mammograms by analysing the relationship of the presence and size of prompts to the recall decision. Local research ethics committee approval was obtained; informed consent was not required. Mammograms were obtained from women attending routine mammography at two breast screening centres in 1996. Films, previously double read, were re-read by a different reader using CAD. The study material included 315 cancer cases comprising all screen-detected cancer cases, all subsequent interval cancers and 861 normal cases randomly selected from 10,267 cases. Ground truth data were used to assess the efficacy of CAD prompting. Associations between prompt attributes and tumour features or reader recall decisions were assessed by chi-squared tests. There was a highly significant relationship between prompting and a decision to recall for cancer cases and for a random sample of normal cases (P < 0.001). Sixty-four per cent of all cases contained at least one CAD prompt. In cancer cases, larger prompts were more likely to be recalled (P = 0.02) for masses but there was no such association for calcifications (P = 0.9). In a random sample of 861 normal cases, larger prompts were more likely to be recalled (P = 0.02) for both mass and calcification prompts. Significant associations were observed with prompting and breast density (p = 0.009) for cancer cases but not for normal cases (P = 0.05). For both normal cases and cancer cases, prompted mammograms were more likely to be recalled and the prompt size was also associated with a recall decision.
Novel Cadmium Resistance Determinant in Listeria monocytogenes.
Parsons, Cameron; Lee, Sangmi; Jayeola, Victor; Kathariou, Sophia
2017-03-01
Listeria monocytogenes is a foodborne pathogen that can cause severe disease (listeriosis) in susceptible individuals. It is ubiquitous in the environment and often exhibits resistance to heavy metals. One of the determinants that enables Listeria to tolerate exposure to cadmium is the cadAC efflux system, with CadA being a P-type ATPase. Three different cadA genes (designated cadA1 to cadA3 ) were previously characterized in L. monocytogenes A novel putative cadmium resistance gene ( cadA4 ) was recently identified through whole-genome sequencing, but experimental confirmation for its involvement in cadmium resistance is lacking. In this study, we characterized cadA4 in L. monocytogenes strain F8027, a cadmium-resistant strain of serotype 4b. By screening a mariner-based transposon library of this strain, we identified a mutant with reduced tolerance to cadmium and that harbored a single transposon insertion in cadA4 The tolerance to cadmium was restored by genetic complementation with the cadmium resistance cassette ( cadA4C ), and enhanced cadmium tolerance was conferred to two unrelated cadmium-sensitive strains via heterologous complementation with cadA4C Cadmium exposure induced cadA4 expression, even at noninhibitory levels. Virulence assessments in the Galleria mellonella model suggested that a functional cadA4 suppressed virulence, potentially promoting commensal colonization of the insect larvae. Biofilm assays suggested that cadA4 inactivation reduced biofilm formation. These data not only confirm cadA4 as a novel cadmium resistance determinant in L. monocytogenes but also provide evidence for roles in virulence and biofilm formation. IMPORTANCE Listeria monocytogenes is an intracellular foodborne pathogen causing the disease listeriosis, which is responsible for numerous hospitalizations and deaths every year. Among the adaptations that enable the survival of Listeria in the environment are the abilities to persist in biofilms, grow in the cold, and tolerate toxic compounds, such as heavy metals. Here, we characterized a novel determinant that was recently identified on a larger mobile genetic island through whole-genome sequencing. This gene ( cadA4 ) was found to be responsible for cadmium detoxification and to be a divergent member of the Cad family of cadmium efflux pumps. Virulence assessments in a Galleria mellonella model suggested that cadA4 may suppress virulence. Additionally, cadA4 may be involved in the ability of Listeria to form biofilms. Beyond the role in cadmium detoxification, the involvement of cadA4 in other cellular functions potentially explains its retention and wide distribution in L. monocytogenes . Copyright © 2017 American Society for Microbiology.
A/E/C CAD Standard, Release 4.0
2009-07-01
Insulating (Transformer) Oil System Lubrication Oil Hot Water Heating System Machine Design Appendix A Model File Level/Layer Assignment Tables A51...of the A /E/C CAD Standard are: “Uniform Drawing System ” The Construction Specifications Institute 99 Canal Center Plaza, Suite 300 Alexandria, VA...FM – Facility Management GIS – Geographic Information System IAI – International Alliance for Interoperability IFC – Industry Foundation
Increasing productivity of the McAuto CAD/CAE system by user-specific applications programming
NASA Technical Reports Server (NTRS)
Plotrowski, S. M.; Vu, T. H.
1985-01-01
Significant improvements in the productivity of the McAuto Computer-Aided Design/Computer-Aided Engineering (CAD/CAE) system were achieved by applications programming using the system's own Graphics Interactive Programming language (GRIP) and the interface capabilities with the main computer on which the system resides. The GRIP programs for creating springs, bar charts, finite element model representations and aiding management planning are presented as examples.
Research on computer-aided design of modern marine power systems
NASA Astrophysics Data System (ADS)
Ding, Dongdong; Zeng, Fanming; Chen, Guojun
2004-03-01
To make the MPS (Marine Power System) design process more economical and easier, a new CAD scheme is brought forward which takes much advantage of VR (Virtual Reality) and AI (Artificial Intelligence) technologies. This CAD system can shorten the period of design and reduce the requirements on designers' experience in large scale. And some key issues like the selection of hardware and software of such a system are discussed.
ERIC Educational Resources Information Center
Nee, John G.; Kare, Audhut P.
1987-01-01
Explores several concepts in computer assisted design/computer assisted manufacturing (CAD/CAM). Defines, evaluates, reviews and compares advanced computer-aided geometric modeling and analysis techniques. Presents the results of a survey to establish the capabilities of minicomputer based-systems with the CAD/CAM packages evaluated. (CW)
Challoumas, Dimitrios; Stavrou, Antonio; Pericleous, Agamemnon; Dimitrakakis, Georgios
2015-02-01
Despite the growing body of evidence on the potential effects of calcium and vitamin D as monotherapies on different cardiovascular (CV) parameters, the combined supplementation with calcium and vitamin D (CaD), which is most frequently encountered in clinical practice, has not received the attention it deserves. A literature search was conducted via EMBASE and Medline and identified 14 randomised controlled trials (RCTs) and 2 meta-analyses reporting on effects of combined supplementation with CaD on CV events, CV death, blood pressure, lipids, glucose metabolism and weight. Overall, the existing evidence does not support beneficial properties of supplementation with CaD on the CV system, nor does it suggest that a re-appraisal of the use of CaD is necessary due to adverse effects, although increased risk of CV events has been reported by some authors. The guidelines for the use of CaD supplementation need not change until well-conducted RCTs that have CV effects as primary outcomes and adjust for major confounders indicate otherwise. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.
Qintao, Cui; Yan, Li; Changhong, Duan; Xiaoliang, Guo; Xiaochen, Liu
2014-12-01
Coronary artery disease (CAD) receives intensive research due to its high incidence and severe impact on the quality of life. One member of the matrix metalloproteinases (MMPs), MMP-1, has been reported to be associated with CAD. To identify the markers contributing to the genetic susceptibility to CAD, nine single-nucleotide polymorphisms (rs1799750, rs498186, rs475007, rs514921, rs494379, rs996999, rs2071232, rs1938901, and rs2239008) throughout the MMP-1 gene were genotyped using MALDI-TOF within the MassARRAY system, and the allele and genotype distributions were compared between 438 healthy controls and 411 patients with CAD from a Chinese Han population. The analysis revealed a weak association between the rs1799750 (in the promoter region) genotype distribution and CAD (p=0.022). An increased risk of CAD was significantly associated with the 2G allele of rs1799750 (p=0.005, odds ratio=1.329, 95% confidence interval=1.090-1.620, after Bonferroni corrections). Strong linkage disequilibrium was observed in three blocks (D'>0.9). Significantly more C-2G (rs498186-rs1799750) haplotypes (p=0.001 after Bonferroni corrections) were found in CAD subjects. These findings point to a role for the polymorphism in the MMP-1 promoter in CAD among a Han Chinese population and may be informative for future genetic or biological studies on CAD.