Wavelet Entropy and Directed Acyclic Graph Support Vector Machine for Detection of Patients with Unilateral Hearing Loss in MRI Scanning.

PubMed

Wang, Shuihua; Yang, Ming; Du, Sidan; Yang, Jiquan; Liu, Bin; Gorriz, Juan M; Ramírez, Javier; Yuan, Ti-Fei; Zhang, Yudong

2016-01-01

Highlights We develop computer-aided diagnosis system for unilateral hearing loss detection in structural magnetic resonance imaging.Wavelet entropy is introduced to extract image global features from brain images. Directed acyclic graph is employed to endow support vector machine an ability to handle multi-class problems.The developed computer-aided diagnosis system achieves an overall accuracy of 95.1% for this three-class problem of differentiating left-sided and right-sided hearing loss from healthy controls. Aim: Sensorineural hearing loss (SNHL) is correlated to many neurodegenerative disease. Now more and more computer vision based methods are using to detect it in an automatic way. Materials: We have in total 49 subjects, scanned by 3.0T MRI (Siemens Medical Solutions, Erlangen, Germany). The subjects contain 14 patients with right-sided hearing loss (RHL), 15 patients with left-sided hearing loss (LHL), and 20 healthy controls (HC). Method: We treat this as a three-class classification problem: RHL, LHL, and HC. Wavelet entropy (WE) was selected from the magnetic resonance images of each subjects, and then submitted to a directed acyclic graph support vector machine (DAG-SVM). Results: The 10 repetition results of 10-fold cross validation shows 3-level decomposition will yield an overall accuracy of 95.10% for this three-class classification problem, higher than feedforward neural network, decision tree, and naive Bayesian classifier. Conclusions: This computer-aided diagnosis system is promising. We hope this study can attract more computer vision method for detecting hearing loss.

Computed-aided diagnosis (CAD) in the detection of breast cancer.

PubMed

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.

Mutual information-based template matching scheme for detection of breast masses: from mammography to digital breast tomosynthesis

PubMed Central

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

Computer-aided diagnosis workstation and database system for chest diagnosis based on multi-helical CT images

NASA Astrophysics Data System (ADS)

Satoh, Hitoshi; Niki, Noboru; Mori, Kiyoshi; Eguchi, Kenji; Kaneko, Masahiro; Kakinuma, Ryutarou; Moriyama, Noriyuki; Ohmatsu, Hironobu; Masuda, Hideo; Machida, Suguru; Sasagawa, Michizou

2006-03-01

Multi-helical CT scanner advanced remarkably at the speed at which the chest CT images were acquired for mass screening. Mass screening based on multi-helical CT images requires a considerable number of images to be read. It is this time-consuming step that makes the use of helical CT for mass screening impractical at present. To overcome this problem, we have provided diagnostic assistance methods to medical screening specialists by developing a lung cancer screening algorithm that automatically detects suspected lung cancers in helical CT images and a coronary artery calcification screening algorithm that automatically detects suspected coronary artery calcification. We also have developed electronic medical recording system and prototype internet system for the community health in two or more regions by using the Virtual Private Network router and Biometric fingerprint authentication system and Biometric face authentication system for safety of medical information. Based on these diagnostic assistance methods, we have now developed a new computer-aided workstation and database that can display suspected lesions three-dimensionally in a short time. This paper describes basic studies that have been conducted to evaluate this new system. The results of this study indicate that our computer-aided diagnosis workstation and network system can increase diagnostic speed, diagnostic accuracy and safety of medical information.

Computer-aided detection of breast lesions in DCE-MRI using region growing based on fuzzy C-means clustering and vesselness filter

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.

FINDS: A fault inferring nonlinear detection system programmers manual, version 3.0

NASA Technical Reports Server (NTRS)

Lancraft, R. E.

1985-01-01

Detailed software documentation of the digital computer program FINDS (Fault Inferring Nonlinear Detection System) Version 3.0 is provided. FINDS is a highly modular and extensible computer program designed to monitor and detect sensor failures, while at the same time providing reliable state estimates. In this version of the program the FINDS methodology is used to detect, isolate, and compensate for failures in simulated avionics sensors used by the Advanced Transport Operating Systems (ATOPS) Transport System Research Vehicle (TSRV) in a Microwave Landing System (MLS) environment. It is intended that this report serve as a programmers guide to aid in the maintenance, modification, and revision of the FINDS software.

Computer-aided Detection of Prostate Cancer with MRI: Technology and Applications.

PubMed

Liu, Lizhi; Tian, Zhiqiang; Zhang, Zhenfeng; Fei, Baowei

2016-08-01

One in six men will develop prostate cancer in his lifetime. Early detection and accurate diagnosis of the disease can improve cancer survival and reduce treatment costs. Recently, imaging of prostate cancer has greatly advanced since the introduction of multiparametric magnetic resonance imaging (mp-MRI). Mp-MRI consists of T2-weighted sequences combined with functional sequences including dynamic contrast-enhanced MRI, diffusion-weighted MRI, and magnetic resonance spectroscopy imaging. Because of the big data and variations in imaging sequences, detection can be affected by multiple factors such as observer variability and visibility and complexity of the lesions. To improve quantitative assessment of the disease, various computer-aided detection systems have been designed to help radiologists in their clinical practice. This review paper presents an overview of literatures on computer-aided detection of prostate cancer with mp-MRI, which include the technology and its applications. The aim of the survey is threefold: an introduction for those new to the field, an overview for those working in the field, and a reference for those searching for literature on a specific application. Copyright © 2016 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

Computer-aided diagnosis workstation and telemedicine network system for chest diagnosis based on multislice CT images

NASA Astrophysics Data System (ADS)

Satoh, Hitoshi; Niki, Noboru; Eguchi, Kenji; Ohmatsu, Hironobu; Kakinuma, Ryutaru; Moriyama, Noriyuki

2009-02-01

Mass screening based on multi-helical CT images requires a considerable number of images to be read. It is this time-consuming step that makes the use of helical CT for mass screening impractical at present. Moreover, the doctor who diagnoses a medical image is insufficient in Japan. To overcome these problems, we have provided diagnostic assistance methods to medical screening specialists by developing a lung cancer screening algorithm that automatically detects suspected lung cancers in helical CT images, a coronary artery calcification screening algorithm that automatically detects suspected coronary artery calcification and a vertebra body analysis algorithm for quantitative evaluation of osteoporosis likelihood by using helical CT scanner for the lung cancer mass screening. The functions to observe suspicious shadow in detail are provided in computer-aided diagnosis workstation with these screening algorithms. We also have developed the telemedicine network by using Web medical image conference system with the security improvement of images transmission, Biometric fingerprint authentication system and Biometric face authentication system. Biometric face authentication used on site of telemedicine makes "Encryption of file" and "Success in login" effective. As a result, patients' private information is protected. We can share the screen of Web medical image conference system from two or more web conference terminals at the same time. An opinion can be exchanged mutually by using a camera and a microphone that are connected with workstation. Based on these diagnostic assistance methods, we have developed a new computer-aided workstation and a new telemedicine network that can display suspected lesions three-dimensionally in a short time. The results of this study indicate that our radiological information system without film by using computer-aided diagnosis workstation and our telemedicine network system can increase diagnostic speed, diagnostic accuracy and security improvement of medical information.

75 FR 16123 - Dave & Buster’s, Inc.; Analysis of Proposed Consent Order to Aid Public Comment

Federal Register 2010, 2011, 2012, 2013, 2014

2010-03-31

... computer networks or to conduct security investigations, such as by employing an intrusion detection system and monitoring system logs; (b) failed to adequately restrict third-party access to its networks, such... reasonable and appropriate security for personal information on its computer networks. Among other things...

Foundation and methodologies in computer-aided diagnosis systems for breast cancer detection.

PubMed

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

PubMed Central

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

Feasibility Study of a Generalized Framework for Developing Computer-Aided Detection Systems-a New Paradigm.

PubMed

Nemoto, Mitsutaka; Hayashi, Naoto; Hanaoka, Shouhei; Nomura, Yukihiro; Miki, Soichiro; Yoshikawa, Takeharu

2017-10-01

We propose a generalized framework for developing computer-aided detection (CADe) systems whose characteristics depend only on those of the training dataset. The purpose of this study is to show the feasibility of the framework. Two different CADe systems were experimentally developed by a prototype of the framework, but with different training datasets. The CADe systems include four components; preprocessing, candidate area extraction, candidate detection, and candidate classification. Four pretrained algorithms with dedicated optimization/setting methods corresponding to the respective components were prepared in advance. The pretrained algorithms were sequentially trained in the order of processing of the components. In this study, two different datasets, brain MRA with cerebral aneurysms and chest CT with lung nodules, were collected to develop two different types of CADe systems in the framework. The performances of the developed CADe systems were evaluated by threefold cross-validation. The CADe systems for detecting cerebral aneurysms in brain MRAs and for detecting lung nodules in chest CTs were successfully developed using the respective datasets. The framework was shown to be feasible by the successful development of the two different types of CADe systems. The feasibility of this framework shows promise for a new paradigm in the development of CADe systems: development of CADe systems without any lesion specific algorithm designing.

High-performance computer aided detection system for polyp detection in CT colonography with fluid and fecal tagging

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.

Second CLIPS Conference Proceedings, volume 1

NASA Technical Reports Server (NTRS)

Giarratano, Joseph (Editor); Culbert, Christopher J. (Editor)

1991-01-01

Topics covered at the 2nd CLIPS Conference held at the Johnson Space Center, September 23-25, 1991 are given. Topics include rule groupings, fault detection using expert systems, decision making using expert systems, knowledge representation, computer aided design and debugging expert systems.

Analog Computer-Aided Detection (CAD) information can be more effective than binary marks.

PubMed

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.

Automatic detection of pulmonary nodules at spiral CT: first clinical experience with a computer-aided diagnosis system

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.

Improved computer-aided detection of small polyps in CT colonography using interpolation for curvature estimationa

PubMed Central

Liu, Jiamin; Kabadi, Suraj; Van Uitert, Robert; Petrick, Nicholas; Deriche, Rachid; Summers, Ronald M.

2011-01-01

Purpose: Surface curvatures are important geometric features for the computer-aided analysis and detection of polyps in CT colonography (CTC). However, the general kernel approach for curvature computation can yield erroneous results for small polyps and for polyps that lie on haustral folds. Those erroneous curvatures will reduce the performance of polyp detection. This paper presents an analysis of interpolation’s effect on curvature estimation for thin structures and its application on computer-aided detection of small polyps in CTC. Methods: The authors demonstrated that a simple technique, image interpolation, can improve the accuracy of curvature estimation for thin structures and thus significantly improve the sensitivity of small polyp detection in CTC. Results: Our experiments showed that the merits of interpolating included more accurate curvature values for simulated data, and isolation of polyps near folds for clinical data. After testing on a large clinical data set, it was observed that sensitivities with linear, quadratic B-spline and cubic B-spline interpolations significantly improved the sensitivity for small polyp detection. Conclusions: The image interpolation can improve the accuracy of curvature estimation for thin structures and thus improve the computer-aided detection of small polyps in CTC. PMID:21859029

Potential clinical impact of advanced imaging and computer-aided diagnosis in chest radiology: importance of radiologist's role and successful observer study.

PubMed

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.

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.

Automatic bone detection and soft tissue aware ultrasound-CT registration for computer-aided orthopedic surgery.

PubMed

Wein, Wolfgang; Karamalis, Athanasios; Baumgartner, Adrian; Navab, Nassir

2015-06-01

The transfer of preoperative CT data into the tracking system coordinates within an operating room is of high interest for computer-aided orthopedic surgery. In this work, we introduce a solution for intra-operative ultrasound-CT registration of bones. We have developed methods for fully automatic real-time bone detection in ultrasound images and global automatic registration to CT. The bone detection algorithm uses a novel bone-specific feature descriptor and was thoroughly evaluated on both in-vivo and ex-vivo data. A global optimization strategy aligns the bone surface, followed by a soft tissue aware intensity-based registration to provide higher local registration accuracy. We evaluated the system on femur, tibia and fibula anatomy in a cadaver study with human legs, where magnetically tracked bone markers were implanted to yield ground truth information. An overall median system error of 3.7 mm was achieved on 11 datasets. Global and fully automatic registration of bones aquired with ultrasound to CT is feasible, with bone detection and tracking operating in real time for immediate feedback to the surgeon.

Segmentation and detection of breast cancer in mammograms combining wavelet analysis and genetic algorithm.

PubMed

Pereira, Danilo Cesar; Ramos, Rodrigo Pereira; do Nascimento, Marcelo Zanchetta

2014-04-01

In Brazil, the National Cancer Institute (INCA) reports more than 50,000 new cases of the disease, with risk of 51 cases per 100,000 women. Radiographic images obtained from mammography equipments are one of the most frequently used techniques for helping in early diagnosis. Due to factors related to cost and professional experience, in the last two decades computer systems to support detection (Computer-Aided Detection - CADe) and diagnosis (Computer-Aided Diagnosis - CADx) have been developed in order to assist experts in detection of abnormalities in their initial stages. Despite the large number of researches on CADe and CADx systems, there is still a need for improved computerized methods. Nowadays, there is a growing concern with the sensitivity and reliability of abnormalities diagnosis in both views of breast mammographic images, namely cranio-caudal (CC) and medio-lateral oblique (MLO). This paper presents a set of computational tools to aid segmentation and detection of mammograms that contained mass or masses in CC and MLO views. An artifact removal algorithm is first implemented followed by an image denoising and gray-level enhancement method based on wavelet transform and Wiener filter. Finally, a method for detection and segmentation of masses using multiple thresholding, wavelet transform and genetic algorithm is employed in mammograms which were randomly selected from the Digital Database for Screening Mammography (DDSM). The developed computer method was quantitatively evaluated using the area overlap metric (AOM). The mean ± standard deviation value of AOM for the proposed method was 79.2 ± 8%. The experiments demonstrate that the proposed method has a strong potential to be used as the basis for mammogram mass segmentation in CC and MLO views. Another important aspect is that the method overcomes the limitation of analyzing only CC and MLO views. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

A Set of Image Processing Algorithms for Computer-Aided Diagnosis in Nuclear Medicine Whole Body Bone Scan Images

NASA Astrophysics Data System (ADS)

Huang, Jia-Yann; Kao, Pan-Fu; Chen, Yung-Sheng

2007-06-01

Adjustment of brightness and contrast in nuclear medicine whole body bone scan images may confuse nuclear medicine physicians when identifying small bone lesions as well as making the identification of subtle bone lesion changes in sequential studies difficult. In this study, we developed a computer-aided diagnosis system, based on the fuzzy sets histogram thresholding method and anatomical knowledge-based image segmentation method that was able to analyze and quantify raw image data and identify the possible location of a lesion. To locate anatomical reference points, the fuzzy sets histogram thresholding method was adopted as a first processing stage to suppress the soft tissue in the bone images. Anatomical knowledge-based image segmentation method was then applied to segment the skeletal frame into different regions of homogeneous bones. For the different segmented bone regions, the lesion thresholds were set at different cut-offs. To obtain lesion thresholds in different segmented regions, the ranges and standard deviations of the image's gray-level distribution were obtained from 100 normal patients' whole body bone images and then, another 62 patients' images were used for testing. The two groups of images were independent. The sensitivity and the mean number of false lesions detected were used as performance indices to evaluate the proposed system. The overall sensitivity of the system is 92.1% (222 of 241) and 7.58 false detections per patient scan image. With a high sensitivity and an acceptable false lesions detection rate, this computer-aided automatic lesion detection system is demonstrated as useful and will probably in the future be able to help nuclear medicine physicians to identify possible bone lesions.

Terrestrial implications of mathematical modeling developed for space biomedical research

NASA Technical Reports Server (NTRS)

Lujan, Barbara F.; White, Ronald J.; Leonard, Joel I.; Srinivasan, R. Srini

1988-01-01

This paper summarizes several related research projects supported by NASA which seek to apply computer models to space medicine and physiology. These efforts span a wide range of activities, including mathematical models used for computer simulations of physiological control systems; power spectral analysis of physiological signals; pattern recognition models for detection of disease processes; and computer-aided diagnosis programs.

Analog Computer-Aided Detection (CAD) information can be more effective than binary marks

PubMed Central

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

A dental vision system for accurate 3D tooth modeling.

PubMed

Zhang, Li; Alemzadeh, K

2006-01-01

This paper describes an active vision system based reverse engineering approach to extract the three-dimensional (3D) geometric information from dental teeth and transfer this information into Computer-Aided Design/Computer-Aided Manufacture (CAD/CAM) systems to improve the accuracy of 3D teeth models and at the same time improve the quality of the construction units to help patient care. The vision system involves the development of a dental vision rig, edge detection, boundary tracing and fast & accurate 3D modeling from a sequence of sliced silhouettes of physical models. The rig is designed using engineering design methods such as a concept selection matrix and weighted objectives evaluation chart. Reconstruction results and accuracy evaluation are presented on digitizing different teeth models.

Robust Nucleus/Cell Detection and Segmentation in Digital Pathology and Microscopy Images: A Comprehensive Review.

PubMed

Xing, Fuyong; Yang, Lin

2016-01-01

Digital pathology and microscopy image analysis is widely used for comprehensive studies of cell morphology or tissue structure. Manual assessment is labor intensive and prone to interobserver variations. Computer-aided methods, which can significantly improve the objectivity and reproducibility, have attracted a great deal of interest in recent literature. Among the pipeline of building a computer-aided diagnosis system, nucleus or cell detection and segmentation play a very important role to describe the molecular morphological information. In the past few decades, many efforts have been devoted to automated nucleus/cell detection and segmentation. In this review, we provide a comprehensive summary of the recent state-of-the-art nucleus/cell segmentation approaches on different types of microscopy images including bright-field, phase-contrast, differential interference contrast, fluorescence, and electron microscopies. In addition, we discuss the challenges for the current methods and the potential future work of nucleus/cell detection and segmentation.

Computer-aided diagnostic system for detection of Hashimoto thyroiditis on ultrasound images from a Polish population.

PubMed

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.

Bi-model processing for early detection of breast tumor in CAD system

NASA Astrophysics Data System (ADS)

Mughal, Bushra; Sharif, Muhammad; Muhammad, Nazeer

2017-06-01

Early screening of skeptical masses in mammograms may reduce mortality rate among women. This rate can be further reduced upon developing the computer-aided diagnosis system with decrease in false assumptions in medical informatics. This method highlights the early tumor detection in digitized mammograms. For improving the performance of this system, a novel bi-model processing algorithm is introduced. It divides the region of interest into two parts, the first one is called pre-segmented region (breast parenchyma) and other is the post-segmented region (suspicious region). This system follows the scheme of the preprocessing technique of contrast enhancement that can be utilized to segment and extract the desired feature of the given mammogram. In the next phase, a hybrid feature block is presented to show the effective performance of computer-aided diagnosis. In order to assess the effectiveness of the proposed method, a database provided by the society of mammographic images is tested. Our experimental outcomes on this database exhibit the usefulness and robustness of the proposed method.

Computer-aided head film analysis: the University of California San Francisco method.

PubMed

Baumrind, S; Miller, D M

1980-07-01

Computer technology is already assuming an important role in the management of orthodontic practices. The next 10 years are likely to see expansion in computer usage into the areas of diagnosis, treatment planning, and treatment-record keeping. In the areas of diagnosis and treatment planning, one of the first problems to be attacked will be the automation of head film analysis. The problems of constructing computer-aided systems for this purpose are considered herein in the light of the authors' 10 years of experience in developing a similar system for research purposes. The need for building in methods for automatic detection and correction of gross errors is discussed and the authors' method for doing so is presented. The construction of a rudimentary machine-readable data base for research and clinical purposes is described.

Anniversary Paper: History and status of CAD and quantitative image analysis: The role of Medical Physics and AAPM

PubMed Central

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

Anniversary Paper: History and status of CAD and quantitative image analysis: The role of Medical Physics and AAPM

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

Evaluation of Microcomputer-Based Operation and Maintenance Management Systems for Army Water/Wastewater Treatment Plant Operation.

DTIC Science & Technology

1986-07-01

COMPUTER-AIDED OPERATION MANAGEMENT SYSTEM ................. 29 Functions of an Off-Line Computer-Aided Operation Management System Applications of...System Comparisons 85 DISTRIBUTION 5V J. • 0. FIGURES Number Page 1 Hardware Components 21 2 Basic Functions of a Computer-Aided Operation Management System...Plant Visits 26 4 Computer-Aided Operation Management Systems Reviewed for Analysis of Basic Functions 29 5 Progress of Software System Installation and

RASCAL: A Rudimentary Adaptive System for Computer-Aided Learning.

ERIC Educational Resources Information Center

Stewart, John Christopher

Both the background of computer-assisted instruction (CAI) systems in general and the requirements of a computer-aided learning system which would be a reasonable assistant to a teacher are discussed. RASCAL (Rudimentary Adaptive System for Computer-Aided Learning) is a first attempt at defining a CAI system which would individualize the learning…

Computer Aided Detection of Breast Masses in Digital Tomosynthesis

DTIC Science & Technology

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

The Feasibility of Classifying Breast Masses Using a Computer-Assisted Diagnosis (CAD) System Based on Ultrasound Elastography and BI-RADS Lexicon.

PubMed

Fleury, Eduardo F C; Gianini, Ana Claudia; Marcomini, Karem; Oliveira, Vilmar

2018-01-01

To determine the applicability of a computer-aided diagnostic system strain elastography system for the classification of breast masses diagnosed by ultrasound and scored using the criteria proposed by the breast imaging and reporting data system ultrasound lexicon and to determine the diagnostic accuracy and interobserver variability. This prospective study was conducted between March 1, 2016, and May 30, 2016. A total of 83 breast masses subjected to percutaneous biopsy were included. Ultrasound elastography images before biopsy were interpreted by 3 radiologists with and without the aid of computer-aided diagnostic system for strain elastography. The parameters evaluated by each radiologist results were sensitivity, specificity, and diagnostic accuracy, with and without computer-aided diagnostic system for strain elastography. Interobserver variability was assessed using a weighted κ test and an intraclass correlation coefficient. The areas under the receiver operating characteristic curves were also calculated. The areas under the receiver operating characteristic curve were 0.835, 0.801, and 0.765 for readers 1, 2, and 3, respectively, without computer-aided diagnostic system for strain elastography, and 0.900, 0.926, and 0.868, respectively, with computer-aided diagnostic system for strain elastography. The intraclass correlation coefficient between the 3 readers was 0.6713 without computer-aided diagnostic system for strain elastography and 0.811 with computer-aided diagnostic system for strain elastography. The proposed computer-aided diagnostic system for strain elastography system has the potential to improve the diagnostic performance of radiologists in breast examination using ultrasound associated with elastography.

[Development of a Computer-aided Diagnosis System to Distinguish between Benign and Malignant Mammary Tumors in Dynamic Magnetic Resonance Images: Automatic Detection of the Position with the Strongest Washout Effect in the Tumor].

PubMed

Miyazaki, Yoshiaki; Tabata, Nobuyuki; Taroura, Tomomi; Shinozaki, Kenji; Kubo, Yuichiro; Tokunaga, Eriko; Taguchi, Kenichi

We propose a computer-aided diagnostic (CAD) system that uses time-intensity curves to distinguish between benign and malignant mammary tumors. Many malignant tumors show a washout pattern in time-intensity curves. Therefore, we designed a program that automatically detects the position with the strongest washout effect using the technique, such as the subtraction technique, which extracts only the washout area in the tumor, and by scanning data in 2×2 pixel region of interest (ROI). Operation of this independently developed program was verified using a phantom system that simulated tumors. In three cases of malignant tumors, the washout pattern detection rate in images with manually set ROI was ≤6%, whereas the detection rate with our novel method was 100%. In one case of a benign tumor, when the same method was used, we checked that there was no washout effect and detected the persistent pattern. Thus, the distinction between benign and malignant tumors using our method was completely consistent with the pathological diagnoses made. Our novel method is therefore effective for differentiating between benign and malignant mammary tumors in dynamic magnetic resonance images.

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.

Improving computer-aided detection assistance in breast cancer screening by removal of obviously false-positive findings.

PubMed

Mordang, Jan-Jurre; Gubern-Mérida, Albert; Bria, Alessandro; Tortorella, Francesco; den Heeten, Gerard; Karssemeijer, Nico

2017-04-01

Computer-aided detection (CADe) systems for mammography screening still mark many false positives. This can cause radiologists to lose confidence in CADe, especially when many false positives are obviously not suspicious to them. In this study, we focus on obvious false positives generated by microcalcification detection algorithms. We aim at reducing the number of obvious false-positive findings by adding an additional step in the detection method. In this step, a multiclass machine learning method is implemented in which dedicated classifiers learn to recognize the patterns of obvious false-positive subtypes that occur most frequently. The method is compared to a conventional two-class approach, where all false-positive subtypes are grouped together in one class, and to the baseline CADe system without the new false-positive removal step. The methods are evaluated on an independent dataset containing 1,542 screening examinations of which 80 examinations contain malignant microcalcifications. Analysis showed that the multiclass approach yielded a significantly higher sensitivity compared to the other two methods (P < 0.0002). At one obvious false positive per 100 images, the baseline CADe system detected 61% of the malignant examinations, while the systems with the two-class and multiclass false-positive reduction step detected 73% and 83%, respectively. Our study showed that by adding the proposed method to a CADe system, the number of obvious false positives can decrease significantly (P < 0.0002). © 2017 American Association of Physicists in Medicine.

Computer-Aided Diagnosis Systems for Lung Cancer: Challenges and Methodologies

PubMed Central

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

Computer-aided detection system for lung cancer in computed tomography scans: Review and future prospects

PubMed Central

2014-01-01

Introduction The goal of this paper is to present a critical review of major Computer-Aided Detection systems (CADe) for lung cancer in order to identify challenges for future research. CADe systems must meet the following requirements: improve the performance of radiologists providing high sensitivity in the diagnosis, a low number of false positives (FP), have high processing speed, present high level of automation, low cost (of implementation, training, support and maintenance), the ability to detect different types and shapes of nodules, and software security assurance. Methods The relevant literature related to “CADe for lung cancer” was obtained from PubMed, IEEEXplore and Science Direct database. Articles published from 2009 to 2013, and some articles previously published, were used. A systemic analysis was made on these articles and the results were summarized. Discussion Based on literature search, it was observed that many if not all systems described in this survey have the potential to be important in clinical practice. However, no significant improvement was observed in sensitivity, number of false positives, level of automation and ability to detect different types and shapes of nodules in the studied period. Challenges were presented for future research. Conclusions Further research is needed to improve existing systems and propose new solutions. For this, we believe that collaborative efforts through the creation of open source software communities are necessary to develop a CADe system with all the requirements mentioned and with a short development cycle. In addition, future CADe systems should improve the level of automation, through integration with picture archiving and communication systems (PACS) and the electronic record of the patient, decrease the number of false positives, measure the evolution of tumors, evaluate the evolution of the oncological treatment, and its possible prognosis. PMID:24713067

Computer-aided detection system for lung cancer in computed tomography scans: review and future prospects.

PubMed

Firmino, Macedo; Morais, Antônio H; Mendoça, Roberto M; Dantas, Marcel R; Hekis, Helio R; Valentim, Ricardo

2014-04-08

The goal of this paper is to present a critical review of major Computer-Aided Detection systems (CADe) for lung cancer in order to identify challenges for future research. CADe systems must meet the following requirements: improve the performance of radiologists providing high sensitivity in the diagnosis, a low number of false positives (FP), have high processing speed, present high level of automation, low cost (of implementation, training, support and maintenance), the ability to detect different types and shapes of nodules, and software security assurance. The relevant literature related to "CADe for lung cancer" was obtained from PubMed, IEEEXplore and Science Direct database. Articles published from 2009 to 2013, and some articles previously published, were used. A systemic analysis was made on these articles and the results were summarized. Based on literature search, it was observed that many if not all systems described in this survey have the potential to be important in clinical practice. However, no significant improvement was observed in sensitivity, number of false positives, level of automation and ability to detect different types and shapes of nodules in the studied period. Challenges were presented for future research. Further research is needed to improve existing systems and propose new solutions. For this, we believe that collaborative efforts through the creation of open source software communities are necessary to develop a CADe system with all the requirements mentioned and with a short development cycle. In addition, future CADe systems should improve the level of automation, through integration with picture archiving and communication systems (PACS) and the electronic record of the patient, decrease the number of false positives, measure the evolution of tumors, evaluate the evolution of the oncological treatment, and its possible prognosis.

Employment Opportunities for the Handicapped in Programmable Automation.

ERIC Educational Resources Information Center

Swift, Richard; Leneway, Robert

A Computer Integrated Manufacturing System may make it possible for severely disabled people to custom design, machine, and manufacture either wood or metal parts. Programmable automation merges computer aided design, computer aided manufacturing, computer aided engineering, and computer integrated manufacturing systems with automated production…

Evaluation of a computer-aided detection algorithm for timely diagnosis of small acute intracranial hemorrhage on computed tomography in a critical care environment

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.

Applicability of mathematical modeling to problems of environmental physiology

NASA Technical Reports Server (NTRS)

White, Ronald J.; Lujan, Barbara F.; Leonard, Joel I.; Srinivasan, R. Srini

1988-01-01

The paper traces the evolution of mathematical modeling and systems analysis from terrestrial research to research related to space biomedicine and back again to terrestrial research. Topics covered include: power spectral analysis of physiological signals; pattern recognition models for detection of disease processes; and, computer-aided diagnosis programs used in conjunction with a special on-line biomedical computer library.

The effect of feature selection methods on computer-aided detection of masses in mammograms

NASA Astrophysics Data System (ADS)

Hupse, Rianne; Karssemeijer, Nico

2010-05-01

In computer-aided diagnosis (CAD) research, feature selection methods are often used to improve generalization performance of classifiers and shorten computation times. In an application that detects malignant masses in mammograms, we investigated the effect of using a selection criterion that is similar to the final performance measure we are optimizing, namely the mean sensitivity of the system in a predefined range of the free-response receiver operating characteristics (FROC). To obtain the generalization performance of the selected feature subsets, a cross validation procedure was performed on a dataset containing 351 abnormal and 7879 normal regions, each region providing a set of 71 mass features. The same number of noise features, not containing any information, were added to investigate the ability of the feature selection algorithms to distinguish between useful and non-useful features. It was found that significantly higher performances were obtained using feature sets selected by the general test statistic Wilks' lambda than using feature sets selected by the more specific FROC measure. Feature selection leads to better performance when compared to a system in which all features were used.

Robust Nucleus/Cell Detection and Segmentation in Digital Pathology and Microscopy Images: A Comprehensive Review

PubMed Central

Xing, Fuyong; Yang, Lin

2016-01-01

Digital pathology and microscopy image analysis is widely used for comprehensive studies of cell morphology or tissue structure. Manual assessment is labor intensive and prone to inter-observer variations. Computer-aided methods, which can significantly improve the objectivity and reproducibility, have attracted a great deal of interest in recent literatures. Among the pipeline of building a computer-aided diagnosis system, nucleus or cell detection and segmentation play a very important role to describe the molecular morphological information. In the past few decades, many efforts have been devoted to automated nucleus/cell detection and segmentation. In this review, we provide a comprehensive summary of the recent state-of-the-art nucleus/cell segmentation approaches on different types of microscopy images including bright-field, phase-contrast, differential interference contrast (DIC), fluorescence, and electron microscopies. In addition, we discuss the challenges for the current methods and the potential future work of nucleus/cell detection and segmentation. PMID:26742143

Advanced instrumentation concepts for environmental control subsystems

NASA Technical Reports Server (NTRS)

Yang, P. Y.; Schubert, F. H.; Gyorki, J. R.; Wynveen, R. A.

1978-01-01

Design, evaluation and demonstration of advanced instrumentation concepts for improving performance of manned spacecraft environmental control and life support systems were successfully completed. Concepts to aid maintenance following fault detection and isolation were defined. A computer-guided fault correction instruction program was developed and demonstrated in a packaged unit which also contains the operator/system interface.

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).

Computer-aided detection and quantification of endolymphatic hydrops within the mouse cochlea in vivo using optical coherence tomography

NASA Astrophysics Data System (ADS)

Liu, George S.; Kim, Jinkyung; Applegate, Brian E.; Oghalai, John S.

2017-07-01

Diseases that cause hearing loss and/or vertigo in humans such as Meniere's disease are often studied using animal models. The volume of endolymph within the inner ear varies with these diseases. Here, we used a mouse model of increased endolymph volume, endolymphatic hydrops, to develop a computer-aided objective approach to measure endolymph volume from images collected in vivo using optical coherence tomography. The displacement of Reissner's membrane from its normal position was measured in cochlear cross sections. We validated our computer-aided measurements with manual measurements and with trained observer labels. This approach allows for computer-aided detection of endolymphatic hydrops in mice, with test performance showing sensitivity of 91% and specificity of 87% using a running average of five measurements. These findings indicate that this approach is accurate and reliable for classifying endolymphatic hydrops and quantifying endolymph volume.

The effects of different restorative materials on the detection of approximal caries in cone-beam computed tomography scans with and without metal artifact reduction mode.

PubMed

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.

Computer-aided detection of basal cell carcinoma through blood content analysis in dermoscopy images

NASA Astrophysics Data System (ADS)

Kharazmi, Pegah; Kalia, Sunil; Lui, Harvey; Wang, Z. Jane; Lee, Tim K.

2018-02-01

Basal cell carcinoma (BCC) is the most common type of skin cancer, which is highly damaging to the skin at its advanced stages and causes huge costs on the healthcare system. However, most types of BCC are easily curable if detected at early stage. Due to limited access to dermatologists and expert physicians, non-invasive computer-aided diagnosis is a viable option for skin cancer screening. A clinical biomarker of cancerous tumors is increased vascularization and excess blood flow. In this paper, we present a computer-aided technique to differentiate cancerous skin tumors from benign lesions based on vascular characteristics of the lesions. Dermoscopy image of the lesion is first decomposed using independent component analysis of the RGB channels to derive melanin and hemoglobin maps. A novel set of clinically inspired features and ratiometric measurements are then extracted from each map to characterize the vascular properties and blood content of the lesion. The feature set is then fed into a random forest classifier. Over a dataset of 664 skin lesions, the proposed method achieved an area under ROC curve of 0.832 in a 10-fold cross validation for differentiating basal cell carcinomas from benign lesions.

Size assessment of breast lesions by means of a computer-aided detection (CAD) system for magnetic resonance mammography.

PubMed

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.

Needs assessment for next generation computer-aided mammography reference image databases and evaluation studies.

PubMed

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.

Monitoring and decision making by people in man machine systems

NASA Technical Reports Server (NTRS)

Johannsen, G.

1979-01-01

The analysis of human monitoring and decision making behavior as well as its modeling are described. Classic and optimal control theoretical, monitoring models are surveyed. The relationship between attention allocation and eye movements is discussed. As an example of applications, the evaluation of predictor displays by means of the optimal control model is explained. Fault detection involving continuous signals and decision making behavior of a human operator engaged in fault diagnosis during different operation and maintenance situations are illustrated. Computer aided decision making is considered as a queueing problem. It is shown to what extent computer aids can be based on the state of human activity as measured by psychophysiological quantities. Finally, management information systems for different application areas are mentioned. The possibilities of mathematical modeling of human behavior in complex man machine systems are also critically assessed.

Computer Aided Diagnostic Support System for Skin Cancer: A Review of Techniques and Algorithms

PubMed Central

Masood, Ammara; Al-Jumaily, Adel Ali

2013-01-01

Image-based computer aided diagnosis systems have significant potential for screening and early detection of malignant melanoma. We review the state of the art in these systems and examine current practices, problems, and prospects of image acquisition, pre-processing, segmentation, feature extraction and selection, and classification of dermoscopic images. This paper reports statistics and results from the most important implementations reported to date. We compared the performance of several classifiers specifically developed for skin lesion diagnosis and discussed the corresponding findings. Whenever available, indication of various conditions that affect the technique's performance is reported. We suggest a framework for comparative assessment of skin cancer diagnostic models and review the results based on these models. The deficiencies in some of the existing studies are highlighted and suggestions for future research are provided. PMID:24575126

Colonic polyps: application value of computer-aided detection in computed tomographic colonography.

PubMed

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.

Integration of the Execution Support System for the Computer-Aided Prototyping System (CAPS)

DTIC Science & Technology

1990-09-01

SUPPORT SYSTEM FOR THE COMPUTER -AIDED PROTOTYPING SYSTEM (CAPS) by Frank V. Palazzo September 1990 Thesis Advisor: Luq± Approved for public release...ZATON REPOR ,,.VBE (, 6a NAME OF PERPORMING ORGAN ZAT7ON 6b OFF:CE SYVBOL 7a NAME OF MONITORINC O0-CA’Za- ON Computer Science Department (if applicable...Include Security Classification) Integration of the Execution Support System for the Computer -Aided Prototyping System (C S) 12 PERSONAL AUTHOR(S) Frank V

Computer-aided detection of renal calculi from noncontrast CT images using TV-flow and MSER features.

PubMed

Liu, Jianfei; Wang, Shijun; Turkbey, Evrim B; Linguraru, Marius George; Yao, Jianhua; Summers, Ronald M

2015-01-01

Renal calculi are common extracolonic incidental findings on computed tomographic colonography (CTC). This work aims to develop a fully automated computer-aided diagnosis system to accurately detect renal calculi on CTC images. The authors developed a total variation (TV) flow method to reduce image noise within the kidneys while maintaining the characteristic appearance of renal calculi. Maximally stable extremal region (MSER) features were then calculated to robustly identify calculi candidates. Finally, the authors computed texture and shape features that were imported to support vector machines for calculus classification. The method was validated on a dataset of 192 patients and compared to a baseline approach that detects calculi by thresholding. The authors also compared their method with the detection approaches using anisotropic diffusion and nonsmoothing. At a false positive rate of 8 per patient, the sensitivities of the new method and the baseline thresholding approach were 69% and 35% (p < 1e - 3) on all calculi from 1 to 433 mm(3) in the testing dataset. The sensitivities of the detection methods using anisotropic diffusion and nonsmoothing were 36% and 0%, respectively. The sensitivity of the new method increased to 90% if only larger and more clinically relevant calculi were considered. Experimental results demonstrated that TV-flow and MSER features are efficient means to robustly and accurately detect renal calculi on low-dose, high noise CTC images. Thus, the proposed method can potentially improve diagnosis.

Computer-aided detection of renal calculi from noncontrast CT images using TV-flow and MSER features

PubMed Central

Liu, Jianfei; Wang, Shijun; Turkbey, Evrim B.; Linguraru, Marius George; Yao, Jianhua; Summers, Ronald M.

2015-01-01

Purpose: Renal calculi are common extracolonic incidental findings on computed tomographic colonography (CTC). This work aims to develop a fully automated computer-aided diagnosis system to accurately detect renal calculi on CTC images. Methods: The authors developed a total variation (TV) flow method to reduce image noise within the kidneys while maintaining the characteristic appearance of renal calculi. Maximally stable extremal region (MSER) features were then calculated to robustly identify calculi candidates. Finally, the authors computed texture and shape features that were imported to support vector machines for calculus classification. The method was validated on a dataset of 192 patients and compared to a baseline approach that detects calculi by thresholding. The authors also compared their method with the detection approaches using anisotropic diffusion and nonsmoothing. Results: At a false positive rate of 8 per patient, the sensitivities of the new method and the baseline thresholding approach were 69% and 35% (p < 1e − 3) on all calculi from 1 to 433 mm3 in the testing dataset. The sensitivities of the detection methods using anisotropic diffusion and nonsmoothing were 36% and 0%, respectively. The sensitivity of the new method increased to 90% if only larger and more clinically relevant calculi were considered. Conclusions: Experimental results demonstrated that TV-flow and MSER features are efficient means to robustly and accurately detect renal calculi on low-dose, high noise CTC images. Thus, the proposed method can potentially improve diagnosis. PMID:25563255

Behavioral features recognition and oestrus detection based on fast approximate clustering algorithm in dairy cows

NASA Astrophysics Data System (ADS)

Tian, Fuyang; Cao, Dong; Dong, Xiaoning; Zhao, Xinqiang; Li, Fade; Wang, Zhonghua

2017-06-01

Behavioral features recognition was an important effect to detect oestrus and sickness in dairy herds and there is a need for heat detection aid. The detection method was based on the measure of the individual behavioural activity, standing time, and temperature of dairy using vibrational sensor and temperature sensor in this paper. The data of behavioural activity index, standing time, lying time and walking time were sent to computer by lower power consumption wireless communication system. The fast approximate K-means algorithm (FAKM) was proposed to deal the data of the sensor for behavioral features recognition. As a result of technical progress in monitoring cows using computers, automatic oestrus detection has become possible.

Computer-Aided Facilities Management Systems (CAFM).

ERIC Educational Resources Information Center

Cyros, Kreon L.

Computer-aided facilities management (CAFM) refers to a collection of software used with increasing frequency by facilities managers. The six major CAFM components are discussed with respect to their usefulness and popularity in facilities management applications: (1) computer-aided design; (2) computer-aided engineering; (3) decision support…

Exploration of available feature detection and identification systems and their performance on radiographs

NASA Astrophysics Data System (ADS)

Wantuch, Andrew C.; Vita, Joshua A.; Jimenez, Edward S.; Bray, Iliana E.

2016-10-01

Despite object detection, recognition, and identification being very active areas of computer vision research, many of the available tools to aid in these processes are designed with only photographs in mind. Although some algorithms used specifically for feature detection and identification may not take explicit advantage of the colors available in the image, they still under-perform on radiographs, which are grayscale images. We are especially interested in the robustness of these algorithms, specifically their performance on a preexisting database of X-ray radiographs in compressed JPEG form, with multiple ways of describing pixel information. We will review various aspects of the performance of available feature detection and identification systems, including MATLABs Computer Vision toolbox, VLFeat, and OpenCV on our non-ideal database. In the process, we will explore possible reasons for the algorithms' lessened ability to detect and identify features from the X-ray radiographs.

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).

Computer-aided diagnosis workstation and teleradiology network system for chest diagnosis using the web medical image conference system with a new information security solution

NASA Astrophysics Data System (ADS)

Satoh, Hitoshi; Niki, Noboru; Eguchi, Kenji; Ohmatsu, Hironobu; Kaneko, Masahiro; Kakinuma, Ryutaro; Moriyama, Noriyuki

2010-03-01

Diagnostic MDCT imaging requires a considerable number of images to be read. Moreover, the doctor who diagnoses a medical image is insufficient in Japan. Because of such a background, we have provided diagnostic assistance methods to medical screening specialists by developing a lung cancer screening algorithm that automatically detects suspected lung cancers in helical CT images, a coronary artery calcification screening algorithm that automatically detects suspected coronary artery calcification and a vertebra body analysis algorithm for quantitative evaluation of osteoporosis. We also have developed the teleradiology network system by using web medical image conference system. In the teleradiology network system, the security of information network is very important subjects. Our teleradiology network system can perform Web medical image conference in the medical institutions of a remote place using the web medical image conference system. We completed the basic proof experiment of the web medical image conference system with information security solution. We can share the screen of web medical image conference system from two or more web conference terminals at the same time. An opinion can be exchanged mutually by using a camera and a microphone that are connected with the workstation that builds in some diagnostic assistance methods. Biometric face authentication used on site of teleradiology makes "Encryption of file" and "Success in login" effective. Our Privacy and information security technology of information security solution ensures compliance with Japanese regulations. As a result, patients' private information is protected. Based on these diagnostic assistance methods, we have developed a new computer-aided workstation and a new teleradiology network that can display suspected lesions three-dimensionally in a short time. The results of this study indicate that our radiological information system without film by using computer-aided diagnosis workstation and our teleradiology network system can increase diagnostic speed, diagnostic accuracy and security improvement of medical information.

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.

Toward the detection of abnormal chest radiographs the way radiologists do it

NASA Astrophysics Data System (ADS)

Alzubaidi, Mohammad; Patel, Ameet; Panchanathan, Sethuraman; Black, John A., Jr.

2011-03-01

Computer Aided Detection (CADe) and Computer Aided Diagnosis (CADx) are relatively recent areas of research that attempt to employ feature extraction, pattern recognition, and machine learning algorithms to aid radiologists in detecting and diagnosing abnormalities in medical images. However, these computational methods are based on the assumption that there are distinct classes of abnormalities, and that each class has some distinguishing features that set it apart from other classes. However, abnormalities in chest radiographs tend to be very heterogeneous. The literature suggests that thoracic (chest) radiologists develop their ability to detect abnormalities by developing a sense of what is normal, so that anything that is abnormal attracts their attention. This paper discusses an approach to CADe that is based on a technique called anomaly detection (which aims to detect outliers in data sets) for the purpose of detecting atypical regions in chest radiographs. However, in order to apply anomaly detection to chest radiographs, it is necessary to develop a basis for extracting features from corresponding anatomical locations in different chest radiographs. This paper proposes a method for doing this, and describes how it can be used to support CADe.

Affective video retrieval: violence detection in Hollywood movies by large-scale segmental feature extraction.

PubMed

Eyben, Florian; Weninger, Felix; Lehment, Nicolas; Schuller, Björn; Rigoll, Gerhard

2013-01-01

Without doubt general video and sound, as found in large multimedia archives, carry emotional information. Thus, audio and video retrieval by certain emotional categories or dimensions could play a central role for tomorrow's intelligent systems, enabling search for movies with a particular mood, computer aided scene and sound design in order to elicit certain emotions in the audience, etc. Yet, the lion's share of research in affective computing is exclusively focusing on signals conveyed by humans, such as affective speech. Uniting the fields of multimedia retrieval and affective computing is believed to lend to a multiplicity of interesting retrieval applications, and at the same time to benefit affective computing research, by moving its methodology "out of the lab" to real-world, diverse data. In this contribution, we address the problem of finding "disturbing" scenes in movies, a scenario that is highly relevant for computer-aided parental guidance. We apply large-scale segmental feature extraction combined with audio-visual classification to the particular task of detecting violence. Our system performs fully data-driven analysis including automatic segmentation. We evaluate the system in terms of mean average precision (MAP) on the official data set of the MediaEval 2012 evaluation campaign's Affect Task, which consists of 18 original Hollywood movies, achieving up to .398 MAP on unseen test data in full realism. An in-depth analysis of the worth of individual features with respect to the target class and the system errors is carried out and reveals the importance of peak-related audio feature extraction and low-level histogram-based video analysis.

Affective Video Retrieval: Violence Detection in Hollywood Movies by Large-Scale Segmental Feature Extraction

PubMed Central

Eyben, Florian; Weninger, Felix; Lehment, Nicolas; Schuller, Björn; Rigoll, Gerhard

2013-01-01

Without doubt general video and sound, as found in large multimedia archives, carry emotional information. Thus, audio and video retrieval by certain emotional categories or dimensions could play a central role for tomorrow's intelligent systems, enabling search for movies with a particular mood, computer aided scene and sound design in order to elicit certain emotions in the audience, etc. Yet, the lion's share of research in affective computing is exclusively focusing on signals conveyed by humans, such as affective speech. Uniting the fields of multimedia retrieval and affective computing is believed to lend to a multiplicity of interesting retrieval applications, and at the same time to benefit affective computing research, by moving its methodology “out of the lab” to real-world, diverse data. In this contribution, we address the problem of finding “disturbing” scenes in movies, a scenario that is highly relevant for computer-aided parental guidance. We apply large-scale segmental feature extraction combined with audio-visual classification to the particular task of detecting violence. Our system performs fully data-driven analysis including automatic segmentation. We evaluate the system in terms of mean average precision (MAP) on the official data set of the MediaEval 2012 evaluation campaign's Affect Task, which consists of 18 original Hollywood movies, achieving up to .398 MAP on unseen test data in full realism. An in-depth analysis of the worth of individual features with respect to the target class and the system errors is carried out and reveals the importance of peak-related audio feature extraction and low-level histogram-based video analysis. PMID:24391704

Incorporating Colour Information for Computer-Aided Diagnosis of Melanoma from Dermoscopy Images: A Retrospective Survey and Critical Analysis

PubMed Central

Drew, Mark S.

2016-01-01

Cutaneous melanoma is the most life-threatening form of skin cancer. Although advanced melanoma is often considered as incurable, if detected and excised early, the prognosis is promising. Today, clinicians use computer vision in an increasing number of applications to aid early detection of melanoma through dermatological image analysis (dermoscopy images, in particular). Colour assessment is essential for the clinical diagnosis of skin cancers. Due to this diagnostic importance, many studies have either focused on or employed colour features as a constituent part of their skin lesion analysis systems. These studies range from using low-level colour features, such as simple statistical measures of colours occurring in the lesion, to availing themselves of high-level semantic features such as the presence of blue-white veil, globules, or colour variegation in the lesion. This paper provides a retrospective survey and critical analysis of contributions in this research direction. PMID:28096807

Using Unix system auditing for detecting network intrusions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Christensen, M.J.

1993-03-01

Intrusion Detection Systems (IDSs) are designed to detect actions of individuals who use computer resources without authorization as well as legitimate users who exceed their privileges. This paper describes a novel approach to IDS research, namely a decision aiding approach to intrusion detection. The introduction of a decision tree represents the logical steps necessary to distinguish and identify different types of attacks. This tool, the Intrusion Decision Aiding Tool (IDAT), utilizes IDS-based attack models and standard Unix audit data. Since attacks have certain characteristics and are based on already developed signature attack models, experienced and knowledgeable Unix system administrators knowmore » what to look for in system audit logs to determine if a system has been attacked. Others, however, are usually less able to recognize common signatures of unauthorized access. Users can traverse the tree using available audit data displayed by IDAT and general knowledge they possess to reach a conclusion regarding suspicious activity. IDAT is an easy-to-use window based application that gathers, analyzes, and displays pertinent system data according to Unix attack characteristics. IDAT offers a more practical approach and allows the user to make an informed decision regarding suspicious activity.« less

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)

Automatic rectum limit detection by anatomical markers correlation.

PubMed

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.

Optimization of Breast Tomosynthesis Imaging Systems for Computer-Aided Detection

DTIC Science & Technology

2011-05-01

R. Saunders, E. Samei, C. Badea, H. Yuan, K. Ghaghada, Y. Qi, L. Hedlund, and S. Mukundan, “Optimization of dual energy contrast enhanced breast...14 4 1 Introduction This is the final report for this body of research. Screen-film mammography and...digital mammography have been used for over 30 years in the early detection of cancer. The combination of screening and adjuvant therapies have led to

A comparison of detection efficiency on an air traffic control monitoring task with and without computer aiding.

DOT National Transportation Integrated Search

1989-01-01

Future levels of air traffic control automation plan to incorporate computer aiding features designed to alert the controller to upcoming problem situations by displaying information that will identify the situation and suggest possible solutions. Co...

Software For Computer-Aided Design Of Control Systems

NASA Technical Reports Server (NTRS)

Wette, Matthew

1994-01-01

Computer Aided Engineering System (CAESY) software developed to provide means to evaluate methods for dealing with users' needs in computer-aided design of control systems. Interpreter program for performing engineering calculations. Incorporates features of both Ada and MATLAB. Designed to be flexible and powerful. Includes internally defined functions, procedures and provides for definition of functions and procedures by user. Written in C language.

An interactive system for computer-aided diagnosis of breast masses.

PubMed

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.

Comparison of diagnosis of early retinal lesions of diabetic retinopathy between a computer system and human experts.

PubMed

Lee, S C; Lee, E T; Kingsley, R M; Wang, Y; Russell, D; Klein, R; Warn, A

2001-04-01

To investigate whether a computer vision system is comparable with humans in detecting early retinal lesions of diabetic retinopathy using color fundus photographs. A computer system has been developed using image processing and pattern recognition techniques to detect early lesions of diabetic retinopathy (hemorrhages and microaneurysms, hard exudates, and cotton-wool spots). Color fundus photographs obtained from American Indians in Oklahoma were used in developing and testing the system. A set of 369 color fundus slides were used to train the computer system using 3 diagnostic categories: lesions present, questionable, or absent (Y/Q/N). A different set of 428 slides were used to test and evaluate the system, and its diagnostic results were compared with those of 2 human experts-the grader at the University of Wisconsin Fundus Photograph Reading Center (Madison) and a general ophthalmologist. The experiments included comparisons using 3 (Y/Q/N) and 2 diagnostic categories (Y/N) (questionable cases excluded in the latter). In the training phase, the agreement rates, sensitivity, and specificity in detecting the 3 lesions between the retinal specialist and the computer system were all above 90%. The kappa statistics were high (0.75-0.97), indicating excellent agreement between the specialist and the computer system. In the testing phase, the results obtained between the computer system and human experts were consistent with those of the training phase, and they were comparable with those between the human experts. The performance of the computer vision system in diagnosing early retinal lesions was comparable with that of human experts. Therefore, this mobile, electronically easily accessible, and noninvasive computer system, could become a mass screening tool and a clinical aid in diagnosing early lesions of diabetic retinopathy.

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.

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.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Christoph, G.G; Jackson, K.A.; Neuman, M.C.

An effective method for detecting computer misuse is the automatic auditing and analysis of on-line user activity. This activity is reflected in the system audit record, by changes in the vulnerability posture of the system configuration, and in other evidence found through active testing of the system. In 1989 we started developing an automatic misuse detection system for the Integrated Computing Network (ICN) at Los Alamos National Laboratory. Since 1990 this system has been operational, monitoring a variety of network systems and services. We call it the Network Anomaly Detection and Intrusion Reporter, or NADIR. During the last year andmore » a half, we expanded NADIR to include processing of audit and activity records for the Cray UNICOS operating system. This new component is called the UNICOS Real-time NADIR, or UNICORN. UNICORN summarizes user activity and system configuration information in statistical profiles. In near real-time, it can compare current activity to historical profiles and test activity against expert rules that express our security policy and define improper or suspicious behavior. It reports suspicious behavior to security auditors and provides tools to aid in follow-up investigations. UNICORN is currently operational on four Crays in Los Alamos` main computing network, the ICN.« less

An intelligent advisory system for pre-launch processing

NASA Technical Reports Server (NTRS)

Engrand, Peter A.; Mitchell, Tami

1991-01-01

The shuttle system of interest in this paper is the shuttle's data processing system (DPS). The DPS is composed of the following: (1) general purpose computers (GPC); (2) a multifunction CRT display system (MCDS); (3) mass memory units (MMU); and (4) a multiplexer/demultiplexer (MDM) and related software. In order to ensure the correct functioning of shuttle systems, some level of automatic error detection has been incorporated into all shuttle systems. For the DPS, error detection equipment has been incorporated into all of its subsystems. The automated diagnostic system, (MCDS) diagnostic tool, that aids in a more efficient processing of the DPS is described.

Development and clinical application of a computer-aided real-time feedback system for detecting in-bed physical activities.

PubMed

Lu, Liang-Hsuan; Chiang, Shang-Lin; Wei, Shun-Hwa; Lin, Chueh-Ho; Sung, Wen-Hsu

2017-08-01

Being bedridden long-term can cause deterioration in patients' physiological function and performance, limiting daily activities and increasing the incidence of falls and other accidental injuries. Little research has been carried out in designing effective detecting systems to monitor the posture and status of bedridden patients and to provide accurate real-time feedback on posture. The purposes of this research were to develop a computer-aided system for real-time detection of physical activities in bed and to validate the system's validity and test-retest reliability in determining eight postures: motion leftward/rightward, turning over leftward/rightward, getting up leftward/rightward, and getting off the bed leftward/rightward. The in-bed physical activity detecting system consists mainly of a clinical sickbed, signal amplifier, a data acquisition (DAQ) system, and operating software for computing and determining postural changes associated with four load cell sensing components. Thirty healthy subjects (15 males and 15 females, mean age = 27.8 ± 5.3 years) participated in the study. All subjects were asked to execute eight in-bed activities in a random order and to participate in an evaluation of the test-retest reliability of the results 14 days later. Spearman's rank correlation coefficient was used to compare the system's determinations of postural states with researchers' recordings of postural changes. The test-retest reliability of the system's ability to determine postures was analyzed using the interclass correlation coefficient ICC(3,1). The system was found to exhibit high validity and accuracy (r = 0.928, p < 0.001; accuracy rate: 87.9%) in determining in-bed displacement, turning over, sitting up, and getting off the bed. The system was particularly accurate in detecting motion rightward (90%), turning over leftward (83%), sitting up leftward or rightward (87-93%), and getting off the bed (100%). The test-retest reliability ICC(3,1) value was 0.968 (p < 0.001). The system developed in this study exhibits satisfactory validity and reliability in detecting changes in-bed body postures and can be beneficial in assisting caregivers and clinical nursing staff in detecting the in-bed physical activities of bedridden patients and in developing fall prevention warning systems. Copyright © 2017 Elsevier B.V. All rights reserved.

Reducing false-positive detections by combining two stage-1 computer-aided mass detection algorithms

NASA Astrophysics Data System (ADS)

Bedard, Noah D.; Sampat, Mehul P.; Stokes, Patrick A.; Markey, Mia K.

2006-03-01

In this paper we present a strategy for reducing the number of false-positives in computer-aided mass detection. Our approach is to only mark "consensus" detections from among the suspicious sites identified by different "stage-1" detection algorithms. By "stage-1" we mean that each of the Computer-aided Detection (CADe) algorithms is designed to operate with high sensitivity, allowing for a large number of false positives. In this study, two mass detection methods were used: (1) Heath and Bowyer's algorithm based on the average fraction under the minimum filter (AFUM) and (2) a low-threshold bi-lateral subtraction algorithm. The two methods were applied separately to a set of images from the Digital Database for Screening Mammography (DDSM) to obtain paired sets of mass candidates. The consensus mass candidates for each image were identified by a logical "and" operation of the two CADe algorithms so as to eliminate regions of suspicion that were not independently identified by both techniques. It was shown that by combining the evidence from the AFUM filter method with that obtained from bi-lateral subtraction, the same sensitivity could be reached with fewer false-positives per image relative to using the AFUM filter alone.

[Clinical skills and outcomes of chair-side computer aided design and computer aided manufacture system].

PubMed

Yu, Q

2018-04-09

Computer aided design and computer aided manufacture (CAD/CAM) technology is a kind of oral digital system which is applied to clinical diagnosis and treatment. It overturns the traditional pattern, and provides a solution to restore defect tooth quickly and efficiently. In this paper we mainly discuss the clinical skills of chair-side CAD/CAM system, including tooth preparation, digital impression, the three-dimensional design of prosthesis, numerical control machining, clinical bonding and so on, and review the outcomes of several common kinds of materials at the same time.

Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning.

PubMed

Shin, Hoo-Chang; Roth, Holger R; Gao, Mingchen; Lu, Le; Xu, Ziyue; Nogues, Isabella; Yao, Jianhua; Mollura, Daniel; Summers, Ronald M

2016-05-01

Remarkable progress has been made in image recognition, primarily due to the availability of large-scale annotated datasets and deep convolutional neural networks (CNNs). CNNs enable learning data-driven, highly representative, hierarchical image features from sufficient training data. However, obtaining datasets as comprehensively annotated as ImageNet in the medical imaging domain remains a challenge. There are currently three major techniques that successfully employ CNNs to medical image classification: training the CNN from scratch, using off-the-shelf pre-trained CNN features, and conducting unsupervised CNN pre-training with supervised fine-tuning. Another effective method is transfer learning, i.e., fine-tuning CNN models pre-trained from natural image dataset to medical image tasks. In this paper, we exploit three important, but previously understudied factors of employing deep convolutional neural networks to computer-aided detection problems. We first explore and evaluate different CNN architectures. The studied models contain 5 thousand to 160 million parameters, and vary in numbers of layers. We then evaluate the influence of dataset scale and spatial image context on performance. Finally, we examine when and why transfer learning from pre-trained ImageNet (via fine-tuning) can be useful. We study two specific computer-aided detection (CADe) problems, namely thoraco-abdominal lymph node (LN) detection and interstitial lung disease (ILD) classification. We achieve the state-of-the-art performance on the mediastinal LN detection, and report the first five-fold cross-validation classification results on predicting axial CT slices with ILD categories. Our extensive empirical evaluation, CNN model analysis and valuable insights can be extended to the design of high performance CAD systems for other medical imaging tasks.

Computer-Aided Diagnosis in Medical Imaging: Historical Review, Current Status and Future Potential

PubMed Central

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

Contrast-enhanced ultrasonography for the detection of joint vascularity in arthritis--subjective grading versus computer-aided objective quantification.

PubMed

Klauser, A S; Franz, M; Bellmann Weiler, R; Gruber, J; Hartig, F; Mur, E; Wick, M C; Jaschke, W

2011-12-01

To compare joint inflammation assessment using subjective grading of power Doppler ultrasonography (PDUS) and contrast-enhanced ultrasonography (CEUS) versus computer-aided objective CEUS quantification. 37 joints of 28 patients with arthritis of different etiologies underwent B-mode ultrasonography, PDUS, and CEUS using a second-generation contrast agent. Synovial thickness, extent of vascularized pannus and intensity of vascularization were included in a 4-point PDUS and CEUS grading system. Subjective CEUS and PDUS scores were compared to computer-aided objective CEUS quantification using Qontrast® software for the calculation of the signal intensity (SI) and the ratio of SI for contrast enhancement. The interobserver agreement for subjective scoring was good to excellent (κ = 0.8 - 1.0; P < 0.0001). Computer-aided objective CEUS quantification correlated statistically significantly with subjective CEUS (P < 0.001) and PDUS grading (P < 0.05). The Qontrast® SI ratio correlated with subjective CEUS (P < 0.02) and PDUS grading (P < 0.03). Clinical activity did not correlate with vascularity or synovial thickening (P = N. S.) and no correlation between synovial thickening and vascularity extent could be found, neither using PDUS nor CEUS (P = N. S.). Both subjective CEUS grading and objective CEUS quantification are valuable for assessing joint vascularity in arthritis and computer-aided CEUS quantification may be a suitable objective tool for therapy follow-up in arthritis. © Georg Thieme Verlag KG Stuttgart · New York.

The electronic stethoscope.

PubMed

Leng, Shuang; Tan, Ru San; Chai, Kevin Tshun Chuan; Wang, Chao; Ghista, Dhanjoo; Zhong, Liang

2015-07-10

Most heart diseases are associated with and reflected by the sounds that the heart produces. Heart auscultation, defined as listening to the heart sound, has been a very important method for the early diagnosis of cardiac dysfunction. Traditional auscultation requires substantial clinical experience and good listening skills. The emergence of the electronic stethoscope has paved the way for a new field of computer-aided auscultation. This article provides an in-depth study of (1) the electronic stethoscope technology, and (2) the methodology for diagnosis of cardiac disorders based on computer-aided auscultation. The paper is based on a comprehensive review of (1) literature articles, (2) market (state-of-the-art) products, and (3) smartphone stethoscope apps. It covers in depth every key component of the computer-aided system with electronic stethoscope, from sensor design, front-end circuitry, denoising algorithm, heart sound segmentation, to the final machine learning techniques. Our intent is to provide an informative and illustrative presentation of the electronic stethoscope, which is valuable and beneficial to academics, researchers and engineers in the technical field, as well as to medical professionals to facilitate its use clinically. The paper provides the technological and medical basis for the development and commercialization of a real-time integrated heart sound detection, acquisition and quantification system.

Automated assessment of joint synovitis activity from medical ultrasound and power doppler examinations using image processing and machine learning methods.

PubMed

Cupek, Rafal; Ziębiński, Adam

2016-01-01

Rheumatoid arthritis is the most common rheumatic disease with arthritis, and causes substantial functional disability in approximately 50% patients after 10 years. Accurate measurement of the disease activity is crucial to provide an adequate treatment and care to the patients. The aim of this study is focused on a computer aided diagnostic system that supports an assessment of synovitis severity. This paper focus on a computer aided diagnostic system that was developed within joint Polish-Norwegian research project related to the automated assessment of the severity of synovitis. Semiquantitative ultrasound with power Doppler is a reliable and widely used method of assessing synovitis. Synovitis is estimated by ultrasound examiner using the scoring system graded from 0 to 3. Activity score is estimated on the basis of the examiner's experience or standardized ultrasound atlases. The method needs trained medical personnel and the result can be affected by a human error. The porotype of a computer-aided diagnostic system and algorithms essential for an analysis of ultrasonic images of finger joints are main scientific output of the MEDUSA project. Medusa Evaluation System prototype uses bone, skin, joint and synovitis area detectors for mutual structural model based evaluation of synovitis. Finally, several algorithms that support the semi-automatic or automatic detection of the bone region were prepared as well as a system that uses the statistical data processing approach in order to automatically localize the regions of interest. Semiquantitative ultrasound with power Doppler is a reliable and widely used method of assessing synovitis. Activity score is estimated on the basis of the examiner's experience and the result can be affected by a human error. In this paper we presented the MEDUSA project which is focused on a computer aided diagnostic system that supports an assessment of synovitis severity.

An adaptive incremental approach to constructing ensemble classifiers: application in an information-theoretic computer-aided decision system for detection of masses in mammograms.

PubMed

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.

Computer-aided decision support systems for endoscopy in the gastrointestinal tract: a review.

PubMed

Liedlgruber, Michael; Uhl, Andreas

2011-01-01

Today, medical endoscopy is a widely used procedure to inspect the inner cavities of the human body. The advent of endoscopic imaging techniques-allowing the acquisition of images or videos-created the possibility for the development of the whole new branch of computer-aided decision support systems. Such systems aim at helping physicians to identify possibly malignant abnormalities more accurately. At the beginning of this paper, we give a brief introduction to the history of endoscopy, followed by introducing the main types of endoscopes which emerged so far (flexible endoscope, wireless capsule endoscope, and confocal laser endomicroscope). We then give a brief introduction to computer-aided decision support systems specifically targeted at endoscopy in the gastrointestinal tract. Then we present general facts and figures concerning computer-aided decision support systems and summarize work specifically targeted at computer-aided decision support in the gastrointestinal tract. This summary is followed by a discussion of some common issues concerning the approaches reviewed and suggestions of possible ways to resolve them.

Machine learning techniques for breast cancer computer aided diagnosis using different image modalities: A systematic review.

PubMed

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.

Diagnosis and management of solitary pulmonary nodules.

PubMed

Jeong, Yeon Joo; Lee, Kyung Soo; Kwon, O Jung

2008-12-01

The advent of computed tomography (CT) screening with or without the help of computer-aided detection systems has increased the detection rate of solitary pulmonary nodules (SPNs), including that of early peripheral lung cancer. Helical dynamic (HD)CT, providing the information on morphologic and hemodynamic characteristics with high specificity and reasonably high accuracy, can be used for the initial assessment of SPNs. (18)F-fluorodeoxyglucose PET/CT is more sensitive at detecting malignancy than HDCT. Therefore, PET/CT may be selectively performed to characterize SPNs when HDCT gives an inconclusive diagnosis. Serial volume measurements are currently the most reliable methods for the tissue characterization of subcentimeter nodules. When malignant nodule is highly suspected for subcentimeter nodules, video-assisted thoracoscopic surgery nodule removal after nodule localization using the pulmonary nodule-marker system may be performed for diagnosis and treatment.

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.

Machine Learning in Ultrasound Computer-Aided Diagnostic Systems: A Survey

PubMed Central

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.

PubMed

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.

A Computer-Based, Interactive Videodisc Job Aid and Expert System for Electron Beam Lithography Integration and Diagnostic Procedures.

ERIC Educational Resources Information Center

Stevenson, Kimberly

This master's thesis describes the development of an expert system and interactive videodisc computer-based instructional job aid used for assisting in the integration of electron beam lithography devices. Comparable to all comprehensive training, expert system and job aid development require a criterion-referenced systems approach treatment to…

Explanation-aware computing of the prognosis for breast cancer supported by IK-DCBRC: Technical innovation.

PubMed

Khelassi, Abdeldjalil

2014-01-01

Active research is being conducted to determine the prognosis for breast cancer. However, the uncertainty is a major obstacle in this domain of medical research. In that context, explanation-aware computing has the potential for providing meaningful interactions between complex medical applications and users, which would ensure a significant reduction of uncertainty and risks. This paper presents an explanation-aware agent, supported by Intensive Knowledge-Distributed Case-Based Reasoning Classifier (IK-DCBRC), to reduce the uncertainty and risks associated with the diagnosis of breast cancer. A meaningful explanation is generated by inferring from a rule-based system according to the level of abstraction and the reasoning traces. The computer-aided detection is conducted by IK-DCBRC, which is a multi-agent system that applies the case-based reasoning paradigm and a fuzzy similarity function for the automatic prognosis by the class of breast tumors, i.e. malignant or benign, from a pattern of cytological images. A meaningful interaction between the physician and the computer-aided diagnosis system, IK-DCBRC, is achieved via an intelligent agent. The physician can observe the trace of reasoning, terms, justifications, and the strategy to be used to decrease the risks and doubts associated with the automatic diagnosis. The capability of the system we have developed was proven by an example in which conflicts were clarified and transparency was ensured. The explanation agent ensures the transparency of the automatic diagnosis of breast cancer supported by IK-DCBRC, which decreases uncertainty and risks and detects some conflicts.

Automated image-based colon cleansing for laxative-free CT colonography computer-aided polyp detection

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

Impact of various color LED flashlights and different lighting source to skin distances on the manual and the computer-aided detection of basal cell carcinoma borders.

PubMed

Bakht, Mohamadreza K; Pouladian, Majid; Mofrad, Farshid B; Honarpisheh, Hamid

2014-02-01

Quantitative analysis based on digital skin image has been proven to be helpful in dermatology. Moreover, the borders of the basal cell carcinoma (BCC) lesions have been challenging borders for the automatic detection methods. In this work, a computer-aided dermatoscopy system was proposed to enhance the clinical detection of BCC lesion borders. Fifty cases of BCC were selected and 2000 pictures were taken. The lesion images data were obtained with eight colors of flashlights and in five different lighting source to skin distances (SSDs). Then, the image-processing techniques were used for automatic detection of lesion borders. Further, the dermatologists marked the lesions on the obtained photos. Considerable differences between the obtained values referring to the photographs that were taken at super blue and aqua green color lighting were observed for most of the BCC borders. It was observed that by changing the SSD, an optimum distance could be found where that the accuracy of the detection reaches to a maximum value. This study clearly indicates that by changing SSD and lighting color, manual and automatic detection of BCC lesions borders can be enhanced. © 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

The ERTS-1 investigation (ER-600): A compendium of analysis results of the utility of ERTS-1 data for land resources management

NASA Technical Reports Server (NTRS)

Erb, R. B.

1974-01-01

The results of the ERTS-1 investigations conducted by the Earth Observations Division at the NASA Lyndon B. Johnson Space Center are summarized in this report, which is an overview of documents detailing individual investigations. Conventional image interpretation and computer-aided classification procedures were the two basic techniques used in analyzing the data for detecting, identifying, locating, and measuring surface features related to earth resources. Data from the ERTS-1 multispectral scanner system were useful for all applications studied, which included agriculture, coastal and estuarine analysis, forestry, range, land use and urban land use, and signature extension. Percentage classification accuracies are cited for the conventional and computer-aided techniques.

A survey on computer aided diagnosis for ocular diseases

PubMed Central

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

Computer-aided Instructional System for Transmission Line Simulation.

ERIC Educational Resources Information Center

Reinhard, Erwin A.; Roth, Charles H., Jr.

A computer-aided instructional system has been developed which utilizes dynamic computer-controlled graphic displays and which requires student interaction with a computer simulation in an instructional mode. A numerical scheme has been developed for digital simulation of a uniform, distortionless transmission line with resistive terminations and…

Computer-Aided Methodology for Syndromic Strabismus Diagnosis.

PubMed

Sousa de Almeida, João Dallyson; Silva, Aristófanes Corrêa; Teixeira, Jorge Antonio Meireles; Paiva, Anselmo Cardoso; Gattass, Marcelo

2015-08-01

Strabismus is a pathology that affects approximately 4 % of the population, causing aesthetic problems reversible at any age and irreversible sensory alterations that modify the vision mechanism. The Hirschberg test is one type of examination for detecting this pathology. Computer-aided detection/diagnosis is being used with relative success to aid health professionals. Nevertheless, the routine use of high-tech devices for aiding ophthalmological diagnosis and therapy is not a reality within the subspecialty of strabismus. Thus, this work presents a methodology to aid in diagnosis of syndromic strabismus through digital imaging. Two hundred images belonging to 40 patients previously diagnosed by an specialist were tested. The method was demonstrated to be 88 % accurate in esotropias identification (ET), 100 % for exotropias (XT), 80.33 % for hypertropias (HT), and 83.33 % for hypotropias (HoT). The overall average error was 5.6Δ and 3.83Δ for horizontal and vertical deviations, respectively, against the measures presented by the specialist.

Computer Instructional Aids for Undergraduate Control Education.

ERIC Educational Resources Information Center

Volz, Richard A.; And Others

Engineering is coming to rely more and more heavily upon the computer for computations, analyses, and graphic displays which aid the design process. A general purpose simulation system, the Time-shared Automatic Control Laboratory (TACL), and a set of computer-aided design programs, Control Oriented Interactive Graphic Analysis and Design…

A novel computer-aided detection system for pulmonary nodule identification in CT images

NASA Astrophysics Data System (ADS)

Han, Hao; Li, Lihong; Wang, Huafeng; Zhang, Hao; Moore, William; Liang, Zhengrong

2014-03-01

Computer-aided detection (CADe) of pulmonary nodules from computer tomography (CT) scans is critical for assisting radiologists to identify lung lesions at an early stage. In this paper, we propose a novel approach for CADe of lung nodules using a two-stage vector quantization (VQ) scheme. The first-stage VQ aims to extract lung from the chest volume, while the second-stage VQ is designed to extract initial nodule candidates (INCs) within the lung volume. Then rule-based expert filtering is employed to prune obvious FPs from INCs, and the commonly-used support vector machine (SVM) classifier is adopted to further reduce the FPs. The proposed system was validated on 100 CT scans randomly selected from the 262 scans that have at least one juxta-pleural nodule annotation in the publicly available database - Lung Image Database Consortium and Image Database Resource Initiative (LIDC-IDRI). The two-stage VQ only missed 2 out of the 207 nodules at agreement level 1, and the INCs detection for each scan took about 30 seconds in average. Expert filtering reduced FPs more than 18 times, while maintaining a sensitivity of 93.24%. As it is trivial to distinguish INCs attached to pleural wall versus not on wall, we investigated the feasibility of training different SVM classifiers to further reduce FPs from these two kinds of INCs. Experiment results indicated that SVM classification over the entire set of INCs was in favor of, where the optimal operating of our CADe system achieved a sensitivity of 89.4% at a specificity of 86.8%.

Vision-Aided Autonomous Landing and Ingress of Micro Aerial Vehicles

NASA Technical Reports Server (NTRS)

Brockers, Roland; Ma, Jeremy C.; Matthies, Larry H.; Bouffard, Patrick

2012-01-01

Micro aerial vehicles have limited sensor suites and computational power. For reconnaissance tasks and to conserve energy, these systems need the ability to autonomously land at vantage points or enter buildings (ingress). But for autonomous navigation, information is needed to identify and guide the vehicle to the target. Vision algorithms can provide egomotion estimation and target detection using input from cameras that are easy to include in miniature systems.

Modeling resident error-making patterns in detection of mammographic masses using computer-extracted image features: preliminary experiments

NASA Astrophysics Data System (ADS)

Mazurowski, Maciej A.; Zhang, Jing; Lo, Joseph Y.; Kuzmiak, Cherie M.; Ghate, Sujata V.; Yoon, Sora

2014-03-01

Providing high quality mammography education to radiology trainees is essential, as good interpretation skills potentially ensure the highest benefit of screening mammography for patients. We have previously proposed a computer-aided education system that utilizes trainee models, which relate human-assessed image characteristics to interpretation error. We proposed that these models be used to identify the most difficult and therefore the most educationally useful cases for each trainee. In this study, as a next step in our research, we propose to build trainee models that utilize features that are automatically extracted from images using computer vision algorithms. To predict error, we used a logistic regression which accepts imaging features as input and returns error as output. Reader data from 3 experts and 3 trainees were used. Receiver operating characteristic analysis was applied to evaluate the proposed trainee models. Our experiments showed that, for three trainees, our models were able to predict error better than chance. This is an important step in the development of adaptive computer-aided education systems since computer-extracted features will allow for faster and more extensive search of imaging databases in order to identify the most educationally beneficial cases.

Nodule Detection in a Lung Region that's Segmented with Using Genetic Cellular Neural Networks and 3D Template Matching with Fuzzy Rule Based Thresholding

PubMed Central

Osman, Onur; Ucan, Osman N.

2008-01-01

Objective The purpose of this study was to develop a new method for automated lung nodule detection in serial section CT images with using the characteristics of the 3D appearance of the nodules that distinguish themselves from the vessels. Materials and Methods Lung nodules were detected in four steps. First, to reduce the number of region of interests (ROIs) and the computation time, the lung regions of the CTs were segmented using Genetic Cellular Neural Networks (G-CNN). Then, for each lung region, ROIs were specified with using the 8 directional search; +1 or -1 values were assigned to each voxel. The 3D ROI image was obtained by combining all the 2-Dimensional (2D) ROI images. A 3D template was created to find the nodule-like structures on the 3D ROI image. Convolution of the 3D ROI image with the proposed template strengthens the shapes that are similar to those of the template and it weakens the other ones. Finally, fuzzy rule based thresholding was applied and the ROI's were found. To test the system's efficiency, we used 16 cases with a total of 425 slices, which were taken from the Lung Image Database Consortium (LIDC) dataset. Results The computer aided diagnosis (CAD) system achieved 100% sensitivity with 13.375 FPs per case when the nodule thickness was greater than or equal to 5.625 mm. Conclusion Our results indicate that the detection performance of our algorithm is satisfactory, and this may well improve the performance of computer-aided detection of lung nodules. PMID:18253070

Development of a computer-aided detection system for lung cancer diagnosis

NASA Astrophysics Data System (ADS)

Suzuki, Hideo; Inaoka, Noriko; Takabatake, Hirotsugu; Mori, Masaki; Sasaoka, Soichi; Natori, Hiroshi; Suzuki, Akira

1992-06-01

This paper describes a modified system for automatic detection of lung nodules by means of chest x ray image processing techniques. The objective of the system is to help radiologists to improve their accuracy in cancer detection. It is known from retrospective studies of chest x- ray images that radiologists fail to detect about 30 percent of lung cancer cases. A computerized method for detecting lung nodules would be very useful for decreasing the proportion of such oversights. Our proposed system consists of five sub-systems, for image input, lung region determination, nodule detection, rule-based false-positive elimination, and statistical false-positive elimination. In an experiment with the modified system, using 30 lung cancer cases and 78 normal control cases, we obtained figures of 73.3 percent and 89.7 percent for the sensitivity and specificity of the system, respectively. The system has been developed to run on the IBM* PS/55* and IBM RISC System/6000* (RS/6000), and we give the processing time for each platform.

Neural networks for computer-aided diagnosis: detection of lung nodules in chest radiograms.

PubMed

Coppini, Giuseppe; Diciotti, Stefano; Falchini, Massimo; Villari, Natale; Valli, Guido

2003-12-01

The paper describes a neural-network-based system for the computer aided detection of lung nodules in chest radiograms. Our approach is based on multiscale processing and artificial neural networks (ANNs). The problem of nodule detection is faced by using a two-stage architecture including: 1) an attention focusing subsystem that processes whole radiographs to locate possible nodular regions ensuring high sensitivity; 2) a validation subsystem that processes regions of interest to evaluate the likelihood of the presence of a nodule, so as to reduce false alarms and increase detection specificity. Biologically inspired filters (both LoG and Gabor kernels) are used to enhance salient image features. ANNs of the feedforward type are employed, which allow an efficient use of a priori knowledge about the shape of nodules, and the background structure. The images from the public JSRT database, including 247 radiograms, were used to build and test the system. We performed a further test by using a second private database with 65 radiograms collected and annotated at the Radiology Department of the University of Florence. Both data sets include nodule and nonnodule radiographs. The use of a public data set along with independent testing with a different image set makes the comparison with other systems easier and allows a deeper understanding of system behavior. Experimental results are described by ROC/FROC analysis. For the JSRT database, we observed that by varying sensitivity from 60 to 75% the number of false alarms per image lies in the range 4-10, while accuracy is in the range 95.7-98.0%. When the second data set was used comparable results were obtained. The observed system performances support the undertaking of system validation in clinical settings.

Mammogram segmentation using maximal cell strength updation in cellular automata.

PubMed

Anitha, J; Peter, J Dinesh

2015-08-01

Breast cancer is the most frequently diagnosed type of cancer among women. Mammogram is one of the most effective tools for early detection of the breast cancer. Various computer-aided systems have been introduced to detect the breast cancer from mammogram images. In a computer-aided diagnosis system, detection and segmentation of breast masses from the background tissues is an important issue. In this paper, an automatic segmentation method is proposed to identify and segment the suspicious mass regions of mammogram using a modified transition rule named maximal cell strength updation in cellular automata (CA). In coarse-level segmentation, the proposed method performs an adaptive global thresholding based on the histogram peak analysis to obtain the rough region of interest. An automatic seed point selection is proposed using gray-level co-occurrence matrix-based sum average feature in the coarse segmented image. Finally, the method utilizes CA with the identified initial seed point and the modified transition rule to segment the mass region. The proposed approach is evaluated over the dataset of 70 mammograms with mass from mini-MIAS database. Experimental results show that the proposed approach yields promising results to segment the mass region in the mammograms with the sensitivity of 92.25% and accuracy of 93.48%.

Study of gamma detection capabilities of the REWARD mobile spectroscopic system

NASA Astrophysics Data System (ADS)

Balbuena, J. P.; Baptista, M.; Barros, S.; Dambacher, M.; Disch, C.; Fiederle, M.; Kuehn, S.; Parzefall, U.

2017-07-01

REWARD is a novel mobile spectroscopic radiation detector system for Homeland Security applications. The system integrates gamma and neutron detection equipped with wireless communication. A comprehensive simulation study on its gamma detection capabilities in different radioactive scenarios is presented in this work. The gamma detection unit consists of a precise energy resolution system based on two stacked (Cd,Zn)Te sensors working in coincidence sum mode. The volume of each of these CZT sensors is 1 cm3. The investigated energy windows used to determine the detection capabilities of the detector correspond to the gamma emissions from 137Cs and 60Co radioactive sources (662 keV and 1173/1333 keV respectively). Monte Carlo and Technology Computer-Aided Design (TCAD) simulations are combined to determine its sensing capabilities for different radiation sources and estimate the limits of detection of the sensing unit as a function of source activity for several shielding materials.

Progressive data transmission for anatomical landmark detection in a cloud.

PubMed

Sofka, M; Ralovich, K; Zhang, J; Zhou, S K; Comaniciu, D

2012-01-01

In the concept of cloud-computing-based systems, various authorized users have secure access to patient records from a number of care delivery organizations from any location. This creates a growing need for remote visualization, advanced image processing, state-of-the-art image analysis, and computer aided diagnosis. This paper proposes a system of algorithms for automatic detection of anatomical landmarks in 3D volumes in the cloud computing environment. The system addresses the inherent problem of limited bandwidth between a (thin) client, data center, and data analysis server. The problem of limited bandwidth is solved by a hierarchical sequential detection algorithm that obtains data by progressively transmitting only image regions required for processing. The client sends a request to detect a set of landmarks for region visualization or further analysis. The algorithm running on the data analysis server obtains a coarse level image from the data center and generates landmark location candidates. The candidates are then used to obtain image neighborhood regions at a finer resolution level for further detection. This way, the landmark locations are hierarchically and sequentially detected and refined. Only image regions surrounding landmark location candidates need to be trans- mitted during detection. Furthermore, the image regions are lossy compressed with JPEG 2000. Together, these properties amount to at least 30 times bandwidth reduction while achieving similar accuracy when compared to an algorithm using the original data. The hierarchical sequential algorithm with progressive data transmission considerably reduces bandwidth requirements in cloud-based detection systems.

Application of local binary pattern and human visual Fibonacci texture features for classification different medical images

NASA Astrophysics Data System (ADS)

Sanghavi, Foram; Agaian, Sos

2017-05-01

The goal of this paper is to (a) test the nuclei based Computer Aided Cancer Detection system using Human Visual based system on the histopathology images and (b) Compare the results of the proposed system with the Local Binary Pattern and modified Fibonacci -p pattern systems. The system performance is evaluated using different parameters such as accuracy, specificity, sensitivity, positive predictive value, and negative predictive value on 251 prostate histopathology images. The accuracy of 96.69% was observed for cancer detection using the proposed human visual based system compared to 87.42% and 94.70% observed for Local Binary patterns and the modified Fibonacci p patterns.

Traffic Monitor

NASA Technical Reports Server (NTRS)

1992-01-01

Mestech's X-15 "Eye in the Sky," a traffic monitoring system, incorporates NASA imaging and robotic vision technology. A camera or "sensor box" is mounted in a housing. The sensor detects vehicles approaching an intersection and sends the information to a computer, which controls the traffic light according to the traffic rate. Jet Propulsion Laboratory technical support packages aided in the company's development of the system. The X-15's "smart highway" can also be used to count vehicles on a highway and compute the number in each lane and their speeds, important information for freeway control engineers. Additional applications are in airport and railroad operations. The system is intended to replace loop-type traffic detectors.

Possible Computer Vision Systems and Automated or Computer-Aided Edging and Trimming

Treesearch

Philip A. Araman

1990-01-01

This paper discusses research which is underway to help our industry reduce costs, increase product volume and value recovery, and market more accurately graded and described products. The research is part of a team effort to help the hardwood sawmill industry automate with computer vision systems, and computer-aided or computer controlled processing. This paper...

Hearing aid malfunction detection system

NASA Technical Reports Server (NTRS)

Kessinger, R. L. (Inventor)

1977-01-01

A malfunction detection system for detecting malfunctions in electrical signal processing circuits is disclosed. Malfunctions of a hearing aid in the form of frequency distortion and/or inadequate amplification by the hearing aid amplifier, as well as weakening of the hearing aid power supply are detectable. A test signal is generated and a timed switching circuit periodically applies the test signal to the input of the hearing aid amplifier in place of the input signal from the microphone. The resulting amplifier output is compared with the input test signal used as a reference signal. The hearing aid battery voltage is also periodically compared to a reference voltage. Deviations from the references beyond preset limits cause a warning system to operate.

Computer-aided diagnosis workstation and network system for chest diagnosis based on multislice CT images

NASA Astrophysics Data System (ADS)

Satoh, Hitoshi; Niki, Noboru; Mori, Kiyoshi; Eguchi, Kenji; Kaneko, Masahiro; Kakinuma, Ryutarou; Moriyama, Noriyuki; Ohmatsu, Hironobu; Masuda, Hideo; Machida, Suguru

2007-03-01

Multislice CT scanner advanced remarkably at the speed at which the chest CT images were acquired for mass screening. Mass screening based on multislice CT images requires a considerable number of images to be read. It is this time-consuming step that makes the use of helical CT for mass screening impractical at present. To overcome this problem, we have provided diagnostic assistance methods to medical screening specialists by developing a lung cancer screening algorithm that automatically detects suspected lung cancers in helical CT images and a coronary artery calcification screening algorithm that automatically detects suspected coronary artery calcification. Moreover, we have provided diagnostic assistance methods to medical screening specialists by using a lung cancer screening algorithm built into mobile helical CT scanner for the lung cancer mass screening done in the region without the hospital. We also have developed electronic medical recording system and prototype internet system for the community health in two or more regions by using the Virtual Private Network router and Biometric fingerprint authentication system and Biometric face authentication system for safety of medical information. Based on these diagnostic assistance methods, we have now developed a new computer-aided workstation and database that can display suspected lesions three-dimensionally in a short time. This paper describes basic studies that have been conducted to evaluate this new system.

Computer Aided Design: Instructional Manual. The North Dakota High Technology Mobile Laboratory Project.

ERIC Educational Resources Information Center

Cheng, Wan-Lee

This instructional manual contains 12 learning activity packets for use in a workshop in computer-aided design and drafting (CADD). The lessons cover the following topics: introduction to computer graphics and computer-aided design/drafting; coordinate systems; advance space graphics hardware configuration and basic features of the IBM PC…

Computer-aided detection in musculoskeletal projection radiography: A systematic review.

PubMed

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.

Development of a computer aided diagnosis model for prostate cancer classification on multi-parametric MRI

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.

Computer-Aided Reliability Estimation

NASA Technical Reports Server (NTRS)

Bavuso, S. J.; Stiffler, J. J.; Bryant, L. A.; Petersen, P. L.

1986-01-01

CARE III (Computer-Aided Reliability Estimation, Third Generation) helps estimate reliability of complex, redundant, fault-tolerant systems. Program specifically designed for evaluation of fault-tolerant avionics systems. However, CARE III general enough for use in evaluation of other systems as well.

Computer-aided assessment of pulmonary disease in novel swine-origin H1N1 influenza on CT

NASA Astrophysics Data System (ADS)

Yao, Jianhua; Dwyer, Andrew J.; Summers, Ronald M.; Mollura, Daniel J.

2011-03-01

The 2009 pandemic is a global outbreak of novel H1N1 influenza. Radiologic images can be used to assess the presence and severity of pulmonary infection. We develop a computer-aided assessment system to analyze the CT images from Swine-Origin Influenza A virus (S-OIV) novel H1N1 cases. The technique is based on the analysis of lung texture patterns and classification using a support vector machine (SVM). Pixel-wise tissue classification is computed from the SVM value. The method was validated on four H1N1 cases and ten normal cases. We demonstrated that the technique can detect regions of pulmonary abnormality in novel H1N1 patients and differentiate these regions from visually normal lung (area under the ROC curve is 0.993). This technique can also be applied to differentiate regions infected by different pulmonary diseases.

Deep learning of contrast-coated serrated polyps for computer-aided detection in CT colonography

NASA Astrophysics Data System (ADS)

Näppi, Janne J.; Pickhardt, Perry; Kim, David H.; Hironaka, Toru; Yoshida, Hiroyuki

2017-03-01

Serrated polyps were previously believed to be benign lesions with no cancer potential. However, recent studies have revealed a novel molecular pathway where also serrated polyps can develop into colorectal cancer. CT colonography (CTC) can detect serrated polyps using the radiomic biomarker of contrast coating, but this requires expertise from the reader and current computer-aided detection (CADe) systems have not been designed to detect the contrast coating. The purpose of this study was to develop a novel CADe method that makes use of deep learning to detect serrated polyps based on their contrast-coating biomarker in CTC. In the method, volumetric shape-based features are used to detect polyp sites over soft-tissue and fecal-tagging surfaces of the colon. The detected sites are imaged using multi-angular 2D image patches. A deep convolutional neural network (DCNN) is used to review the image patches for the presence of polyps. The DCNN-based polyp-likelihood estimates are merged into an aggregate likelihood index where highest values indicate the presence of a polyp. For pilot evaluation, the proposed DCNN-CADe method was evaluated with a 10-fold cross-validation scheme using 101 colonoscopy-confirmed cases with 144 biopsy-confirmed serrated polyps from a CTC screening program, where the patients had been prepared for CTC with saline laxative and fecal tagging by barium and iodine-based diatrizoate. The average per-polyp sensitivity for serrated polyps >=6 mm in size was 93+/-7% at 0:8+/-1:8 false positives per patient on average. The detection accuracy was substantially higher that of a conventional CADe system. Our results indicate that serrated polyps can be detected automatically at high accuracy in CTC.

Mixed spine metastasis detection through positron emission tomography/computed tomography synthesis and multiclassifier

PubMed Central

Yao, Jianhua; Burns, Joseph E.; Sanoria, Vic; Summers, Ronald M.

2017-01-01

Abstract. Bone metastases are a frequent occurrence with cancer, and early detection can guide the patient’s treatment regimen. Metastatic bone disease can present in density extremes as sclerotic (high density) and lytic (low density) or in a continuum with an admixture of both sclerotic and lytic components. We design a framework to detect and characterize the varying spectrum of presentation of spine metastasis on positron emission tomography/computed tomography (PET/CT) data. A technique is proposed to synthesize CT and PET images to enhance the lesion appearance for computer detection. A combination of watershed, graph cut, and level set algorithms is first run to obtain the initial detections. Detections are then sent to multiple classifiers for sclerotic, lytic, and mixed lesions. The system was tested on 44 cases with 225 sclerotic, 139 lytic, and 92 mixed lesions. The results showed that sensitivity (false positive per patient) was 0.81 (2.1), 0.81 (1.3), and 0.76 (2.1) for sclerotic, lytic, and mixed lesions, respectively. It also demonstrates that using PET/CT data significantly improves the computer aided detection performance over using CT alone. PMID:28612036

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% .

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.

A Review of Developments in Computer-Based Systems to Image Teeth and Produce Dental Restorations

PubMed Central

Rekow, E. Dianne; Erdman, Arthur G.; Speidel, T. Michael

1987-01-01

Computer-aided design and manufacturing (CAD/CAM) make it possible to automate the creation of dental restorations. Currently practiced techniques are described. Three automated systems currently under development are described and compared. Advances in computer-aided design and computer-aided manufacturing (CAD/CAM) provide a new option for dentistry, creating an alternative technique for producing dental restorations. It is possible to create dental restorations that are automatically produced and meet or exceed current requirements for fit and occlusion.

Evaluation of MTANNs for eliminating false-positive with different computer aided pulmonary nodules detection software.

PubMed

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.

Classification of Computer-Aided Design-Computer-Aided Manufacturing Applications for the Reconstruction of Cranio-Maxillo-Facial Defects.

PubMed

Wauters, Lauri D J; Miguel-Moragas, Joan San; Mommaerts, Maurice Y

2015-11-01

To gain insight into the methodology of different computer-aided design-computer-aided manufacturing (CAD-CAM) applications for the reconstruction of cranio-maxillo-facial (CMF) defects. We reviewed and analyzed the available literature pertaining to CAD-CAM for use in CMF reconstruction. We proposed a classification system of the techniques of implant and cutting, drilling, and/or guiding template design and manufacturing. The system consisted of 4 classes (I-IV). These classes combine techniques used for both the implant and template to most accurately describe the methodology used. Our classification system can be widely applied. It should facilitate communication and immediate understanding of the methodology of CAD-CAM applications for the reconstruction of CMF defects.

Computer-Aided Characterization and Diagnosis of Diffuse Liver Diseases Based on Ultrasound Imaging: A Review.

PubMed

Bharti, Puja; Mittal, Deepti; Ananthasivan, Rupa

2016-04-19

Diffuse liver diseases, such as hepatitis, fatty liver, and cirrhosis, are becoming a leading cause of fatality and disability all over the world. Early detection and diagnosis of these diseases is extremely important to save lives and improve effectiveness of treatment. Ultrasound imaging, a noninvasive diagnostic technique, is the most commonly used modality for examining liver abnormalities. However, the accuracy of ultrasound-based diagnosis depends highly on expertise of radiologists. Computer-aided diagnosis systems based on ultrasound imaging assist in fast diagnosis, provide a reliable "second opinion" for experts, and act as an effective tool to measure response of treatment on patients undergoing clinical trials. In this review, we first describe appearance of liver abnormalities in ultrasound images and state the practical issues encountered in characterization of diffuse liver diseases that can be addressed by software algorithms. We then discuss computer-aided diagnosis in general with features and classifiers relevant to diffuse liver diseases. In later sections of this paper, we review the published studies and describe the key findings of those studies. A concise tabular summary comparing image database, features extraction, feature selection, and classification algorithms presented in the published studies is also exhibited. Finally, we conclude with a summary of key findings and directions for further improvements in the areas of accuracy and objectiveness of computer-aided diagnosis. © The Author(s) 2016.

Hearing Impairments. Tech Use Guide: Using Computer Technology.

ERIC Educational Resources Information Center

Council for Exceptional Children, Reston, VA. Center for Special Education Technology.

One of nine brief guides for special educators on using computer technology, this guide focuses on advances in electronic aids, computers, telecommunications, and videodiscs to assist students with hearing impairments. Electronic aids include hearing aids, telephone devices for the deaf, teletypes, closed captioning systems for television, and…

Investigation of optimal use of computer-aided detection systems: the role of the "machine" in decision making process.

PubMed

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.

Computer-aided design and computer science technology

NASA Technical Reports Server (NTRS)

Fulton, R. E.; Voigt, S. J.

1976-01-01

A description is presented of computer-aided design requirements and the resulting computer science advances needed to support aerospace design. The aerospace design environment is examined, taking into account problems of data handling and aspects of computer hardware and software. The interactive terminal is normally the primary interface between the computer system and the engineering designer. Attention is given to user aids, interactive design, interactive computations, the characteristics of design information, data management requirements, hardware advancements, and computer science developments.

Digital receiver study and implementation

NASA Technical Reports Server (NTRS)

Fogle, D. A.; Lee, G. M.; Massey, J. C.

1972-01-01

Computer software was developed which makes it possible to use any general purpose computer with A/D conversion capability as a PSK receiver for low data rate telemetry processing. Carrier tracking, bit synchronization, and matched filter detection are all performed digitally. To aid in the implementation of optimum computer processors, a study of general digital processing techniques was performed which emphasized various techniques for digitizing general analog systems. In particular, the phase-locked loop was extensively analyzed as a typical non-linear communication element. Bayesian estimation techniques for PSK demodulation were studied. A hardware implementation of the digital Costas loop was developed.

Automated high-grade prostate cancer detection and ranking on whole slide images

NASA Astrophysics Data System (ADS)

Huang, Chao-Hui; Racoceanu, Daniel

2017-03-01

Recently, digital pathology (DP) has been largely improved due to the development of computer vision and machine learning. Automated detection of high-grade prostate carcinoma (HG-PCa) is an impactful medical use-case showing the paradigm of collaboration between DP and computer science: given a field of view (FOV) from a whole slide image (WSI), the computer-aided system is able to determine the grade by classifying the FOV. Various approaches have been reported based on this approach. However, there are two reasons supporting us to conduct this work: first, there is still room for improvement in terms of detection accuracy of HG-PCa; second, a clinical practice is more complex than the operation of simple image classification. FOV ranking is also an essential step. E.g., in clinical practice, a pathologist usually evaluates a case based on a few FOVs from the given WSI. Then, makes decision based on the most severe FOV. This important ranking scenario is not yet being well discussed. In this work, we introduce an automated detection and ranking system for PCa based on Gleason pattern discrimination. Our experiments suggested that the proposed system is able to perform high-accuracy detection ( 95:57% +/- 2:1%) and excellent performance of ranking. Hence, the proposed system has a great potential to support the daily tasks in the medical routine of clinical pathology.

Pulmonary lobar volumetry using novel volumetric computer-aided diagnosis and computed tomography

PubMed Central

Iwano, Shingo; Kitano, Mariko; Matsuo, Keiji; Kawakami, Kenichi; Koike, Wataru; Kishimoto, Mariko; Inoue, Tsutomu; Li, Yuanzhong; Naganawa, Shinji

2013-01-01

OBJECTIVES To compare the accuracy of pulmonary lobar volumetry using the conventional number of segments method and novel volumetric computer-aided diagnosis using 3D computed tomography images. METHODS We acquired 50 consecutive preoperative 3D computed tomography examinations for lung tumours reconstructed at 1-mm slice thicknesses. We calculated the lobar volume and the emphysematous lobar volume < −950 HU of each lobe using (i) the slice-by-slice method (reference standard), (ii) number of segments method, and (iii) semi-automatic and (iv) automatic computer-aided diagnosis. We determined Pearson correlation coefficients between the reference standard and the three other methods for lobar volumes and emphysematous lobar volumes. We also compared the relative errors among the three measurement methods. RESULTS Both semi-automatic and automatic computer-aided diagnosis results were more strongly correlated with the reference standard than the number of segments method. The correlation coefficients for automatic computer-aided diagnosis were slightly lower than those for semi-automatic computer-aided diagnosis because there was one outlier among 50 cases (2%) in the right upper lobe and two outliers among 50 cases (4%) in the other lobes. The number of segments method relative error was significantly greater than those for semi-automatic and automatic computer-aided diagnosis (P < 0.001). The computational time for automatic computer-aided diagnosis was 1/2 to 2/3 than that of semi-automatic computer-aided diagnosis. CONCLUSIONS A novel lobar volumetry computer-aided diagnosis system could more precisely measure lobar volumes than the conventional number of segments method. Because semi-automatic computer-aided diagnosis and automatic computer-aided diagnosis were complementary, in clinical use, it would be more practical to first measure volumes by automatic computer-aided diagnosis, and then use semi-automatic measurements if automatic computer-aided diagnosis failed. PMID:23526418

An adaptive incremental approach to constructing ensemble classifiers: Application in an information-theoretic computer-aided decision system for detection of masses in mammograms

PubMed Central

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

[Accuracy of computer aided measurement for detecting dental proximal caries lesions in images of cone-beam computed tomography].

PubMed

Zhang, Z L; Li, J P; Li, G; Ma, X C

2017-02-09

Objective: To establish and validate a computer program used to aid the detection of dental proximal caries in the images cone beam computed tomography (CBCT) images. Methods: According to the characteristics of caries lesions in X-ray images, a computer aided detection program for proximal caries was established with Matlab and Visual C++. The whole process for caries lesion detection included image import and preprocessing, measuring average gray value of air area, choosing region of interest and calculating gray value, defining the caries areas. The program was used to examine 90 proximal surfaces from 45 extracted human teeth collected from Peking University School and Hospital of Stomatology. The teeth were then scanned with a CBCT scanner (Promax 3D). The proximal surfaces of the teeth were respectively detected by caries detection program and scored by human observer for the extent of lesions with 6-level-scale. With histologic examination serving as the reference standard, the caries detection program and the human observer performances were assessed with receiver operating characteristic (ROC) curves. Student t -test was used to analyze the areas under the ROC curves (AUC) for the differences between caries detection program and human observer. Spearman correlation coefficient was used to analyze the detection accuracy of caries depth. Results: For the diagnosis of proximal caries in CBCT images, the AUC values of human observers and caries detection program were 0.632 and 0.703, respectively. There was a statistically significant difference between the AUC values ( P= 0.023). The correlation between program performance and gold standard (correlation coefficient r (s)=0.525) was higher than that of observer performance and gold standard ( r (s)=0.457) and there was a statistically significant difference between the correlation coefficients ( P= 0.000). Conclusions: The program that automatically detects dental proximal caries lesions could improve the diagnostic value of CBCT images.

Optimizing computer-aided colonic polyp detection for CT colonography by evolving the Pareto front1

PubMed Central

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

Wavelet method for CT colonography computer-aided polyp detection.

PubMed

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.

A Review. A Real-Time Microcomputer-Assisted System for Translating Aural, Monophonic Tones into Music Notation as an Aid in Sight-Singing.

ERIC Educational Resources Information Center

Higgins, William R.

1987-01-01

Reviews a dissertation in which the problems of real-time pitch detection by computer were studied in an attempt to develop a learning tool for sightsinging students. Specialized hardware and software were developed to discriminate aural pitches and to display them in real-time using standard notation. (BSR)

Computer-aided diagnosis of cavernous malformations in brain MR images.

PubMed

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.

Software Tools for Shipbuilding Productivity

DTIC Science & Technology

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

Low-Cost Computer-Aided Instruction/Computer-Managed Instruction (CAI/CMI) System: Feasibility Study. Final Report.

ERIC Educational Resources Information Center

Lintz, Larry M.; And Others

This study investigated the feasibility of a low cost computer-aided instruction/computer-managed instruction (CAI/CMI) system. Air Force instructors and training supervisors were surveyed to determine the potential payoffs of various CAI and CMI functions. Results indicated that a wide range of capabilities had potential for resident technical…

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.

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.

Comparative performance analysis for computer aided lung nodule detection and segmentation on ultra-low-dose vs. standard-dose CT

NASA Astrophysics Data System (ADS)

Wiemker, Rafael; Rogalla, Patrik; Opfer, Roland; Ekin, Ahmet; Romano, Valentina; Bülow, Thomas

2006-03-01

The performance of computer aided lung nodule detection (CAD) and computer aided nodule volumetry is compared between standard-dose (70-100 mAs) and ultra-low-dose CT images (5-10 mAs). A direct quantitative performance comparison was possible, since for each patient both an ultra-low-dose and a standard-dose CT scan were acquired within the same examination session. The data sets were recorded with a multi-slice CT scanner at the Charite university hospital Berlin with 1 mm slice thickness. Our computer aided nodule detection and segmentation algorithms were deployed on both ultra-low-dose and standard-dose CT data without any dose-specific fine-tuning or preprocessing. As a reference standard 292 nodules from 20 patients were visually identified, each nodule both in ultra-low-dose and standard-dose data sets. The CAD performance was analyzed by virtue of multiple FROC curves for different lower thresholds of the nodule diameter. For nodules with a volume-equivalent diameter equal or larger than 4 mm (149 nodules pairs), we observed a detection rate of 88% at a median false positive rate of 2 per patient in standard-dose images, and 86% detection rate in ultra-low-dose images, also at 2 FPs per patient. Including even smaller nodules equal or larger than 2 mm (272 nodules pairs), we observed a detection rate of 86% in standard-dose images, and 84% detection rate in ultra-low-dose images, both at a rate of 5 FPs per patient. Moreover, we observed a correlation of 94% between the volume-equivalent nodule diameter as automatically measured on ultra-low-dose versus on standard-dose images, indicating that ultra-low-dose CT is also feasible for growth-rate assessment in follow-up examinations. The comparable performance of lung nodule CAD in ultra-low-dose and standard-dose images is of particular interest with respect to lung cancer screening of asymptomatic patients.

Evaluating Imaging and Computer-aided Detection and Diagnosis Devices at the FDA

PubMed Central

Gallas, Brandon D.; Chan, Heang-Ping; D’Orsi, Carl J.; Dodd, Lori E.; Giger, Maryellen L.; Gur, David; Krupinski, Elizabeth A.; Metz, Charles E.; Myers, Kyle J.; Obuchowski, Nancy A.; Sahiner, Berkman; Toledano, Alicia Y.; Zuley, Margarita L.

2017-01-01

This report summarizes the Joint FDA-MIPS Workshop on Methods for the Evaluation of Imaging and Computer-Assist Devices. The purpose of the workshop was to gather information on the current state of the science and facilitate consensus development on statistical methods and study designs for the evaluation of imaging devices to support US Food and Drug Administration submissions. Additionally, participants expected to identify gaps in knowledge and unmet needs that should be addressed in future research. This summary is intended to document the topics that were discussed at the meeting and disseminate the lessons that have been learned through past studies of imaging and computer-aided detection and diagnosis device performance. PMID:22306064

Computational oncology.

PubMed

Lefor, Alan T

2011-08-01

Oncology research has traditionally been conducted using techniques from the biological sciences. The new field of computational oncology has forged a new relationship between the physical sciences and oncology to further advance research. By applying physics and mathematics to oncologic problems, new insights will emerge into the pathogenesis and treatment of malignancies. One major area of investigation in computational oncology centers around the acquisition and analysis of data, using improved computing hardware and software. Large databases of cellular pathways are being analyzed to understand the interrelationship among complex biological processes. Computer-aided detection is being applied to the analysis of routine imaging data including mammography and chest imaging to improve the accuracy and detection rate for population screening. The second major area of investigation uses computers to construct sophisticated mathematical models of individual cancer cells as well as larger systems using partial differential equations. These models are further refined with clinically available information to more accurately reflect living systems. One of the major obstacles in the partnership between physical scientists and the oncology community is communications. Standard ways to convey information must be developed. Future progress in computational oncology will depend on close collaboration between clinicians and investigators to further the understanding of cancer using these new approaches.

A tutorial on the use of ROC analysis for computer-aided diagnostic systems.

PubMed

Scheipers, Ulrich; Perrey, Christian; Siebers, Stefan; Hansen, Christian; Ermert, Helmut

2005-07-01

The application of the receiver operating characteristic (ROC) curve for computer-aided diagnostic systems is reviewed. A statistical framework is presented and different methods of evaluating the classification performance of computer-aided diagnostic systems, and, in particular, systems for ultrasonic tissue characterization, are derived. Most classifiers that are used today are dependent on a separation threshold, which can be chosen freely in many cases. The separation threshold separates the range of output values of the classification system into different target groups, thus conducting the actual classification process. In the first part of this paper, threshold specific performance measures, e.g., sensitivity and specificity, are presented. In the second part, a threshold-independent performance measure, the area under the ROC curve, is reviewed. Only the use of separation threshold-independent performance measures provides classification results that are overall representative for computer-aided diagnostic systems. The following text was motivated by the lack of a complete and definite discussion of the underlying subject in available textbooks, references and publications. Most manuscripts published so far address the theme of performance evaluation using ROC analysis in a manner too general to be practical for everyday use in the development of computer-aided diagnostic systems. Nowadays, the user of computer-aided diagnostic systems typically handles huge amounts of numerical data, not always distributed normally. Many assumptions made in more or less theoretical works on ROC analysis are no longer valid for real-life data. The paper aims at closing the gap between theoretical works and real-life data. The review provides the interested scientist with information needed to conduct ROC analysis and to integrate algorithms performing ROC analysis into classification systems while understanding the basic principles of classification.

Computer-Aided Sensor Development Focused on Security Issues.

PubMed

Bialas, Andrzej

2016-05-26

The paper examines intelligent sensor and sensor system development according to the Common Criteria methodology, which is the basic security assurance methodology for IT products and systems. The paper presents how the development process can be supported by software tools, design patterns and knowledge engineering. The automation of this process brings cost-, quality-, and time-related advantages, because the most difficult and most laborious activities are software-supported and the design reusability is growing. The paper includes a short introduction to the Common Criteria methodology and its sensor-related applications. In the experimental section the computer-supported and patterns-based IT security development process is presented using the example of an intelligent methane detection sensor. This process is supported by an ontology-based tool for security modeling and analyses. The verified and justified models are transferred straight to the security target specification representing security requirements for the IT product. The novelty of the paper is to provide a patterns-based and computer-aided methodology for the sensors development with a view to achieving their IT security assurance. The paper summarizes the validation experiment focused on this methodology adapted for the sensors system development, and presents directions of future research.

Computer-Aided Sensor Development Focused on Security Issues

PubMed Central

Bialas, Andrzej

2016-01-01

The paper examines intelligent sensor and sensor system development according to the Common Criteria methodology, which is the basic security assurance methodology for IT products and systems. The paper presents how the development process can be supported by software tools, design patterns and knowledge engineering. The automation of this process brings cost-, quality-, and time-related advantages, because the most difficult and most laborious activities are software-supported and the design reusability is growing. The paper includes a short introduction to the Common Criteria methodology and its sensor-related applications. In the experimental section the computer-supported and patterns-based IT security development process is presented using the example of an intelligent methane detection sensor. This process is supported by an ontology-based tool for security modeling and analyses. The verified and justified models are transferred straight to the security target specification representing security requirements for the IT product. The novelty of the paper is to provide a patterns-based and computer-aided methodology for the sensors development with a view to achieving their IT security assurance. The paper summarizes the validation experiment focused on this methodology adapted for the sensors system development, and presents directions of future research. PMID:27240360

Key Issues in Instructional Computer Graphics.

ERIC Educational Resources Information Center

Wozny, Michael J.

1981-01-01

Addresses key issues facing universities which plan to establish instructional computer graphics facilities, including computer-aided design/computer aided manufacturing systems, role in curriculum, hardware, software, writing instructional software, faculty involvement, operations, and research. Thirty-seven references and two appendices are…

Identifying opportune landing sites in degraded visual environments with terrain and cultural databases

NASA Astrophysics Data System (ADS)

Moody, Marc; Fisher, Robert; Little, J. Kristin

2014-06-01

Boeing has developed a degraded visual environment navigational aid that is flying on the Boeing AH-6 light attack helicopter. The navigational aid is a two dimensional software digital map underlay generated by the Boeing™ Geospatial Embedded Mapping Software (GEMS) and fully integrated with the operational flight program. The page format on the aircraft's multi function displays (MFD) is termed the Approach page. The existing work utilizes Digital Terrain Elevation Data (DTED) and OpenGL ES 2.0 graphics capabilities to compute the pertinent graphics underlay entirely on the graphics processor unit (GPU) within the AH-6 mission computer. The next release will incorporate cultural databases containing Digital Vertical Obstructions (DVO) to warn the crew of towers, buildings, and power lines when choosing an opportune landing site. Future IRAD will include Light Detection and Ranging (LIDAR) point cloud generating sensors to provide 2D and 3D synthetic vision on the final approach to the landing zone. Collision detection with respect to terrain, cultural, and point cloud datasets may be used to further augment the crew warning system. The techniques for creating the digital map underlay leverage the GPU almost entirely, making this solution viable on most embedded mission computing systems with an OpenGL ES 2.0 capable GPU. This paper focuses on the AH-6 crew interface process for determining a landing zone and flying the aircraft to it.

Imaging Performance of a Handheld Ultrasound System With Real-Time Computer-Aided Detection of Lumbar Spine Anatomy: A Feasibility Study.

PubMed

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.

Investigations in Computer-Aided Instruction and Computer-Aided Controls. Final Report.

ERIC Educational Resources Information Center

Rosenberg, R.C.; And Others

These research projects, designed to delve into certain relationships between humans and computers, are focused on computer-assisted instruction and on man-computer interaction. One study demonstrates that within the limits of formal engineering theory, a computer simulated laboratory (Dynamic Systems Laboratory) can be built in which freshmen…

An esthetics rehabilitation with computer-aided design/ computer-aided manufacturing technology.

PubMed

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.

Computer Aided Grid Interface: An Interactive CFD Pre-Processor

NASA Technical Reports Server (NTRS)

Soni, Bharat K.

1997-01-01

NASA maintains an applications oriented computational fluid dynamics (CFD) efforts complementary to and in support of the aerodynamic-propulsion design and test activities. This is especially true at NASA/MSFC where the goal is to advance and optimize present and future liquid-fueled rocket engines. Numerical grid generation plays a significant role in the fluid flow simulations utilizing CFD. An overall goal of the current project was to develop a geometry-grid generation tool that will help engineers, scientists and CFD practitioners to analyze design problems involving complex geometries in a timely fashion. This goal is accomplished by developing the CAGI: Computer Aided Grid Interface system. The CAGI system is developed by integrating CAD/CAM (Computer Aided Design/Computer Aided Manufacturing) geometric system output and/or Initial Graphics Exchange Specification (IGES) files (including all the NASA-IGES entities), geometry manipulations and generations associated with grid constructions, and robust grid generation methodologies. This report describes the development process of the CAGI system.

Computer Aided Grid Interface: An Interactive CFD Pre-Processor

NASA Technical Reports Server (NTRS)

Soni, Bharat K.

1996-01-01

NASA maintains an applications oriented computational fluid dynamics (CFD) efforts complementary to and in support of the aerodynamic-propulsion design and test activities. This is especially true at NASA/MSFC where the goal is to advance and optimize present and future liquid-fueled rocket engines. Numerical grid generation plays a significant role in the fluid flow simulations utilizing CFD. An overall goal of the current project was to develop a geometry-grid generation tool that will help engineers, scientists and CFD practitioners to analyze design problems involving complex geometries in a timely fashion. This goal is accomplished by developing the Computer Aided Grid Interface system (CAGI). The CAGI system is developed by integrating CAD/CAM (Computer Aided Design/Computer Aided Manufacturing) geometric system output and / or Initial Graphics Exchange Specification (IGES) files (including all the NASA-IGES entities), geometry manipulations and generations associated with grid constructions, and robust grid generation methodologies. This report describes the development process of the CAGI system.

Computational System For Rapid CFD Analysis In Engineering

NASA Technical Reports Server (NTRS)

Barson, Steven L.; Ascoli, Edward P.; Decroix, Michelle E.; Sindir, Munir M.

1995-01-01

Computational system comprising modular hardware and software sub-systems developed to accelerate and facilitate use of techniques of computational fluid dynamics (CFD) in engineering environment. Addresses integration of all aspects of CFD analysis process, including definition of hardware surfaces, generation of computational grids, CFD flow solution, and postprocessing. Incorporates interfaces for integration of all hardware and software tools needed to perform complete CFD analysis. Includes tools for efficient definition of flow geometry, generation of computational grids, computation of flows on grids, and postprocessing of flow data. System accepts geometric input from any of three basic sources: computer-aided design (CAD), computer-aided engineering (CAE), or definition by user.

Computer-aided detection of bladder wall thickening in CT urography (CTU)

NASA Astrophysics Data System (ADS)

Cha, Kenny H.; Hadjiiski, Lubomir M.; Chan, Heang-Ping; Caoili, Elaine M.; Cohan, Richard H.; Weizer, Alon Z.; Gordon, Marshall N.; Samala, Ravi K.

2018-02-01

We are developing a computer-aided detection system for bladder cancer in CT urography (CTU). Bladder wall thickening is a manifestation of bladder cancer and its detection is more challenging than the detection of bladder masses. We first segmented the inner and outer bladder walls using our method that combined deep-learning convolutional neural network with level sets. The non-contrast-enhanced region was separated from the contrast-enhanced region with a maximum-intensity-projection-based method. The non-contrast region was smoothed and gray level threshold was applied to the contrast and non-contrast regions separately to extract the bladder wall and potential lesions. The bladder wall was transformed into a straightened thickness profile, which was analyzed to identify regions of wall thickening candidates. Volume-based features of the wall thickening candidates were analyzed with linear discriminant analysis (LDA) to differentiate bladder wall thickenings from false positives. A data set of 112 patients, 87 with wall thickening and 25 with normal bladders, was collected retrospectively with IRB approval, and split into independent training and test sets. Of the 57 training cases, 44 had bladder wall thickening and 13 were normal. Of the 55 test cases, 43 had wall thickening and 12 were normal. The LDA classifier was trained with the training set and evaluated with the test set. FROC analysis showed that the system achieved sensitivities of 93.2% and 88.4% for the training and test sets, respectively, at 0.5 FPs/case.

A computer-aided approach to detect the fetal behavioral states using multi-sensor Magnetocardiographic recordings.

PubMed

Vairavan, S; Ulusar, U D; Eswaran, H; Preissl, H; Wilson, J D; Mckelvey, S S; Lowery, C L; Govindan, R B

2016-02-01

We propose a novel computational approach to automatically identify the fetal heart rate patterns (fHRPs), which are reflective of sleep/awake states. By combining these patterns with presence or absence of movements, a fetal behavioral state (fBS) was determined. The expert scores were used as the gold standard and objective thresholds for the detection procedure were obtained using Receiver Operating Characteristics (ROC) analysis. To assess the performance, intraclass correlation was computed between the proposed approach and the mutually agreed expert scores. The detected fHRPs were then associated to their corresponding fBS based on the fetal movement obtained from fetal magnetocardiogaphic (fMCG) signals. This approach may aid clinicians in objectively assessing the fBS and monitoring fetal wellbeing. Copyright © 2015 Elsevier Ltd. All rights reserved.

Vertebra identification using template matching modelmp and K-means clustering.

PubMed

Larhmam, Mohamed Amine; Benjelloun, Mohammed; Mahmoudi, Saïd

2014-03-01

Accurate vertebra detection and segmentation are essential steps for automating the diagnosis of spinal disorders. This study is dedicated to vertebra alignment measurement, the first step in a computer-aided diagnosis tool for cervical spine trauma. Automated vertebral segment alignment determination is a challenging task due to low contrast imaging and noise. A software tool for segmenting vertebrae and detecting subluxations has clinical significance. A robust method was developed and tested for cervical vertebra identification and segmentation that extracts parameters used for vertebra alignment measurement. Our contribution involves a novel combination of a template matching method and an unsupervised clustering algorithm. In this method, we build a geometric vertebra mean model. To achieve vertebra detection, manual selection of the region of interest is performed initially on the input image. Subsequent preprocessing is done to enhance image contrast and detect edges. Candidate vertebra localization is then carried out by using a modified generalized Hough transform (GHT). Next, an adapted cost function is used to compute local voted centers and filter boundary data. Thereafter, a K-means clustering algorithm is applied to obtain clusters distribution corresponding to the targeted vertebrae. These clusters are combined with the vote parameters to detect vertebra centers. Rigid segmentation is then carried out by using GHT parameters. Finally, cervical spine curves are extracted to measure vertebra alignment. The proposed approach was successfully applied to a set of 66 high-resolution X-ray images. Robust detection was achieved in 97.5 % of the 330 tested cervical vertebrae. An automated vertebral identification method was developed and demonstrated to be robust to noise and occlusion. This work presents a first step toward an automated computer-aided diagnosis system for cervical spine trauma detection.

Automated detection of dark and bright lesions in retinal images for early detection of diabetic retinopathy.

PubMed

Akram, Usman M; Khan, Shoab A

2012-10-01

There is an ever-increasing interest in the development of automatic medical diagnosis systems due to the advancement in computing technology and also to improve the service by medical community. The knowledge about health and disease is required for reliable and accurate medical diagnosis. Diabetic Retinopathy (DR) is one of the most common causes of blindness and it can be prevented if detected and treated early. DR has different signs and the most distinctive are microaneurysm and haemorrhage which are dark lesions and hard exudates and cotton wool spots which are bright lesions. Location and structure of blood vessels and optic disk play important role in accurate detection and classification of dark and bright lesions for early detection of DR. In this article, we propose a computer aided system for the early detection of DR. The article presents algorithms for retinal image preprocessing, blood vessel enhancement and segmentation and optic disk localization and detection which eventually lead to detection of different DR lesions using proposed hybrid fuzzy classifier. The developed methods are tested on four different publicly available databases. The presented methods are compared with recently published methods and the results show that presented methods outperform all others.

Cloud-Based NoSQL Open Database of Pulmonary Nodules for Computer-Aided Lung Cancer Diagnosis and Reproducible Research.

PubMed

Ferreira Junior, José Raniery; Oliveira, Marcelo Costa; de Azevedo-Marques, Paulo Mazzoncini

2016-12-01

Lung cancer is the leading cause of cancer-related deaths in the world, and its main manifestation is pulmonary nodules. Detection and classification of pulmonary nodules are challenging tasks that must be done by qualified specialists, but image interpretation errors make those tasks difficult. In order to aid radiologists on those hard tasks, it is important to integrate the computer-based tools with the lesion detection, pathology diagnosis, and image interpretation processes. However, computer-aided diagnosis research faces the problem of not having enough shared medical reference data for the development, testing, and evaluation of computational methods for diagnosis. In order to minimize this problem, this paper presents a public nonrelational document-oriented cloud-based database of pulmonary nodules characterized by 3D texture attributes, identified by experienced radiologists and classified in nine different subjective characteristics by the same specialists. Our goal with the development of this database is to improve computer-aided lung cancer diagnosis and pulmonary nodule detection and classification research through the deployment of this database in a cloud Database as a Service framework. Pulmonary nodule data was provided by the Lung Image Database Consortium and Image Database Resource Initiative (LIDC-IDRI), image descriptors were acquired by a volumetric texture analysis, and database schema was developed using a document-oriented Not only Structured Query Language (NoSQL) approach. The proposed database is now with 379 exams, 838 nodules, and 8237 images, 4029 of them are CT scans and 4208 manually segmented nodules, and it is allocated in a MongoDB instance on a cloud infrastructure.

Computer-Aided College Algebra: Learning Components that Students Find Beneficial

ERIC Educational Resources Information Center

Aichele, Douglas B.; Francisco, Cynthia; Utley, Juliana; Wescoatt, Benjamin

2011-01-01

A mixed-method study was conducted during the Fall 2008 semester to better understand the experiences of students participating in computer-aided instruction of College Algebra using the software MyMathLab. The learning environment included a computer learning system for the majority of the instruction, a support system via focus groups (weekly…

Computer Code Aids Design Of Wings

NASA Technical Reports Server (NTRS)

Carlson, Harry W.; Darden, Christine M.

1993-01-01

AERO2S computer code developed to aid design engineers in selection and evaluation of aerodynamically efficient wing/canard and wing/horizontal-tail configurations that includes simple hinged-flap systems. Code rapidly estimates longitudinal aerodynamic characteristics of conceptual airplane lifting-surface arrangements. Developed in FORTRAN V on CDC 6000 computer system, and ported to MS-DOS environment.

Evaluation of Fuzzy Rulemaking for Expert Systems for Failure Detection

NASA Technical Reports Server (NTRS)

Laritz, F.; Sheridan, T. B.

1984-01-01

Computer aids in expert systems were proposed to diagnose failures in complex systems. It is shown that the fuzzy set theory of Zadeh offers a new perspective for modeling for humans thinking and language use. It is assumed that real expert human operators of aircraft, power plants and other systems do not think of their control tasks or failure diagnosis tasks in terms of control laws in differential equation form, but rather keep in mind a set of rules of thumb in fuzzy form. Fuzzy set experiments are described.

Computer-Aided Communication Satellite System Analysis and Optimization.

ERIC Educational Resources Information Center

Stagl, Thomas W.; And Others

Various published computer programs for fixed/broadcast communication satellite system synthesis and optimization are discussed. The rationale for selecting General Dynamics/Convair's Satellite Telecommunication Analysis and Modeling Program (STAMP) in modified form to aid in the system costing and sensitivity analysis work in the Program on…

Strategies for Improved Interpretation of Computer-Aided Detections for CT Colonography Utilizing Distributed Human Intelligence

PubMed Central

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

Strategies for improved interpretation of computer-aided detections for CT colonography utilizing distributed human intelligence.

PubMed

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.

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.

Lung nodule detection from CT scans using 3D convolutional neural networks without candidate selection

NASA Astrophysics Data System (ADS)

Jenuwine, Natalia M.; Mahesh, Sunny N.; Furst, Jacob D.; Raicu, Daniela S.

2018-02-01

Early detection of lung nodules from CT scans is key to improving lung cancer treatment, but poses a significant challenge for radiologists due to the high throughput required of them. Computer-Aided Detection (CADe) systems aim to automatically detect these nodules with computer algorithms, thus improving diagnosis. These systems typically use a candidate selection step, which identifies all objects that resemble nodules, followed by a machine learning classifier which separates true nodules from false positives. We create a CADe system that uses a 3D convolutional neural network (CNN) to detect nodules in CT scans without a candidate selection step. Using data from the LIDC database, we train a 3D CNN to analyze subvolumes from anywhere within a CT scan and output the probability that each subvolume contains a nodule. Once trained, we apply our CNN to detect nodules from entire scans, by systematically dividing the scan into overlapping subvolumes which we input into the CNN to obtain the corresponding probabilities. By enabling our network to process an entire scan, we expect to streamline the detection process while maintaining its effectiveness. Our results imply that with continued training using an iterative training scheme, the one-step approach has the potential to be highly effective.

Strategies for the Creation, Design and Implementation of Effective Interactive Computer-Aided Learning Software in Numerate Business Subjects--The Byzantium Experience.

ERIC Educational Resources Information Center

Wilkinson-Riddle, G. J.; Patel, Ashok

1998-01-01

Discusses courseware development, including intelligent tutoring systems, under the Teaching and Learning Technology Programme and the Byzantium project that was designed to define computer-aided learning performance standards suitable for numerate business subjects; examine reasons to use computer-aided learning; and improve access to educational…

Detection of longitudinal ulcer using roughness value for computer aided diagnosis of Crohn's disease

NASA Astrophysics Data System (ADS)

Oda, Masahiro; Kitasaka, Takayuki; Furukawa, Kazuhiro; Watanabe, Osamu; Ando, Takafumi; Goto, Hidemi; Mori, Kensaku

2011-03-01

The purpose of this paper is to present a new method to detect ulcers, which is one of the symptoms of Crohn's disease, from CT images. Crohn's disease is an inflammatory disease of the digestive tract. Crohn's disease commonly affects the small intestine. An optical or a capsule endoscope is used for small intestine examinations. However, these endoscopes cannot pass through intestinal stenosis parts in some cases. A CT image based diagnosis allows a physician to observe whole intestine even if intestinal stenosis exists. However, because of the complicated shape of the small and large intestines, understanding of shapes of the intestines and lesion positions are difficult in the CT image based diagnosis. Computer-aided diagnosis system for Crohn's disease having automated lesion detection is required for efficient diagnosis. We propose an automated method to detect ulcers from CT images. Longitudinal ulcers make rough surface of the small and large intestinal wall. The rough surface consists of combination of convex and concave parts on the intestinal wall. We detect convex and concave parts on the intestinal wall by a blob and an inverse-blob structure enhancement filters. A lot of convex and concave parts concentrate on roughed parts. We introduce a roughness value to differentiate convex and concave parts concentrated on the roughed parts from the other on the intestinal wall. The roughness value effectively reduces false positives of ulcer detection. Experimental results showed that the proposed method can detect convex and concave parts on the ulcers.

Computer-aided detection system for chest radiography: reducing report turnaround times of examinations with abnormalities.

PubMed

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.

Computer Assisted Instructional Design for Computer-Based Instruction. Final Report. Working Papers.

ERIC Educational Resources Information Center

Russell, Daniel M.; Pirolli, Peter

Recent advances in artificial intelligence and the cognitive sciences have made it possible to develop successful intelligent computer-aided instructional systems for technical and scientific training. In addition, computer-aided design (CAD) environments that support the rapid development of such computer-based instruction have also been recently…

Implementation of combined SVM-algorithm and computer-aided perception feedback for pulmonary nodule detection

NASA Astrophysics Data System (ADS)

Pietrzyk, Mariusz W.; Rannou, Didier; Brennan, Patrick C.

2012-02-01

This pilot study examines the effect of a novel decision support system in medical image interpretation. This system is based on combining image spatial frequency properties and eye-tracking data in order to recognize over and under calling errors. Thus, before it can be implemented as a detection aided schema, training is required during which SVMbased algorithm learns to recognize FP from all reported outcomes, and, FN from all unreported prolonged dwelled regions. Eight radiologists inspected 50 PA chest radiographs with the specific task of identifying lung nodules. Twentyfive cases contained CT proven subtle malignant lesions (5-20mm), but prevalence was not known by the subjects, who took part in two sequential reading sessions, the second, without and with support system feedback. MCMR ROC DBM and JAFROC analyses were conducted and demonstrated significantly higher scores following feedback with p values of 0.04, and 0.03 respectively, highlighting significant improvements in radiology performance once feedback was used. This positive effect on radiologists' performance might have important implications for future CAD-system development.

A Model for Intelligent Computer-Aided Education Systems.

ERIC Educational Resources Information Center

Du Plessis, Johan P.; And Others

1995-01-01

Proposes a model for intelligent computer-aided education systems that is based on cooperative learning, constructive problem-solving, object-oriented programming, interactive user interfaces, and expert system techniques. Future research is discussed, and a prototype for teaching mathematics to 10- to 12-year-old students is appended. (LRW)

23 CFR 771.117 - Categorical exclusions.

Code of Federal Regulations, 2010 CFR

2010-04-01

..., computer-aided dispatching systems, radio communications systems, dynamic message signs, and security... effects can be assessed; and Federal-aid system revisions which establish classes of highways on the Federal-aid highway system. (2) Approval of utility installations along or across a transportation...

Primary or secondary tasks? Dual-task interference between cyclist hazard perception and cadence control using cross-modal sensory aids with rider assistance bike computers.

PubMed

Yang, Chao-Yang; Wu, Cheng-Tse

2017-03-01

This research investigated the risks involved in bicycle riding while using various sensory modalities to deliver training information. To understand the risks associated with using bike computers, this study evaluated hazard perception performance through lab-based simulations of authentic riding conditions. Analysing hazard sensitivity (d') of signal detection theory, the rider's response time, and eye glances provided insights into the risks of using bike computers. In this study, 30 participants were tested with eight hazard perception tasks while they maintained a cadence of 60 ± 5 RPM and used bike computers with different sensory displays, namely visual, auditory, and tactile feedback signals. The results indicated that synchronously using different sense organs to receive cadence feedback significantly affects hazard perception performance; direct visual information leads to the worst rider distraction, with a mean sensitivity to hazards (d') of -1.03. For systems with multiple interacting sensory aids, auditory aids were found to result in the greatest reduction in sensitivity to hazards (d' mean = -0.57), whereas tactile sensory aids reduced the degree of rider distraction (d' mean = -0.23). Our work complements existing work in this domain by advancing the understanding of how to design devices that deliver information subtly, thereby preventing disruption of a rider's perception of road hazards. Copyright © 2016 Elsevier Ltd. All rights reserved.

Use of Current 2010 Forest Disturbance Monitoring Products for the Conterminous United States in Aiding a National Forest Threat Early Warning System

NASA Technical Reports Server (NTRS)

Spruce, Joseph P.; Hargrove, William; Gasser, J.; Smoot, J.; Kuper, P.

2010-01-01

This presentation discusses contributions of near real time (NRT) MODIS forest disturbance detection products for the conterminous United States to an emerging national forest threat early warning system (EWS). The latter is being developed by the USDA Forest Service s Eastern and Western Environmental Threat Centers with help from NASA Stennis Space Center and the Oak Ridge National Laboratory. Building off work done in 2009, this national and regional forest disturbance detection and viewing capability of the EWS employs NRT MODIS NDVI data from the USGS eMODIS group and historical NDVI data from standard MOD13 products. Disturbance detection products are being computed for 24 day composites that are refreshed every 8 days. Products for 2010 include 42 dates of the 24 day composites. For each compositing date, we computed % change in forest maximum NDVI products for 2010 with respect to each of three historical baselines of 2009, 2007-2009, and 2003-2009,. The three baselines enable one to view potential current, recent, and longer term forest disturbances. A rainbow color table was applied to each forest change product so that potential disturbances (NDVI drops) were identified in hot color tones and growth (NDVI gains) in cold color tones. Example products were provided to end-users responsible for forest health monitoring at the Federal and State levels. Large patches of potential forest disturbances were validated based on comparisons with available reference data, including Landsat and field survey data. Products were posted on two internet mapping systems for US Forest Service internal and collaborator use. MODIS forest disturbance detection products were computed and posted for use in as little as 1 day after the last input date of the compositing period. Such products were useful for aiding aerial disturbance detection surveys and for assessing disturbance persistence on both inter- and intra-annual scales. Multiple 2010 forest disturbance events were detected across the nation, including damage from ice storms, tornadoes, caterpillars, bark beetles, and wildfires. This effort enabled improved NRT forest disturbance monitoring capabilities for this nation-wide forest threat EWS.

Use of Current 2010 Forest Disturbance Monitoring Products for the Conterminous United States in Aiding a National Forest Threat Early Warning System

NASA Astrophysics Data System (ADS)

Spruce, J.; Hargrove, W. W.; Gasser, J.; Smoot, J.; Kuper, P.

2010-12-01

This presentation discusses contributions of near real time (NRT) MODIS forest disturbance detection products for the conterminous United States to an emerging national forest threat early warning system (EWS). The latter is being developed by the USDA Forest Service’s Eastern and Western Environmental Threat Centers with help from NASA Stennis Space Center and the Oak Ridge National Laboratory. Building off work done in 2009, this national and regional forest disturbance detection and viewing capability of the EWS employs NRT MODIS NDVI data from the USGS eMODIS group and historical NDVI data from standard MOD13 products. Disturbance detection products are being computed for 24 day composites that are refreshed every 8 days. Products for 2010 include 42 dates of the 24 day composites. For each compositing date, we computed % change in forest maximum NDVI products for 2010 with respect to each of three historical baselines of 2009, 2007-2009, and 2003-2009. The three baselines enable one to view potential current, recent, and longer term forest disturbances. A rainbow color table was applied to each forest change product so that potential disturbances (NDVI drops) were identified in hot color tones and growth (NDVI gains) in cold color tones. Example products were provided to end-users responsible for forest health monitoring at the Federal and State levels. Large patches of potential forest disturbances were validated based on comparisons with available reference data, including Landsat and field survey data. Products were posted on two internet mapping systems for US Forest Service internal and collaborator use. MODIS forest disturbance detection products were computed and posted for use in as little as 1 day after the last input date of the compositing period. Such products were useful for aiding aerial disturbance detection surveys and for assessing disturbance persistence on both inter- and intra-annual scales. Multiple 2010 forest disturbance events were detected across the nation, including damage from ice storms, tornados, caterpillars, bark beetles, and wildfires. This effort enabled improved NRT forest disturbance monitoring capabilities for this nation-wide forest threat EWS.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jackson, K.A.; Neuman, M.C.; Simmonds, D.D.

An effective method for detecting computer misuse is the automatic monitoring and analysis of on-line user activity. This activity is reflected in the system audit record, in the system vulnerability posture, and in other evidence found through active testing of the system. During the last several years we have implemented an automatic misuse detection system at Los Alamos. This is the Network Anomaly Detection and Intrusion Reporter (NADIR). We are currently expanding NADIR to include processing of the Cray UNICOS operating system. This new component is called the UNICOS Realtime NADIR, or UNICORN. UNICORN summarizes user activity and system configurationmore » in statistical profiles. It compares these profiles to expert rules that define security policy and improper or suspicious behavior. It reports suspicious behavior to security auditors and provides tools to aid in follow-up investigations. The first phase of UNICORN development is nearing completion, and will be operational in late 1994.« less

A method for evaluating the performance of computer-aided detection of pulmonary nodules in lung cancer CT screening: detection limit for nodule size and density

PubMed Central

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

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

Analysis of the impact of digital watermarking on computer-aided diagnosis in medical imaging.

PubMed

Garcia-Hernandez, Jose Juan; Gomez-Flores, Wilfrido; Rubio-Loyola, Javier

2016-01-01

Medical images (MI) are relevant sources of information for detecting and diagnosing a large number of illnesses and abnormalities. Due to their importance, this study is focused on breast ultrasound (BUS), which is the main adjunct for mammography to detect common breast lesions among women worldwide. On the other hand, aiming to enhance data security, image fidelity, authenticity, and content verification in e-health environments, MI watermarking has been widely used, whose main goal is to embed patient meta-data into MI so that the resulting image keeps its original quality. In this sense, this paper deals with the comparison of two watermarking approaches, namely spread spectrum based on the discrete cosine transform (SS-DCT) and the high-capacity data-hiding (HCDH) algorithm, so that the watermarked BUS images are guaranteed to be adequate for a computer-aided diagnosis (CADx) system, whose two principal outcomes are lesion segmentation and classification. Experimental results show that HCDH algorithm is highly recommended for watermarking medical images, maintaining the image quality and without introducing distortion into the output of CADx. Copyright © 2015 Elsevier Ltd. All rights reserved.

Interactive computer aided technology, evolution in the design/manufacturing process

NASA Technical Reports Server (NTRS)

English, C. H.

1975-01-01

A powerful computer-operated three dimensional graphic system and associated auxiliary computer equipment used in advanced design, production design, and manufacturing was described. This system has made these activities more productive than when using older and more conventional methods to design and build aerospace vehicles. With the use of this graphic system, designers are now able to define parts using a wide variety of geometric entities, define parts as fully surface 3-dimensional models as well as "wire-frame" models. Once geometrically defined, the designer is able to take section cuts of the surfaced model and automatically determine all of the section properties of the planar cut, lightpen detect all of the surface patches and automatically determine the volume and weight of the part. Further, his designs are defined mathematically at a degree of accuracy never before achievable.

A Multidisciplinary Research Team Approach to Computer-Aided Drafting (CAD) System Selection. Final Report.

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…

Proceedings of the Workshop on Computational Aspects in the Control of Flexible Systems, part 1

NASA Technical Reports Server (NTRS)

Taylor, Lawrence W., Jr. (Compiler)

1989-01-01

Control/Structures Integration program software needs, computer aided control engineering for flexible spacecraft, computer aided design, computational efficiency and capability, modeling and parameter estimation, and control synthesis and optimization software for flexible structures and robots are among the topics discussed.

Computer-aided design/computer-aided manufacturing skull base drill.

PubMed

Couldwell, William T; MacDonald, Joel D; Thomas, Charles L; Hansen, Bradley C; Lapalikar, Aniruddha; Thakkar, Bharat; Balaji, Alagar K

2017-05-01

The authors have developed a simple device for computer-aided design/computer-aided manufacturing (CAD-CAM) that uses an image-guided system to define a cutting tool path that is shared with a surgical machining system for drilling bone. Information from 2D images (obtained via CT and MRI) is transmitted to a processor that produces a 3D image. The processor generates code defining an optimized cutting tool path, which is sent to a surgical machining system that can drill the desired portion of bone. This tool has applications for bone removal in both cranial and spine neurosurgical approaches. Such applications have the potential to reduce surgical time and associated complications such as infection or blood loss. The device enables rapid removal of bone within 1 mm of vital structures. The validity of such a machining tool is exemplified in the rapid (< 3 minutes machining time) and accurate removal of bone for transtemporal (for example, translabyrinthine) approaches.

Speaking Volumes About 3-D

NASA Technical Reports Server (NTRS)

2002-01-01

In 1999, Genex submitted a proposal to Stennis Space Center for a volumetric 3-D display technique that would provide multiple users with a 360-degree perspective to simultaneously view and analyze 3-D data. The futuristic capabilities of the VolumeViewer(R) have offered tremendous benefits to commercial users in the fields of medicine and surgery, air traffic control, pilot training and education, computer-aided design/computer-aided manufacturing, and military/battlefield management. The technology has also helped NASA to better analyze and assess the various data collected by its satellite and spacecraft sensors. Genex capitalized on its success with Stennis by introducing two separate products to the commercial market that incorporate key elements of the 3-D display technology designed under an SBIR contract. The company Rainbow 3D(R) imaging camera is a novel, three-dimensional surface profile measurement system that can obtain a full-frame 3-D image in less than 1 second. The third product is the 360-degree OmniEye(R) video system. Ideal for intrusion detection, surveillance, and situation management, this unique camera system offers a continuous, panoramic view of a scene in real time.

Communication Aid with Human Eyes Only

NASA Astrophysics Data System (ADS)

Arai, Kohei; Yajima, Kenro

A communication aid with human eyes only is proposed. A set of candidate character is displayed onto computer screen of relatively small and light Head Mount Display: HMD that is mounted on glasses of which user wears on. When user looks at a candidate character with his/hers left eye while right eye picture is taken with small and light web camera that also is mounted on the glasses. The proposed system can selects 81 characters with two layers of 9 by 9 character candidate image. Other than these there is another selective image including control keys and frequently use of sentences. By using image matching between previously acquired template image for each candidate character and the currently acquired image, the proposed system realizes that which character in the candidates is selected. By using blinking and fix one's eye on combine together, the proposed system recognizes that user determines the selected key from the candidates. The blinking detection method employs a morphologic filter to avoid misunderstanding of dark eye detection due to eyebrows and shadows. Thus user can input sentences. User also may edit the sentences and then the sentences are read with Text to Speech: TTS software tool. Thus the system allows support conversations between handicapped and disabled persons without voice and the others peoples because only the function required for conversation is human eyes. Also the proposed system can be used as an input system for wearable computing systems. Test results by the 6 different able persons show that the proposed system does work with acceptable speed, around 1.5 second / character.

Performance of fusion algorithms for computer-aided detection and classification of mines in very shallow water obtained from testing in navy Fleet Battle Exercise-Hotel 2000

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.

Unit cell-based computer-aided manufacturing system for tissue engineering.

PubMed

Kang, Hyun-Wook; Park, Jeong Hun; Kang, Tae-Yun; Seol, Young-Joon; Cho, Dong-Woo

2012-03-01

Scaffolds play an important role in the regeneration of artificial tissues or organs. A scaffold is a porous structure with a micro-scale inner architecture in the range of several to several hundreds of micrometers. Therefore, computer-aided construction of scaffolds should provide sophisticated functionality for porous structure design and a tool path generation strategy that can achieve micro-scale architecture. In this study, a new unit cell-based computer-aided manufacturing (CAM) system was developed for the automated design and fabrication of a porous structure with micro-scale inner architecture that can be applied to composite tissue regeneration. The CAM system was developed by first defining a data structure for the computing process of a unit cell representing a single pore structure. Next, an algorithm and software were developed and applied to construct porous structures with a single or multiple pore design using solid freeform fabrication technology and a 3D tooth/spine computer-aided design model. We showed that this system is quite feasible for the design and fabrication of a scaffold for tissue engineering.

Is computer-aided interpretation of 99Tcm-HMPAO leukocyte scans better than the naked eye?

PubMed

Almer, S; Peters, A M; Ekberg, S; Franzén, L; Granerus, G; Ström, M

1995-04-01

In order to compare visual interpretation of inflammation detected by leukocyte scintigraphy with that of different computer-aided quantification methods, 34 patients (25 with ulcerative colitis and 9 with endoscopically verified non-inflamed colonic mucosa), were investigated using 99Tcm-hexamethylpropyleneamine oxime (99Tcm-HMPAO) leukocyte scintigraphy and colonoscopy with biopsies. Scintigrams were obtained 45 min and 4 h after the injection of labelled cells. Computer-generated grading of seven colon segments using four different methods was performed on each scintigram for each patient. The same segments were graded independently using a 4-point visual scale. Endoscopic and histological inflammation were scored on 4-point scales. At 45 min, a positive correlation was found between endoscopic and scan gradings in individual colon segments when using visual grading and three of the four computer-aided methods (Spearman's rs = 0.30-0.64, P < 0.001). Histological grading correlated with visual grading and with two of the four computer-aided methods at 45 min (rs = 0.42-0.54, P < 0.001). At 4 h, all grading methods correlated positively with both endoscopic and histological assessment. The correlation coefficients were, in all but one instance, highest for the visual grading. As an inter-observer comparison to assess agreement between the visual gradings of two nuclear physicians, 14 additional patients (9 ulcerative colitis, 5 infectious enterocolitis) underwent leukocyte scintigraphy. Agreement assessed using kappa statistics was 0.54 at 45 min (P < 0.001). Separate data concerning the presence/absence of active inflammation showed a high kappa value (0.74, P < 0.001). Our results showed that a simple scintigraphic scoring system based on assessment using the human eye reflects colonic inflammation at least as well as computer-aided grading, and that highly correlated results can be achieved between different investigators.

Computer-aided detection of bladder mass within non-contrast-enhanced region of CT Urography (CTU)

NASA Astrophysics Data System (ADS)

Cha, Kenny H.; Hadjiiski, Lubomir M.; Chan, Heang-Ping; Caoili, Elaine M.; Cohan, Richard H.; Weizer, Alon; Zhou, Chuan

2016-03-01

We are developing a computer-aided detection system for bladder cancer in CT urography (CTU). We have previously developed methods for detection of bladder masses within the contrast-enhanced region of the bladder. In this study, we investigated methods for detection of bladder masses within the non-contrast enhanced region. The bladder was first segmented using a newly developed deep-learning convolutional neural network in combination with level sets. The non-contrast-enhanced region was separated from the contrast-enhanced region with a maximum-intensityprojection- based method. The non-contrast region was smoothed and a gray level threshold was employed to segment the bladder wall and potential masses. The bladder wall was transformed into a straightened thickness profile, which was analyzed to identify lesion candidates as a prescreening step. The lesion candidates were segmented using our autoinitialized cascaded level set (AI-CALS) segmentation method, and 27 morphological features were extracted for each candidate. Stepwise feature selection with simplex optimization and leave-one-case-out resampling were used for training and validation of a false positive (FP) classifier. In each leave-one-case-out cycle, features were selected from the training cases and a linear discriminant analysis (LDA) classifier was designed to merge the selected features into a single score for classification of the left-out test case. A data set of 33 cases with 42 biopsy-proven lesions in the noncontrast enhanced region was collected. During prescreening, the system obtained 83.3% sensitivity at an average of 2.4 FPs/case. After feature extraction and FP reduction by LDA, the system achieved 81.0% sensitivity at 2.0 FPs/case, and 73.8% sensitivity at 1.5 FPs/case.

Clinical experience with a computer-aided diagnosis system for automatic detection of pulmonary nodules at spiral CT of the chest

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.

The NASA computer aided design and test system

NASA Technical Reports Server (NTRS)

Gould, J. M.; Juergensen, K.

1973-01-01

A family of computer programs facilitating the design, layout, evaluation, and testing of digital electronic circuitry is described. CADAT (computer aided design and test system) is intended for use by NASA and its contractors and is aimed predominantly at providing cost effective microelectronic subsystems based on custom designed metal oxide semiconductor (MOS) large scale integrated circuits (LSIC's). CADAT software can be easily adopted by installations with a wide variety of computer hardware configurations. Its structure permits ease of update to more powerful component programs and to newly emerging LSIC technologies. The components of the CADAT system are described stressing the interaction of programs rather than detail of coding or algorithms. The CADAT system provides computer aids to derive and document the design intent, includes powerful automatic layout software, permits detailed geometry checks and performance simulation based on mask data, and furnishes test pattern sequences for hardware testing.

Diagnosis of toxoplasmic encephalitis in patients with acquired immunodeficiency syndrome by using a new serologic method.

PubMed Central

Suzuki, Y; Israelski, D M; Dannemann, B R; Stepick-Biek, P; Thulliez, P; Remington, J S

1988-01-01

The present study was performed to develop a serological method for diagnosing toxoplasmic encephalitis in patients with acquired immunodeficiency syndrome (AIDS). The trophozoite form of Toxoplasma gondii, fixed with either Formalin or acetone, was used in a modification of an agglutination method previously shown to differentiate between the acute and the chronic (latent) stages of infection with toxoplasma in immunologically normal persons. By using these antigens in separate tests and evaluating the data for statistical significance, 70% of patients with AIDS with biopsy-proven toxoplasmic encephalitis were distinguished from control, ambulatory patients with AIDS with toxoplasma antibodies but without signs or symptoms of central nervous system involvement. In a separate study, the agglutination tests identified from controls 84% of patients with AIDS with two or more brain lesions detected by computed-tomographic or magnetic-resonance-imaging scans and suspected of having toxoplasmic encephalitis. Thus, these agglutination tests should prove valuable for the noninvasive diagnosis of toxoplasmic encephalitis in patients with AIDS. PMID:3230132

System integration of pattern recognition, adaptive aided, upper limb prostheses

NASA Technical Reports Server (NTRS)

Lyman, J.; Freedy, A.; Solomonow, M.

1975-01-01

The requirements for successful integration of a computer aided control system for multi degree of freedom artificial arms are discussed. Specifications are established for a system which shares control between a human amputee and an automatic control subsystem. The approach integrates the following subsystems: (1) myoelectric pattern recognition, (2) adaptive computer aiding; (3) local reflex control; (4) prosthetic sensory feedback; and (5) externally energized arm with the functions of prehension, wrist rotation, elbow extension and flexion and humeral rotation.

Computer aided diagnosis system for the Alzheimer's disease based on partial least squares and random forest SPECT image classification.

PubMed

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.

Modeling and Analysis of Power Processing Systems (MAPPS). Volume 1: Technical report

NASA Technical Reports Server (NTRS)

Lee, F. C.; Rahman, S.; Carter, R. A.; Wu, C. H.; Yu, Y.; Chang, R.

1980-01-01

Computer aided design and analysis techniques were applied to power processing equipment. Topics covered include: (1) discrete time domain analysis of switching regulators for performance analysis; (2) design optimization of power converters using augmented Lagrangian penalty function technique; (3) investigation of current-injected multiloop controlled switching regulators; and (4) application of optimization for Navy VSTOL energy power system. The generation of the mathematical models and the development and application of computer aided design techniques to solve the different mathematical models are discussed. Recommendations are made for future work that would enhance the application of the computer aided design techniques for power processing systems.

Algorithms for detection of objects in image sequences captured from an airborne imaging system

NASA Technical Reports Server (NTRS)

Kasturi, Rangachar; Camps, Octavia; Tang, Yuan-Liang; Devadiga, Sadashiva; Gandhi, Tarak

1995-01-01

This research was initiated as a part of the effort at the NASA Ames Research Center to design a computer vision based system that can enhance the safety of navigation by aiding the pilots in detecting various obstacles on the runway during critical section of the flight such as a landing maneuver. The primary goal is the development of algorithms for detection of moving objects from a sequence of images obtained from an on-board video camera. Image regions corresponding to the independently moving objects are segmented from the background by applying constraint filtering on the optical flow computed from the initial few frames of the sequence. These detected regions are tracked over subsequent frames using a model based tracking algorithm. Position and velocity of the moving objects in the world coordinate is estimated using an extended Kalman filter. The algorithms are tested using the NASA line image sequence with six static trucks and a simulated moving truck and experimental results are described. Various limitations of the currently implemented version of the above algorithm are identified and possible solutions to build a practical working system are investigated.

An evaluation of computer-aided disproportionality analysis for post-marketing signal detection.

PubMed

Lehman, H P; Chen, J; Gould, A L; Kassekert, R; Beninger, P R; Carney, R; Goldberg, M; Goss, M A; Kidos, K; Sharrar, R G; Shields, K; Sweet, A; Wiholm, B E; Honig, P K

2007-08-01

To understand the value of computer-aided disproportionality analysis (DA) in relation to current pharmacovigilance signal detection methods, four products were retrospectively evaluated by applying an empirical Bayes method to Merck's post-marketing safety database. Findings were compared with the prior detection of labeled post-marketing adverse events. Disproportionality ratios (empirical Bayes geometric mean lower 95% bounds for the posterior distribution (EBGM05)) were generated for product-event pairs. Overall (1993-2004 data, EBGM05> or =2, individual terms) results of signal detection using DA compared to standard methods were sensitivity, 31.1%; specificity, 95.3%; and positive predictive value, 19.9%. Using groupings of synonymous labeled terms, sensitivity improved (40.9%). More of the adverse events detected by both methods were detected earlier using DA and grouped (versus individual) terms. With 1939-2004 data, diagnostic properties were similar to those from 1993 to 2004. DA methods using Merck's safety database demonstrate sufficient sensitivity and specificity to be considered for use as an adjunct to conventional signal detection methods.

Computer-Aided Detection of Mammographic Masses in Dense Breast Images

DTIC Science & Technology

2005-06-01

Kinnard, Ph.D. CONTRACTING ORGANIZATION: Howard University Washington, DC 20059 REPORT DATE: June 2005 TYPE OF REPORT: Annual Summary PREPARED FOR: U.S...AND ADDRESS(ES) 8. PERFORMING ORGANIZATION REPORT NUMBER Howard University Washington, DC 20059 9. SPONSORING / MONITORING AGENCY NAME(S) AND ADDRESS(ES...34, Preparing for the Postdoctoral Institute, August, 2004, Howard University and The University of Texas at El Paso. 2. "Computer-Aided Diagnosis and Image

Three-dimensional surgical simulation.

PubMed

Cevidanes, Lucia H C; Tucker, Scott; Styner, Martin; Kim, Hyungmin; Chapuis, Jonas; Reyes, Mauricio; Proffit, William; Turvey, Timothy; Jaskolka, Michael

2010-09-01

In this article, we discuss the development of methods for computer-aided jaw surgery, which allows us to incorporate the high level of precision necessary for transferring virtual plans into the operating room. We also present a complete computer-aided surgery system developed in close collaboration with surgeons. Surgery planning and simulation include construction of 3-dimensional surface models from cone-beam computed tomography, dynamic cephalometry, semiautomatic mirroring, interactive cutting of bone, and bony segment repositioning. A virtual setup can be used to manufacture positioning splints for intraoperative guidance. The system provides further intraoperative assistance with a computer display showing jaw positions and 3-dimensional positioning guides updated in real time during the surgical procedure. The computer-aided surgery system aids in dealing with complex cases with benefits for the patient, with surgical practice, and for orthodontic finishing. Advanced software tools for diagnosis and treatment planning allow preparation of detailed operative plans, osteotomy repositioning, bone reconstructions, surgical resident training, and assessing the difficulties of the surgical procedures before the surgery. Computer-aided surgery can make the elaboration of the surgical plan a more flexible process, increase the level of detail and accuracy of the plan, yield higher operative precision and control, and enhance documentation of cases. 2010 American Association of Orthodontists. Published by Mosby, Inc. All rights reserved.

A new 2D segmentation method based on dynamic programming applied to computer aided detection in mammography.

PubMed

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.

[Key points for esthetic rehabilitation of anterior teeth using chair-side computer aided design and computer aided manufacture technique].

PubMed

Yang, J; Feng, H L

2018-04-09

With the rapid development of the chair-side computer aided design and computer aided manufacture (CAD/CAM) technology, its accuracy and operability of have been greatly improved in recent years. Chair-side CAD/CAM system may produce all kinds of indirect restorations, and has the advantages of rapid, accurate and stable production. It has become the future development direction of Stomatology. This paper describes the clinical application of the chair-side CAD/CAM technology for anterior aesthetic restorations from the aspects of shade and shape.

Computer-aided diagnosis of leukoencephalopathy in children treated for acute lymphoblastic leukemia

NASA Astrophysics Data System (ADS)

Glass, John O.; Li, Chin-Shang; Helton, Kathleen J.; Reddick, Wilburn E.

2005-04-01

The purpose of this study was to use objective quantitative MR imaging methods to develop a computer-aided diagnosis tool to differentiate white matter (WM) hyperintensities as either leukoencephalopathy (LE) or normal maturational processes in children treated for acute lymphoblastic leukemia with intravenous high dose methotrexate. A combined imaging set consisting of T1, T2, PD, and FLAIR MR images and WM, gray matter, and cerebrospinal fluid a priori maps from a spatially normalized atlas were analyzed with a neural network segmentation based on a Kohonen Self-Organizing Map. Segmented regions were manually classified to identify the most hyperintense WM region and the normal appearing genu region. Signal intensity differences normalized to the genu within each examination were generated for two time points in 203 children. An unsupervised hierarchical clustering algorithm with the agglomeration method of McQuitty was used to divide data from the first examination into normal appearing or LE groups. A C-support vector machine (C-SVM) was then trained on the first examination data and used to classify the data from the second examination. The overall accuracy of the computer-aided detection tool was 83.5% (299/358) with sensitivity to normal WM of 86.9% (199/229) and specificity to LE of 77.5% (100/129) when compared to the readings of two expert observers. These results suggest that subtle therapy-induced leukoencephalopathy can be objectively and reproducibly detected in children treated for cancer using this computer-aided detection approach based on relative differences in quantitative signal intensity measures normalized within each examination.

SAMO (Sistema de Apoyo Mechanizado a la Operacion): An operational aids computer system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stormer, T.D.; Laflor, E.V.

1989-01-01

SAMO (Sistema de Apoyo Mechanizado a la Operacion) is a sensor-driven, computer-based, graphic display system designed by Westinghouse to aid the A. N. Asco operations staff during all modes of plant operations, including emergencies. The SAMO system is being implemented in the A. N. Asco plant in two phases that coincide with consecutive refueling outages for each of two nuclear units at the Asco site. Phase 1 of the SAMO system implements the following functions: (1) emergency operational aids, (2) postaccident monitoring, (3) plant graphics display, (4) high-speed transient analysis recording, (5) historical data collection, storage, and retrieval, (6) sequencemore » of events, and (7) posttrip review. During phase 2 of the SAMO project, the current plant computer will be removed and the functions now performed by the plant computer will be performed by the SAMO system. In addition, the following functions will be implemented: (1) normal and simple transients operational aid, (2) plant information graphics; and (3) real-time radiological off-site dose calculation.« less

Persons with Alzheimer's Disease Make Phone Calls Independently Using a Computer-Aided Telephone System

ERIC Educational Resources Information Center

Perilli, Viviana; Lancioni, Giulio E.; Singh, Nirbhay N.; O'Reilly, Mark F.; Sigafoos, Jeff; Cassano, Germana; Cordiano, Noemi; Pinto, Katia; Minervini, Mauro G.; Oliva, Doretta

2012-01-01

This study assessed whether four patients with a diagnosis of Alzheimer's disease could make independent phone calls via a computer-aided telephone system. The study was carried out according to a non-concurrent multiple baseline design across participants. All participants started with baseline during which the telephone system was not available,…

Mixed-Initiative Information System for Computer-Aided Training and Decision Making. Final Report.

ERIC Educational Resources Information Center

Grignetti, Mario C.; Warnock, Eleanor H.

A description of the NET-SCHOLAR system, an on-line aid for naive users of the Advanced Research Projects Administration (ARPA) Computer Network, is provided. The discussion focuses upon the system's representation and handling of functional and procedural information and its ability to deal with action verbs, all within the context of the ARPA…

Design, Development, Implementation, and Evaluation of the Computer Aided Interactive Testing System (CAITS). Focus on the Trained Person.

ERIC Educational Resources Information Center

1983

This report describes the design, development, implementation, and evaluation of the Computer Aided Interactive Testing System (CAITS) and addresses the applicability of the system in the Naval Education and Training Command. In addition to an introduction (section one), the report contains four sections and three appendices. Section two describes…

Functional Specifications for Computer Aided Training Systems Development and Management (CATSDM) Support Functions. Final Report.

ERIC Educational Resources Information Center

Hughes, John; And Others

This report provides a description of a Computer Aided Training System Development and Management (CATSDM) environment based on state-of-the-art hardware and software technology, and including recommendations for off the shelf systems to be utilized as a starting point in addressing the particular systematic training and instruction design and…

A Complete Interactive Graphical Computer-Aided Instruction System.

ERIC Educational Resources Information Center

Abrams, Steven Selby

The use of interactive graphics in computer-aided instruction systems is discussed with emphasis placed on two requirements of such a system. The first is the need to provide the teacher with a useful tool with which to design and modify teaching sessions tailored to the individual needs and capabilities of the students. The second is the…

SVM classifier on chip for melanoma detection.

PubMed

Afifi, Shereen; GholamHosseini, Hamid; Sinha, Roopak

2017-07-01

Support Vector Machine (SVM) is a common classifier used for efficient classification with high accuracy. SVM shows high accuracy for classifying melanoma (skin cancer) clinical images within computer-aided diagnosis systems used by skin cancer specialists to detect melanoma early and save lives. We aim to develop a medical low-cost handheld device that runs a real-time embedded SVM-based diagnosis system for use in primary care for early detection of melanoma. In this paper, an optimized SVM classifier is implemented onto a recent FPGA platform using the latest design methodology to be embedded into the proposed device for realizing online efficient melanoma detection on a single system on chip/device. The hardware implementation results demonstrate a high classification accuracy of 97.9% and a significant acceleration factor of 26 from equivalent software implementation on an embedded processor, with 34% of resources utilization and 2 watts for power consumption. Consequently, the implemented system meets crucial embedded systems constraints of high performance and low cost, resources utilization and power consumption, while achieving high classification accuracy.

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.

ΤND: a thyroid nodule detection system for analysis of ultrasound images and videos.

PubMed

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.

Modeling And Simulation Of Bar Code Scanners Using Computer Aided Design Software

NASA Astrophysics Data System (ADS)

Hellekson, Ron; Campbell, Scott

1988-06-01

Many optical systems have demanding requirements to package the system in a small 3 dimensional space. The use of computer graphic tools can be a tremendous aid to the designer in analyzing the optical problems created by smaller and less costly systems. The Spectra Physics grocery store bar code scanner employs an especially complex 3 dimensional scan pattern to read bar code labels. By using a specially written program which interfaces with a computer aided design system, we have simulated many of the functions of this complex optical system. In this paper we will illustrate how a recent version of the scanner has been designed. We will discuss the use of computer graphics in the design process including interactive tweaking of the scan pattern, analysis of collected light, analysis of the scan pattern density, and analysis of the manufacturing tolerances used to build the scanner.

Computer-aided field editing in DHS: the Turkey experiment.

PubMed

1995-01-01

A study comparing field editing using a Notebook computer, computer-aided field editing (CAFE), with that done manually in the standard manner, during the 1993 Demographic and Health Survey (DHS) in Turkey, demonstrated that there was less missing data and a lower mean number of errors for teams using CAFE. 6 of 13 teams used CAFE in the Turkey experiment; the computers were equipped with Integrated System for Survey Analysis (ISSA) software for editing the DHS questionnaires. The CAFE teams completed 2466 out of 8619 household questionnaires and 1886 out of 6649 individual questionnaires. The CAFE team editor entered data into the computer and marked any detected errors on the questionnaire; the errors were then corrected by the editor, in the field, based on other responses in the questionnaire, or on corrections made by the interviewer to which the questionnaire was returned. Errors in questionnaires edited manually are not identified until they are sent to the survey office for data processing, when it is too late to ask for clarification from respondents. There was one area where the error rate was higher for CAFE teams; the CAFE editors paid less attention to errors presented as warnings only.

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…

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.

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.

A handheld computer-aided diagnosis system and simulated analysis

NASA Astrophysics Data System (ADS)

Su, Mingjian; Zhang, Xuejun; Liu, Brent; Su, Kening; Louie, Ryan

2016-03-01

This paper describes a Computer Aided Diagnosis (CAD) system based on cellphone and distributed cluster. One of the bottlenecks in building a CAD system for clinical practice is the storage and process of mass pathology samples freely among different devices, and normal pattern matching algorithm on large scale image set is very time consuming. Distributed computation on cluster has demonstrated the ability to relieve this bottleneck. We develop a system enabling the user to compare the mass image to a dataset with feature table by sending datasets to Generic Data Handler Module in Hadoop, where the pattern recognition is undertaken for the detection of skin diseases. A single and combination retrieval algorithm to data pipeline base on Map Reduce framework is used in our system in order to make optimal choice between recognition accuracy and system cost. The profile of lesion area is drawn by doctors manually on the screen, and then uploads this pattern to the server. In our evaluation experiment, an accuracy of 75% diagnosis hit rate is obtained by testing 100 patients with skin illness. Our system has the potential help in building a novel medical image dataset by collecting large amounts of gold standard during medical diagnosis. Once the project is online, the participants are free to join and eventually an abundant sample dataset will soon be gathered enough for learning. These results demonstrate our technology is very promising and expected to be used in clinical practice.

Accuracy evaluation of metal copings fabricated by computer-aided milling and direct metal laser sintering systems

PubMed Central

Lee, Wan-Sun; Kim, Woong-Chul

2015-01-01

PURPOSE To assess the marginal and internal gaps of the copings fabricated by computer-aided milling and direct metal laser sintering (DMLS) systems in comparison to casting method. MATERIALS AND METHODS Ten metal copings were fabricated by casting, computer-aided milling, and DMLS. Seven mesiodistal and labiolingual positions were then measured, and each of these were divided into the categories; marginal gap (MG), cervical gap (CG), axial wall at internal gap (AG), and incisal edge at internal gap (IG). Evaluation was performed by a silicone replica technique. A digital microscope was used for measurement of silicone layer. Statistical analyses included one-way and repeated measure ANOVA to test the difference between the fabrication methods and categories of measured points (α=.05), respectively. RESULTS The mean gap differed significantly with fabrication methods (P<.001). Casting produced the narrowest gap in each of the four measured positions, whereas CG, AG, and IG proved narrower in computer-aided milling than in DMLS. Thus, with the exception of MG, all positions exhibited a significant difference between computer-aided milling and DMLS (P<.05). CONCLUSION Although the gap was found to vary with fabrication methods, the marginal and internal gaps of the copings fabricated by computer-aided milling and DMLS fell within the range of clinical acceptance (<120 µm). However, the statistically significant difference to conventional casting indicates that the gaps in computer-aided milling and DMLS fabricated restorations still need to be further reduced. PMID:25932310

Accuracy evaluation of metal copings fabricated by computer-aided milling and direct metal laser sintering systems.

PubMed

Park, Jong-Kyoung; Lee, Wan-Sun; Kim, Hae-Young; Kim, Woong-Chul; Kim, Ji-Hwan

2015-04-01

To assess the marginal and internal gaps of the copings fabricated by computer-aided milling and direct metal laser sintering (DMLS) systems in comparison to casting method. Ten metal copings were fabricated by casting, computer-aided milling, and DMLS. Seven mesiodistal and labiolingual positions were then measured, and each of these were divided into the categories; marginal gap (MG), cervical gap (CG), axial wall at internal gap (AG), and incisal edge at internal gap (IG). Evaluation was performed by a silicone replica technique. A digital microscope was used for measurement of silicone layer. Statistical analyses included one-way and repeated measure ANOVA to test the difference between the fabrication methods and categories of measured points (α=.05), respectively. The mean gap differed significantly with fabrication methods (P<.001). Casting produced the narrowest gap in each of the four measured positions, whereas CG, AG, and IG proved narrower in computer-aided milling than in DMLS. Thus, with the exception of MG, all positions exhibited a significant difference between computer-aided milling and DMLS (P<.05). Although the gap was found to vary with fabrication methods, the marginal and internal gaps of the copings fabricated by computer-aided milling and DMLS fell within the range of clinical acceptance (<120 µm). However, the statistically significant difference to conventional casting indicates that the gaps in computer-aided milling and DMLS fabricated restorations still need to be further reduced.

Computer-aided detection of acute pulmonary embolism with 64-slice multi-detector row computed tomography: impact of the scanning conditions and overall image quality in the detection of peripheral clots.

PubMed

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.

Simplified computer-aided detection scheme of microcalcification clusters in digital breast tomosynthesis images.

PubMed

Ji-Wook Jeong; Seung-Hoon Chae; Eun Young Chae; Hak Hee Kim; Young Wook Choi; Sooyeul Lee

2016-08-01

A computer-aided detection (CADe) algorithm for clustered microcalcifications (MCs) in reconstructed digital breast tomosynthesis (DBT) images is suggested. The MC-like objects were enhanced by a Hessian-based 3D calcification response function, and a signal-to-noise ratio (SNR) enhanced image was also generated to screen the MC clustering seed objects. A connected component segmentation method was used to detect the cluster seed objects, which were considered as potential clustering centers of MCs. Bounding cubes for the accepted clustering seed candidate were generated and the overlapping cubes were combined and examined. After the MC clustering and false-positive (FP) reduction step, the average number of FPs was estimated to be 0.87 per DBT volume with a sensitivity of 90.5%.

An Approach towards Ultrasound Kidney Cysts Detection using Vector Graphic Image Analysis

NASA Astrophysics Data System (ADS)

Mahmud, Wan Mahani Hafizah Wan; Supriyanto, Eko

2017-08-01

This study develops new approach towards detection of kidney ultrasound image for both with single cyst as well as multiple cysts. 50 single cyst images and 25 multiple cysts images were used to test the developed algorithm. Steps involved in developing this algorithm were vector graphic image formation and analysis, thresholding, binarization, filtering as well as roundness test. Performance evaluation to 50 single cyst images gave accuracy of 92%, while for multiple cysts images, the accuracy was about 86.89% when tested to 25 multiple cysts images. This developed algorithm may be used in developing a computerized system such as computer aided diagnosis system to help medical experts in diagnosis of kidney cysts.

Computer-aided system for diabetes care in Berlin, G.D.R.

PubMed

Thoelke, H; Meusel, K; Ratzmann, K P

1990-01-01

In the Centre of Diabetes and Metabolic Disorders of Berlin, G.D.R., a computer-aided care system has been used since 1974, aiming at relieving physicians and medical staff from routine tasks and rendering possible epidemiological research on an unselected diabetes population of a defined area. The basis of the system is the data bank on diabetics (DB), where at present data from approximately 55,000 patients are stored. DB is used as a diabetes register of Berlin. On the basis of standardised criteria of diagnosis and therapy of diabetes mellitus in our dispensary care system, DB facilitates representative epidemiological analyses of the diabetic population, e.g. prevalence, incidence, duration of diabetes, and modes of treatment. The availability of general data on the population or the selection of specified groups of patients serves the management of the care system. Also, it supports the computer-aided recall of type II diabetics, treated either with diet alone or with diet and oral drugs. In this way, the standardised evaluation of treatment strategies in large populations of diabetics is possible on the basis of uniform metabolic criteria (blood glucose plus urinary glucose). The system consists of a main computer in the data processing unit and of personal computers in the diabetes centre which can be used either individually or as terminals to the main computer. During 14 years of experience, the computer-aided out-patient care of type II diabetics has proved efficient in a big-city area with a large population.

Computer-aided detection of pulmonary embolism at CT pulmonary angiography: can it improve performance of inexperienced readers?

PubMed

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.

Care 3 phase 2 report, maintenance manual

NASA Technical Reports Server (NTRS)

Bryant, L. A.; Stiffler, J. J.

1982-01-01

CARE 3 (Computer-Aided Reliability Estimation, version three) is a computer program designed to help estimate the reliability of complex, redundant systems. Although the program can model a wide variety of redundant structures, it was developed specifically for fault-tolerant avionics systems--systems distinguished by the need for extremely reliable performance since a system failure could well result in the loss of human life. It substantially generalizes the class of redundant configurations that could be accommodated, and includes a coverage model to determine the various coverage probabilities as a function of the applicable fault recovery mechanisms (detection delay, diagnostic scheduling interval, isolation and recovery delay, etc.). CARE 3 further generalizes the class of system structures that can be modeled and greatly expands the coverage model to take into account such effects as intermittent and transient faults, latent faults, error propagation, etc.

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.

[A computer-aided image diagnosis and study system].

PubMed

Li, Zhangyong; Xie, Zhengxiang

2004-08-01

The revolution in information processing, particularly the digitizing of medicine, has changed the medical study, work and management. This paper reports a method to design a system for computer-aided image diagnosis and study. Combined with some good idea of graph-text system and picture archives communicate system (PACS), the system was realized and used for "prescription through computer", "managing images" and "reading images under computer and helping the diagnosis". Also typical examples were constructed in a database and used to teach the beginners. The system was developed by the visual developing tools based on object oriented programming (OOP) and was carried into operation on the Windows 9X platform. The system possesses friendly man-machine interface.

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,…

A Computer-Aided Diagnosis System for Breast Cancer Combining Mammography and Proteomics

DTIC Science & Technology

2007-05-01

findings in both Data sets C and M. The likelihood ratio is the probability of the features un- der the malignant case divided by the probability of...likelihood ratio value as a classification decision variable, the probabilities of detection and false alarm are calculated as follows: Pdfusion...lowered the fused classifier’s performance to near chance levels. A genetic algorithm searched over the likelihood- ratio thresh- old values for each

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.

Deep convolutional neural network for the automated detection and diagnosis of seizure using EEG signals.

PubMed

Acharya, U Rajendra; Oh, Shu Lih; Hagiwara, Yuki; Tan, Jen Hong; Adeli, Hojjat

2017-09-27

An encephalogram (EEG) is a commonly used ancillary test to aide in the diagnosis of epilepsy. The EEG signal contains information about the electrical activity of the brain. Traditionally, neurologists employ direct visual inspection to identify epileptiform abnormalities. This technique can be time-consuming, limited by technical artifact, provides variable results secondary to reader expertise level, and is limited in identifying abnormalities. Therefore, it is essential to develop a computer-aided diagnosis (CAD) system to automatically distinguish the class of these EEG signals using machine learning techniques. This is the first study to employ the convolutional neural network (CNN) for analysis of EEG signals. In this work, a 13-layer deep convolutional neural network (CNN) algorithm is implemented to detect normal, preictal, and seizure classes. The proposed technique achieved an accuracy, specificity, and sensitivity of 88.67%, 90.00% and 95.00%, respectively. Copyright © 2017 Elsevier Ltd. All rights reserved.

Minnesota Computer Aided Library System (MCALS); University of Minnesota Subsystem Cost/Benefits Analysis.

ERIC Educational Resources Information Center

Lourey, Eugene D., Comp.

The Minnesota Computer Aided Library System (MCALS) provides a basis of unification for library service program development in Minnesota for eventual linkage to the national information network. A prototype plan for communications functions is illustrated. A cost/benefits analysis was made to show the cost/effectiveness potential for MCALS. System…

Performance Measures in Courses Using Computer-Aided Personalized System of Instruction

ERIC Educational Resources Information Center

Springer, C. R.; Pear, J. J.

2008-01-01

Archived data from four courses taught with computer-aided personalized system of instruction (CAPSI)--an online, self-paced, instructional program--were used to explore the relationship between objectively rescored final exam grades, peer reviewing, and progress rate--i.e., the rate at which students completed unit tests. There was a strong…

CAD/CAM complete dentures: a review of two commercial fabrication systems.

PubMed

Kattadiyil, Mathew T; Goodacre, Charles J; Baba, Nadim Z

2013-06-01

The use of computer-aided design and computer-aided manufacturing (CAD/CAM) has become available for complete dentures through the AvaDent and Dentca systems. AvaDent uses laser scanning and computer technology. Teeth are arranged and bases formed using proprietary software.The bases are milled from prepolymerized pucks of resin. Dentca uses computer software to produce virtual maxillary and mandibular edentulous ridges, arrange the teeth and form bases. The dentures are fabricated using a conventional processing technique.

Year 2000 Computing Crisis: Significant Risks Remain to Department of Education's Student Financial Aid Systems. Testimony before the Subcommittee on Oversight and Investigations, Committee on Education and the Workforce, House of Representatives.

ERIC Educational Resources Information Center

Willemssen, Joel C.

This testimony discusses the risks faced by the U.S. Department of Education due to the year 2000 (Y2K) computing crisis, focusing on student financial aid systems, the actions the Department has taken in recent months to address these risks, and the key issues the Department must deal with if its computer systems are to be ready for the century…

Automatic system for computer program documentation

NASA Technical Reports Server (NTRS)

Simmons, D. B.; Elliott, R. W.; Arseven, S.; Colunga, D.

1972-01-01

Work done on a project to design an automatic system for computer program documentation aids was made to determine what existing programs could be used effectively to document computer programs. Results of the study are included in the form of an extensive bibliography and working papers on appropriate operating systems, text editors, program editors, data structures, standards, decision tables, flowchart systems, and proprietary documentation aids. The preliminary design for an automated documentation system is also included. An actual program has been documented in detail to demonstrate the types of output that can be produced by the proposed system.

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

Student Performance in Computer-Assisted Instruction in Programming.

ERIC Educational Resources Information Center

Friend, Jamesine E.; And Others

A computer-assisted instructional system to teach college students the computer language, AID (Algebraic Interpretive Dialogue), two control programs, and data collected by the two control programs are described. It was found that although first response errors were often those of AID syntax, such errors were easily corrected. Secondly, while…

Computer-Assisted Instruction: One Aid for Teachers of Reading.

ERIC Educational Resources Information Center

Rauch, Margaret; Samojeden, Elizabeth

Computer assisted instruction (CAI), an instructional system with direct interaction between the student and the computer, can be a valuable aid for presenting new concepts, for reinforcing of selective skills, and for individualizing instruction. The advantages CAI provides include self-paced learning, more efficient allocation of classroom time,…

Quantitative kinetic analysis of lung nodules by temporal subtraction technique in dynamic chest radiography with a flat panel detector

NASA Astrophysics Data System (ADS)

Tsuchiya, Yuichiro; Kodera, Yoshie; Tanaka, Rie; Sanada, Shigeru

2007-03-01

Early detection and treatment of lung cancer is one of the most effective means to reduce cancer mortality; chest X-ray radiography has been widely used as a screening examination or health checkup. The new examination method and the development of computer analysis system allow obtaining respiratory kinetics by the use of flat panel detector (FPD), which is the expanded method of chest X-ray radiography. Through such changes functional evaluation of respiratory kinetics in chest has become available. Its introduction into clinical practice is expected in the future. In this study, we developed the computer analysis algorithm for the purpose of detecting lung nodules and evaluating quantitative kinetics. Breathing chest radiograph obtained by modified FPD was converted into 4 static images drawing the feature, by sequential temporal subtraction processing, morphologic enhancement processing, kinetic visualization processing, and lung region detection processing, after the breath synchronization process utilizing the diaphragmatic analysis of the vector movement. The artificial neural network used to analyze the density patterns detected the true nodules by analyzing these static images, and drew their kinetic tracks. For the algorithm performance and the evaluation of clinical effectiveness with 7 normal patients and simulated nodules, both showed sufficient detecting capability and kinetic imaging function without statistically significant difference. Our technique can quantitatively evaluate the kinetic range of nodules, and is effective in detecting a nodule on a breathing chest radiograph. Moreover, the application of this technique is expected to extend computer-aided diagnosis systems and facilitate the development of an automatic planning system for radiation therapy.

A study on spatial decision support systems for HIV/AIDS prevention based on COM GIS technology

NASA Astrophysics Data System (ADS)

Yang, Kun; Luo, Huasong; Peng, Shungyun; Xu, Quanli

2007-06-01

Based on the deeply analysis of the current status and the existing problems of GIS technology applications in Epidemiology, this paper has proposed the method and process for establishing the spatial decision support systems of AIDS epidemic prevention by integrating the COM GIS, Spatial Database, GPS, Remote Sensing, and Communication technologies, as well as ASP and ActiveX software development technologies. One of the most important issues for constructing the spatial decision support systems of AIDS epidemic prevention is how to integrate the AIDS spreading models with GIS. The capabilities of GIS applications in the AIDS epidemic prevention have been described here in this paper firstly. Then some mature epidemic spreading models have also been discussed for extracting the computation parameters. Furthermore, a technical schema has been proposed for integrating the AIDS spreading models with GIS and relevant geospatial technologies, in which the GIS and model running platforms share a common spatial database and the computing results can be spatially visualized on Desktop or Web GIS clients. Finally, a complete solution for establishing the decision support systems of AIDS epidemic prevention has been offered in this paper based on the model integrating methods and ESRI COM GIS software packages. The general decision support systems are composed of data acquisition sub-systems, network communication sub-systems, model integrating sub-systems, AIDS epidemic information spatial database sub-systems, AIDS epidemic information querying and statistical analysis sub-systems, AIDS epidemic dynamic surveillance sub-systems, AIDS epidemic information spatial analysis and decision support sub-systems, as well as AIDS epidemic information publishing sub-systems based on Web GIS.

Micro and Mainframe Computer Models for Improved Planning in Awarding Financial Aid to Disadvantaged Students.

ERIC Educational Resources Information Center

Attinasi, Louis C., Jr.; Fenske, Robert H.

1988-01-01

Two computer models used at Arizona State University recognize the tendency of students from low-income and minority backgrounds to apply for assistance late in the funding cycle. They permit administrators to project the amount of aid needed by such students. The Financial Aid Computerized Tracking System is described. (Author/MLW)

Quality indexing with computer-aided lexicography

NASA Technical Reports Server (NTRS)

Buchan, Ronald L.

1992-01-01

Indexing with computers is a far cry from indexing with the first indexing tool, the manual card sorter. With the aid of computer-aided lexicography, both indexing and indexing tools can provide standardization, consistency, and accuracy, resulting in greater quality control than ever before. A brief survey of computer activity in indexing is presented with detailed illustrations from NASA activity. Applications from techniques mentioned, such as Retrospective Indexing (RI), can be made to many indexing systems. In addition to improving the quality of indexing with computers, the improved efficiency with which certain tasks can be done is demonstrated.

Multidisciplinary analysis of actively controlled large flexible spacecraft

NASA Technical Reports Server (NTRS)

Cooper, Paul A.; Young, John W.; Sutter, Thomas R.

1986-01-01

The control of Flexible Structures (COFS) program has supported the development of an analysis capability at the Langley Research Center called the Integrated Multidisciplinary Analysis Tool (IMAT) which provides an efficient data storage and transfer capability among commercial computer codes to aid in the dynamic analysis of actively controlled structures. IMAT is a system of computer programs which transfers Computer-Aided-Design (CAD) configurations, structural finite element models, material property and stress information, structural and rigid-body dynamic model information, and linear system matrices for control law formulation among various commercial applications programs through a common database. Although general in its formulation, IMAT was developed specifically to aid in the evaluation of the structures. A description of the IMAT system and results of an application of the system are given.

Design Aids for Real-Time Systems (DARTS)

NASA Technical Reports Server (NTRS)

Szulewski, P. A.

1982-01-01

Design-Aids for Real-Time Systems (DARTS) is a tool that assists in defining embedded computer systems through tree structured graphics, military standard documentation support, and various analyses including automated Software Science parameter counting and metrics calculation. These analyses provide both static and dynamic design quality feedback which can potentially aid in producing efficient, high quality software systems.

Early esophageal cancer detection using RF classifiers

NASA Astrophysics Data System (ADS)

Janse, Markus H. A.; van der Sommen, Fons; Zinger, Svitlana; Schoon, Erik J.; de With, Peter H. N.

2016-03-01

Esophageal cancer is one of the fastest rising forms of cancer in the Western world. Using High-Definition (HD) endoscopy, gastroenterology experts can identify esophageal cancer at an early stage. Recent research shows that early cancer can be found using a state-of-the-art computer-aided detection (CADe) system based on analyzing static HD endoscopic images. Our research aims at extending this system by applying Random Forest (RF) classification, which introduces a confidence measure for detected cancer regions. To visualize this data, we propose a novel automated annotation system, employing the unique characteristics of the previous confidence measure. This approach allows reliable modeling of multi-expert knowledge and provides essential data for real-time video processing, to enable future use of the system in a clinical setting. The performance of the CADe system is evaluated on a 39-patient dataset, containing 100 images annotated by 5 expert gastroenterologists. The proposed system reaches a precision of 75% and recall of 90%, thereby improving the state-of-the-art results by 11 and 6 percentage points, respectively.

A computer aided engineering tool for ECLS systems

NASA Technical Reports Server (NTRS)

Bangham, Michal E.; Reuter, James L.

1987-01-01

The Computer-Aided Systems Engineering and Analysis tool used by NASA for environmental control and life support system design studies is capable of simulating atmospheric revitalization systems, water recovery and management systems, and single-phase active thermal control systems. The designer/analysis interface used is graphics-based, and allows the designer to build a model by constructing a schematic of the system under consideration. Data management functions are performed, and the program is translated into a format that is compatible with the solution routines.

Incorporation of CAD/CAM Restoration Into Navy Dentistry

DTIC Science & Technology

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

Expanding Biosensing Abilities through Computer-Aided Design of Metabolic Pathways.

PubMed

Libis, Vincent; Delépine, Baudoin; Faulon, Jean-Loup

2016-10-21

Detection of chemical signals is critical for cells in nature as well as in synthetic biology, where they serve as inputs for designer circuits. Important progress has been made in the design of signal processing circuits triggering complex biological behaviors, but the range of small molecules recognized by sensors as inputs is limited. The ability to detect new molecules will increase the number of synthetic biology applications, but direct engineering of tailor-made sensors takes time. Here we describe a way to immediately expand the range of biologically detectable molecules by systematically designing metabolic pathways that transform nondetectable molecules into molecules for which sensors already exist. We leveraged computer-aided design to predict such sensing-enabling metabolic pathways, and we built several new whole-cell biosensors for molecules such as cocaine, parathion, hippuric acid, and nitroglycerin.

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.

Using Computer Graphics in the 90's.

ERIC Educational Resources Information Center

Towne, Violet A.

Computer-Aided Design, a hands-on program for public school teachers, was first offered in the summer of 1987 as an outgrowth of a 1986 robotics training program. Area technology teachers needed computer-aided design (CAD) training because of a New York State Education system transition from the industrial arts curriculum to a new curriculum in…

Noise studies of communication systems using the SYSTID computer aided analysis program

NASA Technical Reports Server (NTRS)

Tranter, W. H.; Dawson, C. T.

1973-01-01

SYSTID computer aided design is a simple program for simulating data systems and communication links. A trial of the efficiency of the method was carried out by simulating a linear analog communication system to determine its noise performance and by comparing the SYSTID result with the result arrived at by theoretical calculation. It is shown that the SYSTID program is readily applicable to the analysis of these types of systems.

Development of an autonomous video rendezvous and docking system, phase 2

NASA Technical Reports Server (NTRS)

Tietz, J. C.; Richardson, T. E.

1983-01-01

The critical elements of an autonomous video rendezvous and docking system were built and used successfully in a physical laboratory simulation. The laboratory system demonstrated that a small, inexpensive electronic package and a flight computer of modest size can analyze television images to derive guidance information for spacecraft. In the ultimate application, the system would use a docking aid consisting of three flashing lights mounted on a passive target spacecraft. Television imagery of the docking aid would be processed aboard an active chase vehicle to derive relative positions and attitudes of the two spacecraft. The demonstration system used scale models of the target spacecraft with working docking aids. A television camera mounted on a 6 degree of freedom (DOF) simulator provided imagery of the target to simulate observations from the chase vehicle. A hardware video processor extracted statistics from the imagery, from which a computer quickly computed position and attitude. Computer software known as a Kalman filter derived velocity information from position measurements.

Computer-aided mathematical analysis of probability of intercept for ground-based communication intercept system

NASA Astrophysics Data System (ADS)

Park, Sang Chul

1989-09-01

We develop a mathematical analysis model to calculate the probability of intercept (POI) for the ground-based communication intercept (COMINT) system. The POI is a measure of the effectiveness of the intercept system. We define the POI as the product of the probability of detection and the probability of coincidence. The probability of detection is a measure of the receiver's capability to detect a signal in the presence of noise. The probability of coincidence is the probability that an intercept system is available, actively listening in the proper frequency band, in the right direction and at the same time that the signal is received. We investigate the behavior of the POI with respect to the observation time, the separation distance, antenna elevations, the frequency of the signal, and the receiver bandwidths. We observe that the coincidence characteristic between the receiver scanning parameters and the signal parameters is the key factor to determine the time to obtain a given POI. This model can be used to find the optimal parameter combination to maximize the POI in a given scenario. We expand this model to a multiple system. This analysis is conducted on a personal computer to provide the portability. The model is also flexible and can be easily implemented under different situations.

Computer-aided detection of bladder masses in CT urography (CTU)

NASA Astrophysics Data System (ADS)

Cha, Kenny H.; Hadjiiski, Lubomir M.; Chan, Heang-Ping; Caoili, Elaine M.; Cohan, Richard H.; Weizer, Alon; Samala, Ravi K.

2017-03-01

We are developing a computer-aided detection system for bladder cancer in CT urography (CTU). We have previously developed methods for detection of bladder masses within the contrast-enhanced and the non-contrastenhanced regions of the bladder individually. In this study, we investigated methods for detection of bladder masses within the entire bladder. The bladder was segmented using our method that combined deep-learning convolutional neural network with level sets. The non-contrast-enhanced region was separated from the contrast-enhanced region with a maximum-intensity-projection-based method. The non-contrast region was smoothed and gray level threshold was applied to the contrast and non-contrast regions separately to extract the bladder wall and potential masses. The bladder wall was transformed into a straightened thickness profile, which was analyzed to identify lesion candidates in a prescreening step. The candidates were mapped back to the 3D CT volume and segmented using our auto-initialized cascaded level set (AI-CALS) segmentation method. Twenty-seven morphological features were extracted for each candidate. A data set of 57 patients with 71 biopsy-proven bladder lesions was used, which was split into independent training and test sets: 42 training cases with 52 lesions, and 15 test cases with 19 lesions. Using the training set, feature selection was performed and a linear discriminant (LDA) classifier was designed to merge the selected features for classification of bladder lesions and false positives. The trained classifier was evaluated with the test set. FROC analysis showed that the system achieved a sensitivity of 86.5% at 3.3 FPs/case for the training set, and 84.2% at 3.7 FPs/case for the test set.

A computer aided treatment event recognition system in radiation therapy.

PubMed

Xia, Junyi; Mart, Christopher; Bayouth, John

2014-01-01

To develop an automated system to safeguard radiation therapy treatments by analyzing electronic treatment records and reporting treatment events. CATERS (Computer Aided Treatment Event Recognition System) was developed to detect treatment events by retrieving and analyzing electronic treatment records. CATERS is designed to make the treatment monitoring process more efficient by automating the search of the electronic record for possible deviations from physician's intention, such as logical inconsistencies as well as aberrant treatment parameters (e.g., beam energy, dose, table position, prescription change, treatment overrides, etc). Over a 5 month period (July 2012-November 2012), physicists were assisted by the CATERS software in conducting normal weekly chart checks with the aims of (a) determining the relative frequency of particular events in the authors' clinic and (b) incorporating these checks into the CATERS. During this study period, 491 patients were treated at the University of Iowa Hospitals and Clinics for a total of 7692 fractions. All treatment records from the 5 month analysis period were evaluated using all the checks incorporated into CATERS after the training period. About 553 events were detected as being exceptions, although none of them had significant dosimetric impact on patient treatments. These events included every known event type that was discovered during the trial period. A frequency analysis of the events showed that the top three types of detected events were couch position override (3.2%), extra cone beam imaging (1.85%), and significant couch position deviation (1.31%). The significant couch deviation is defined as the number of treatments where couch vertical exceeded two times standard deviation of all couch verticals, or couch lateral/longitudinal exceeded three times standard deviation of all couch laterals and longitudinals. On average, the application takes about 1 s per patient when executed on either a desktop computer or a mobile device. CATERS offers an effective tool to detect and report treatment events. Automation and rapid processing enables electronic record interrogation daily, alerting the medical physicist of deviations potentially days prior to performing weekly check. The output of CATERS could also be utilized as an important input to failure mode and effects analysis.

Automated identification of retained surgical items in radiological images

NASA Astrophysics Data System (ADS)

Agam, Gady; Gan, Lin; Moric, Mario; Gluncic, Vicko

2015-03-01

Retained surgical items (RSIs) in patients is a major operating room (OR) patient safety concern. An RSI is any surgical tool, sponge, needle or other item inadvertently left in a patients body during the course of surgery. If left undetected, RSIs may lead to serious negative health consequences such as sepsis, internal bleeding, and even death. To help physicians efficiently and effectively detect RSIs, we are developing computer-aided detection (CADe) software for X-ray (XR) image analysis, utilizing large amounts of currently available image data to produce a clinically effective RSI detection system. Physician analysis of XRs for the purpose of RSI detection is a relatively lengthy process that may take up to 45 minutes to complete. It is also error prone due to the relatively low acuity of the human eye for RSIs in XR images. The system we are developing is based on computer vision and machine learning algorithms. We address the problem of low incidence by proposing synthesis algorithms. The CADe software we are developing may be integrated into a picture archiving and communication system (PACS), be implemented as a stand-alone software application, or be integrated into portable XR machine software through application programming interfaces. Preliminary experimental results on actual XR images demonstrate the effectiveness of the proposed approach.

Programming Design Guide for Computer Implementation of Job Aid for Selecting Instructional Setting. Final Report.

ERIC Educational Resources Information Center

Schulz, Russel E.; And Others

This Programming Design Guide (PDG) was developed to permit the offline Job Aid for Selecting Instructional Setting, which is one of 13 job aids presently available for use with the Instructional Systems Development (ISD) model, to be available in an inquiry-type, online version. It is intended to provide computer programmers with all of the…

Topics in programmable automation. [for materials handling, inspection, and assembly

NASA Technical Reports Server (NTRS)

Rosen, C. A.

1975-01-01

Topics explored in the development of integrated programmable automation systems include: numerically controlled and computer controlled machining; machine intelligence and the emulation of human-like capabilities; large scale semiconductor integration technology applications; and sensor technology for asynchronous local computation without burdening the executive minicomputer which controls the whole system. The role and development of training aids, and the potential application of these aids to augmented teleoperator systems are discussed.

A System Engineering Study and Concept Development for a Humanitarian Aid and Disaster Relief Operations Management Platform

DTIC Science & Technology

2016-09-01

and network. The computing and network hardware are identified and include routers, servers, firewalls, laptops , backup hard drives, smart phones...deployable hardware units will be necessary. This includes the use of ruggedized laptops and desktop computers , a projector system, communications system...ENGINEERING STUDY AND CONCEPT DEVELOPMENT FOR A HUMANITARIAN AID AND DISASTER RELIEF OPERATIONS MANAGEMENT PLATFORM by Julie A. Reed September

Denver RTD's computer aided dispatch/automatic vehicle location system : the human factors consequences

DOT National Transportation Integrated Search

1999-09-01

This report documents what happened to employees' work procedures when their employer when their employer installed Computer Aided Disptach/Automatic Vehicle Locator (CAD/AVL) technology to provide real-time surveillance of vehicles and to upgrade ra...

A Computer-Aided Diagnosis System for Breast Cancer Combining Digital Mammography and Genomics

DTIC Science & Technology

2006-05-01

Huang, "Breast cancer diagnosis using self-organizing map for sonography." Ultrasound Med. Biol. 26, 405 (2000). 20 K. Horsch, M.L. Giger, L.A. Venta ...L.A. Venta , "Performance of computer-aided diagnosis in the interpretation of lesions on breast sonography." Acad Radiol 11, 272 (2004). 22 W. Chen...418. 27. Horsch K, Giger ML, Vyborny CJ, Venta LA. Performance of computer-aided diagnosis in the interpretation of lesions on breast sonography

A computer-aided design system geared toward conceptual design in a research environment. [for hypersonic vehicles

NASA Technical Reports Server (NTRS)

STACK S. H.

1981-01-01

A computer-aided design system has recently been developed specifically for the small research group environment. The system is implemented on a Prime 400 minicomputer linked with a CDC 6600 computer. The goal was to assign the minicomputer specific tasks, such as data input and graphics, thereby reserving the large mainframe computer for time-consuming analysis codes. The basic structure of the design system consists of GEMPAK, a computer code that generates detailed configuration geometry from a minimum of input; interface programs that reformat GEMPAK geometry for input to the analysis codes; and utility programs that simplify computer access and data interpretation. The working system has had a large positive impact on the quantity and quality of research performed by the originating group. This paper describes the system, the major factors that contributed to its particular form, and presents examples of its application.

Computer-aided diagnosis of liver tumors on computed tomography images.

PubMed

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.

Psychological Issues in Online Adaptive Task Allocation

NASA Technical Reports Server (NTRS)

Morris, N. M.; Rouse, W. B.; Ward, S. L.; Frey, P. R.

1984-01-01

Adaptive aiding is an idea that offers potential for improvement over many current approaches to aiding in human-computer systems. The expected return of tailoring the system to fit the user could be in the form of improved system performance and/or increased user satisfaction. Issues such as the manner in which information is shared between human and computer, the appropriate division of labor between them, and the level of autonomy of the aid are explored. A simulated visual search task was developed. Subjects are required to identify targets in a moving display while performing a compensatory sub-critical tracking task. By manipulating characteristics of the situation such as imposed task-related workload and effort required to communicate with the computer, it is possible to create conditions in which interaction with the computer would be more or less desirable. The results of preliminary research using this experimental scenario are presented, and future directions for this research effort are discussed.

Soil, water, and vegetation conditions in south Texas

NASA Technical Reports Server (NTRS)

Wiegand, C. L.; Gausman, H. W.; Leamer, R. W.; Richardson, A. J.; Everitt, J. H.; Gerbermann, A. H. (Principal Investigator)

1976-01-01

The author has identified the following significant results. Software development for a computer-aided crop and soil survey system is nearing completion. Computer-aided variety classification accuracies using LANDSAT-1 MSS data for a 600 hectare citrus farm were 83% for Redblush grapefruit and 91% for oranges. These accuracies indicate that there is good potential for computer-aided inventories of grapefruit and orange citrus orchards with LANDSAT-type MSS data. Mean digital values of clouds differed statistically from those for crop, soil, and water entities, and those for cloud shadows were enough lower than sunlit crop and soil to be distinguishable. The standard errors of estimate for the calibration of computer compatible tape coordinate system (pixel and record) to earth coordinate system (longitude and latitude) for 6 LANDSAT scenes ranged from 0.72 to 1.50 pixels and from 0.58 to 1.75 records.

Deep-reasoning fault diagnosis - An aid and a model

NASA Technical Reports Server (NTRS)

Yoon, Wan Chul; Hammer, John M.

1988-01-01

The design and evaluation are presented for the knowledge-based assistance of a human operator who must diagnose a novel fault in a dynamic, physical system. A computer aid based on a qualitative model of the system was built to help the operators overcome some of their cognitive limitations. This aid differs from most expert systems in that it operates at several levels of interaction that are believed to be more suitable for deep reasoning. Four aiding approaches, each of which provided unique information to the operator, were evaluated. The aiding features were designed to help the human's casual reasoning about the system in predicting normal system behavior (N aiding), integrating observations into actual system behavior (O aiding), finding discrepancies between the two (O-N aiding), or finding discrepancies between observed behavior and hypothetical behavior (O-HN aiding). Human diagnostic performance was found to improve by almost a factor of two with O aiding and O-N aiding.

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.

Observer training for computer-aided detection of pulmonary nodules in chest radiography.

PubMed

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.

A Computer-Aided Telephone System to Enable Five Persons with Alzheimer's Disease to Make Phone Calls Independently

ERIC Educational Resources Information Center

Perilli, Viviana; Lancioni, Giulio E.; Laporta, Dominga; Paparella, Adele; Caffo, Alessandro O.; Singh, Nirbhay N.; O'Reilly, Mark F.; Sigafoos, Jeff; Oliva, Doretta

2013-01-01

This study extended the assessment of a computer-aided telephone system to enable five patients with a diagnosis of Alzheimer's disease to make phone calls independently. The patients were divided into two groups and exposed to intervention according to a non-concurrent multiple baseline design across groups. All patients started with baseline in…

Data Management Standards in Computer-aided Acquisition and Logistic Support (CALS)

NASA Technical Reports Server (NTRS)

Jefferson, David K.

1990-01-01

Viewgraphs and discussion on data management standards in computer-aided acquisition and logistic support (CALS) are presented. CALS is intended to reduce cost, increase quality, and improve timeliness of weapon system acquisition and support by greatly improving the flow of technical information. The phase 2 standards, industrial environment, are discussed. The information resource dictionary system (IRDS) is described.

Investigation of air transportation technology at Princeton University, 1990-1991

NASA Technical Reports Server (NTRS)

Stengel, Robert F.

1991-01-01

The Air Transportation Technology Program at Princeton University is a program that emphasizes graduate and undergraduate student research. The program proceeded along six avenues during the past year: microburst hazards to aircraft, intelligent failure tolerant control, computer-aided heuristics for piloted flight, stochastic robustness of flight control systems, neural networks for flight control, and computer-aided control system design.

Computer-Aided Air-Traffic Control In The Terminal Area

NASA Technical Reports Server (NTRS)

Erzberger, Heinz

1995-01-01

Developmental computer-aided system for automated management and control of arrival traffic at large airport includes three integrated subsystems. One subsystem, called Traffic Management Advisor, another subsystem, called Descent Advisor, and third subsystem, called Final Approach Spacing Tool. Data base that includes current wind measurements and mathematical models of performances of types of aircraft contributes to effective operation of system.

Implementation and Evaluation of Computer-Aided Mandarin Phonemes Training System for Hearing-Impaired Students

ERIC Educational Resources Information Center

Yang, Hui-Jen; Lay, Yun-Long

2005-01-01

A computer-aided Mandarin phonemes training (CAMPT) system was developed and evaluated for training hearing-impaired students in their pronunciation of Mandarin phonemes. Deaf or hearing-impaired people have difficulty hearing their own voice, hence most of them cannot learn how to speak. Phonemes are the basis for learning to read and speak in…

Two Adults with Multiple Disabilities Use a Computer-Aided Telephone System to Make Phone Calls Independently

ERIC Educational Resources Information Center

Lancioni, Giulio E.; O'Reilly, Mark F.; Singh, Nirbhay N.; Sigafoos, Jeff; Oliva, Doretta; Alberti, Gloria; Lang, Russell

2011-01-01

This study extended the assessment of a newly developed computer-aided telephone system with two participants (adults) who presented with blindness or severe visual impairment and motor or motor and intellectual disabilities. For each participant, the study was carried out according to an ABAB design, in which the A represented baseline phases and…

Analytical Procedures for Testability.

DTIC Science & Technology

1983-01-01

Beat Internal Classifications", AD: A018516. "A System of Computer Aided Diagnosis with Blood Serum Chemistry Tests and Bayesian Statistics", AD: 786284...6 LIST OF TALS .. 1. Truth Table ......................................... 49 2. Covering Problem .............................. 93 3. Primary and...quential classification procedure in a coronary care ward is evaluated. In the toxicology field "A System of Computer Aided Diagnosis with Blood Serum

A Language Translator for a Computer Aided Rapid Prototyping System.

DTIC Science & Technology

1988-03-01

PROBLEM ................... S B. THE TRADITIONAL "WATERFALL LIFE CYCLE" .. ............... 14 C. RAPID PROTOTYPING...feature of everyday life for almost the entire industrialized world. Few governments or businesses function without the aid of computer systems. Com...engineering. B. TIE TRADITIONAL "WATERFALL LIFE CYCLE" I. Characteristics The traditional method of software engineering is the "waterfall life cycle

Space Spurred Computer Graphics

NASA Technical Reports Server (NTRS)

1983-01-01

Dicomed Corporation was asked by NASA in the early 1970s to develop processing capabilities for recording images sent from Mars by Viking spacecraft. The company produced a film recorder which increased the intensity levels and the capability for color recording. This development led to a strong technology base resulting in sophisticated computer graphics equipment. Dicomed systems are used to record CAD (computer aided design) and CAM (computer aided manufacturing) equipment, to update maps and produce computer generated animation.

77 FR 21574 - Prospective Grant of Exclusive License: Method for Segmenting Medical Images and Detecting...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-04-10

... methods help solve imaging problems such as image ``leakage,'' which causes distortion, overloads datasets... enhance detection. This is helpful to identify harmful features such as precancerous polyps or other anomalies. The field of use may be limited to ``computer aided detection in colonography.'' The prospective...

Research on computer aided testing of pilot response to critical in-flight events

NASA Technical Reports Server (NTRS)

Giffin, W. C.; Rockwell, T. H.; Smith, P. J.

1984-01-01

Experiments on pilot decision making are described. The development of models of pilot decision making in critical in flight events (CIFE) are emphasized. The following tests are reported on the development of: (1) a frame system representation describing how pilots use their knowledge in a fault diagnosis task; (2) assessment of script norms, distance measures, and Markov models developed from computer aided testing (CAT) data; and (3) performance ranking of subject data. It is demonstrated that interactive computer aided testing either by touch CRT's or personal computers is a useful research and training device for measuring pilot information management in diagnosing system failures in simulated flight situations. Performance is dictated by knowledge of aircraft sybsystems, initial pilot structuring of the failure symptoms and efficient testing of plausible causal hypotheses.

Do pre-trained deep learning models improve computer-aided classification of digital mammograms?

NASA Astrophysics Data System (ADS)

Aboutalib, Sarah S.; Mohamed, Aly A.; Zuley, Margarita L.; Berg, Wendie A.; Luo, Yahong; Wu, Shandong

2018-02-01

Digital mammography screening is an important exam for the early detection of breast cancer and reduction in mortality. False positives leading to high recall rates, however, results in unnecessary negative consequences to patients and health care systems. In order to better aid radiologists, computer-aided tools can be utilized to improve distinction between image classifications and thus potentially reduce false recalls. The emergence of deep learning has shown promising results in the area of biomedical imaging data analysis. This study aimed to investigate deep learning and transfer learning methods that can improve digital mammography classification performance. In particular, we evaluated the effect of pre-training deep learning models with other imaging datasets in order to boost classification performance on a digital mammography dataset. Two types of datasets were used for pre-training: (1) a digitized film mammography dataset, and (2) a very large non-medical imaging dataset. By using either of these datasets to pre-train the network initially, and then fine-tuning with the digital mammography dataset, we found an increase in overall classification performance in comparison to a model without pre-training, with the very large non-medical dataset performing the best in improving the classification accuracy.

CAGI: Computer Aided Grid Interface. A work in progress

NASA Technical Reports Server (NTRS)

Soni, Bharat K.; Yu, Tzu-Yi; Vaughn, David

1992-01-01

Progress realized in the development of a Computer Aided Grid Interface (CAGI) software system in integrating CAD/CAM geometric system output and/or Interactive Graphics Exchange Standard (IGES) files, geometry manipulations associated with grid generation, and robust grid generation methodologies is presented. CAGI is being developed in a modular fashion and will offer fast, efficient and economical response to geometry/grid preparation, allowing the ability to upgrade basic geometry in a step-by-step fashion interactively and under permanent visual control along with minimizing the differences between the actual hardware surface descriptions and corresponding numerical analog. The computer code GENIE is used as a basis. The Non-Uniform Rational B-Splines (NURBS) representation of sculptured surfaces is utilized for surface grid redistribution. The computer aided analysis system, PATRAN, is adapted as a CAD/CAM system. The progress realized in NURBS surface grid generation, the development of IGES transformer, and geometry adaption using PATRAN will be presented along with their applicability to grid generation associated with rocket propulsion applications.

Computer Aided Dosimetry and Verification of Exposure to Radiation

DTIC Science & Technology

2002-06-01

Event matrix 2. Hematopoietic * Absolute blood counts * Relative blood counts 3. Dosimetry * TLD * EPDQuantitative * Radiation survey * Whole body...EI1 Defence Research and Recherche et developpement Development Canada pour la d6fense Canada DEFENCE •mI•DEFENSE Computer Aided Dosimetry and...Aided Dosimetry and Verification of Exposure to Radiation Edward Waller SAIC Canada Robert Z Stodilka Radiation Effects Group, Space Systems and

[Medical computer-aided detection method based on deep learning].

PubMed

Tao, Pan; Fu, Zhongliang; Zhu, Kai; Wang, Lili

2018-03-01

This paper performs a comprehensive study on the computer-aided detection for the medical diagnosis with deep learning. Based on the region convolution neural network and the prior knowledge of target, this algorithm uses the region proposal network, the region of interest pooling strategy, introduces the multi-task loss function: classification loss, bounding box localization loss and object rotation loss, and optimizes it by end-to-end. For medical image it locates the target automatically, and provides the localization result for the next stage task of segmentation. For the detection of left ventricular in echocardiography, proposed additional landmarks such as mitral annulus, endocardial pad and apical position, were used to estimate the left ventricular posture effectively. In order to verify the robustness and effectiveness of the algorithm, the experimental data of ultrasonic and nuclear magnetic resonance images are selected. Experimental results show that the algorithm is fast, accurate and effective.

A rule based computer aided design system

NASA Technical Reports Server (NTRS)

Premack, T.

1986-01-01

A Computer Aided Design (CAD) system is presented which supports the iterative process of design, the dimensional continuity between mating parts, and the hierarchical structure of the parts in their assembled configuration. Prolog, an interactive logic programming language, is used to represent and interpret the data base. The solid geometry representing the parts is defined in parameterized form using the swept volume method. The system is demonstrated with a design of a spring piston.

The Development of a Design Database for the Computer Aided Prototyping System

DTIC Science & Technology

1991-09-01

COMPUTER AIDED PROTOTYPING SYSTEM by Andrew Patrick Dwyer Captain, United States Marine Corps B.S., Juniata College, 1980 M.B.A. Webster University...Postgraduate School, Monterey, California, May 1990. Page-Jones, M., The Practical guide to Structured Systems Design, Yourdon Press, 1980 . Rumbaugh, J. and...United States Laboratory Command Army Research Office Attn: Dr. David Hislop P. 0. Box 12211 Research Triangle Park, NC 27709-2211 50. George Mason

Prosthetically guided maxillofacial surgery: evaluation of the accuracy of a surgical guide and custom-made bone plate in oncology patients after mandibular reconstruction.

PubMed

Mazzoni, Simona; Marchetti, Claudio; Sgarzani, Rossella; Cipriani, Riccardo; Scotti, Roberto; Ciocca, Leonardo

2013-06-01

The aim of the present study was to evaluate the accuracy of prosthetically guided maxillofacial surgery in reconstructing the mandible with a free vascularized flap using custom-made bone plates and a surgical guide to cut the mandible and fibula. The surgical protocol was applied in a study group of seven consecutive mandibular-reconstructed patients who were compared with a control group treated using the standard preplating technique on stereolithographic models (indirect computer-aided design/computer-aided manufacturing method). The precision of both surgical techniques (prosthetically guided maxillofacial surgery and indirect computer-aided design/computer-aided manufacturing procedure) was evaluated by comparing preoperative and postoperative computed tomographic data and assessment of specific landmarks. With regard to midline deviation, no significant difference was documented between the test and control groups. With regard to mandibular angle shift, only one left angle shift on the lateral plane showed a statistically significant difference between the groups. With regard to angular deviation of the body axis, the data showed a significant difference in the arch deviation. All patients in the control group registered greater than 8 degrees of deviation, determining a facial contracture of the external profile at the lower margin of the mandible. With regard to condylar position, the postoperative condylar position was better in the test group than in the control group, although no significant difference was detected. The new protocol for mandibular reconstruction using computer-aided design/computer-aided manufacturing prosthetically guided maxillofacial surgery to construct custom-made guides and plates may represent a viable method of reproducing the patient's anatomical contour, giving the surgeon better procedural control and reducing procedure time. Therapeutic, III.

The Power of Computer-aided Tomography to Investigate Marine Benthic Communities

EPA Science Inventory

Utilization of Computer-aided-Tomography (CT) technology is a powerful tool to investigate benthic communities in aquatic systems. In this presentation, we will attempt to summarize our 15 years of experience in developing specific CT methods and applications to marine benthic co...

Fixed-point Design of the Lattice-reduction-aided Iterative Detection and Decoding Receiver for Coded MIMO Systems

DTIC Science & Technology

2011-01-01

reliability, e.g., Turbo Codes [2] and Low Density Parity Check ( LDPC ) codes [3]. The challenge to apply both MIMO and ECC into wireless systems is on...REPORT Fixed-point Design of theLattice-reduction-aided Iterative Detection andDecoding Receiver for Coded MIMO Systems 14. ABSTRACT 16. SECURITY...illustrates the performance of coded LR aided detectors. 1. REPORT DATE (DD-MM-YYYY) 4. TITLE AND SUBTITLE 13. SUPPLEMENTARY NOTES The views, opinions

Microwave processing of a dental ceramic used in computer-aided design/computer-aided manufacturing.

PubMed

Pendola, Martin; Saha, Subrata

2015-01-01

Because of their favorable mechanical properties and natural esthetics, ceramics are widely used in restorative dentistry. The conventional ceramic sintering process required for their use is usually slow, however, and the equipment has an elevated energy consumption. Sintering processes that use microwaves have several advantages compared to regular sintering: shorter processing times, lower energy consumption, and the capacity for volumetric heating. The objective of this study was to test the mechanical properties of a dental ceramic used in computer-aided design/computer-aided manufacturing (CAD/CAM) after the specimens were processed with microwave hybrid sintering. Density, hardness, and bending strength were measured. When ceramic specimens were sintered with microwaves, the processing times were reduced and protocols were simplified. Hardness was improved almost 20% compared to regular sintering, and flexural strength measurements suggested that specimens were approximately 50% stronger than specimens sintered in a conventional system. Microwave hybrid sintering may preserve or improve the mechanical properties of dental ceramics designed for CAD/CAM processing systems, reducing processing and waiting times.

Three-Dimensional Computer-Aided Detection of Microcalcification Clusters in Digital Breast Tomosynthesis.

PubMed

Jeong, Ji-Wook; Chae, Seung-Hoon; Chae, Eun Young; Kim, Hak Hee; Choi, Young-Wook; Lee, Sooyeul

2016-01-01

We propose computer-aided detection (CADe) algorithm for microcalcification (MC) clusters in reconstructed digital breast tomosynthesis (DBT) images. The algorithm consists of prescreening, MC detection, clustering, and false-positive (FP) reduction steps. The DBT images containing the MC-like objects were enhanced by a multiscale Hessian-based three-dimensional (3D) objectness response function and a connected-component segmentation method was applied to extract the cluster seed objects as potential clustering centers of MCs. Secondly, a signal-to-noise ratio (SNR) enhanced image was also generated to detect the individual MC candidates and prescreen the MC-like objects. Each cluster seed candidate was prescreened by counting neighboring individual MC candidates nearby the cluster seed object according to several microcalcification clustering criteria. As a second step, we introduced bounding boxes for the accepted seed candidate, clustered all the overlapping cubes, and examined. After the FP reduction step, the average number of FPs per case was estimated to be 2.47 per DBT volume with a sensitivity of 83.3%.

Hybrid tracking and control system for computer-aided retinal surgery

NASA Astrophysics Data System (ADS)

Ferguson, R. D.; Wright, Cameron H. G.; Rylander, Henry G., III; Welch, Ashley J.; Barrett, Steven F.

1996-05-01

We describe initial experimental results of a new hybrid digital and analog design for retinal tracking and laser beam control. Initial results demonstrate tracking rates which exceed the equivalent of 50 degrees per second in the eye, with automatic lesion pattern creation and robust loss of lock detection. Robotically assisted laser surgery to treat conditions such as diabetic retinopathy, macular degeneration, and retinal tears can now be realized under clinical conditions with requisite safety using standard video hardware and inexpensive optical components.

Computer-Aided Design of Low-Noise Microwave Circuits

NASA Astrophysics Data System (ADS)

Wedge, Scott William

1991-02-01

Devoid of most natural and manmade noise, microwave frequencies have detection sensitivities limited by internally generated receiver noise. Low-noise amplifiers are therefore critical components in radio astronomical antennas, communications links, radar systems, and even home satellite dishes. A general technique to accurately predict the noise performance of microwave circuits has been lacking. Current noise analysis methods have been limited to specific circuit topologies or neglect correlation, a strong effect in microwave devices. Presented here are generalized methods, developed for computer-aided design implementation, for the analysis of linear noisy microwave circuits comprised of arbitrarily interconnected components. Included are descriptions of efficient algorithms for the simultaneous analysis of noisy and deterministic circuit parameters based on a wave variable approach. The methods are therefore particularly suited to microwave and millimeter-wave circuits. Noise contributions from lossy passive components and active components with electronic noise are considered. Also presented is a new technique for the measurement of device noise characteristics that offers several advantages over current measurement methods.

IDEAS: A multidisciplinary computer-aided conceptual design system for spacecraft

NASA Technical Reports Server (NTRS)

Ferebee, M. J., Jr.

1984-01-01

During the conceptual development of advanced aerospace vehicles, many compromises must be considered to balance economy and performance of the total system. Subsystem tradeoffs may need to be made in order to satisfy system-sensitive attributes. Due to the increasingly complex nature of aerospace systems, these trade studies have become more difficult and time-consuming to complete and involve interactions of ever-larger numbers of subsystems, components, and performance parameters. The current advances of computer-aided synthesis, modeling and analysis techniques have greatly helped in the evaluation of competing design concepts. Langley Research Center's Space Systems Division is currently engaged in trade studies for a variety of systems which include advanced ground-launched space transportation systems, space-based orbital transfer vehicles, large space antenna concepts and space stations. The need for engineering analysis tools to aid in the rapid synthesis and evaluation of spacecraft has led to the development of the Interactive Design and Evaluation of Advanced Spacecraft (IDEAS) computer-aided design system. The ADEAS system has been used to perform trade studies of competing technologies and requirements in order to pinpoint possible beneficial areas for research and development. IDEAS is presented as a multidisciplinary tool for the analysis of advanced space systems. Capabilities range from model generation and structural and thermal analysis to subsystem synthesis and performance analysis.

Computer-aided-engineering system for modeling and analysis of ECLSS integration testing

NASA Technical Reports Server (NTRS)

Sepahban, Sonbol

1987-01-01

The accurate modeling and analysis of two-phase fluid networks found in environmental control and life support systems is presently undertaken by computer-aided engineering (CAE) techniques whose generalized fluid dynamics package can solve arbitrary flow networks. The CAE system for integrated test bed modeling and analysis will also furnish interfaces and subsystem/test-article mathematical models. Three-dimensional diagrams of the test bed are generated by the system after performing the requisite simulation and analysis.

Program Aids Design Of Fluid-Circulating Systems

NASA Technical Reports Server (NTRS)

Bacskay, Allen; Dalee, Robert

1992-01-01

Computer Aided Systems Engineering and Analysis (CASE/A) program is interactive software tool for trade study and analysis, designed to increase productivity during all phases of systems engineering. Graphics-based command-driven software package provides user-friendly computing environment in which engineer analyzes performance and interface characteristics of ECLS/ATC system. Useful during all phases of spacecraft-design program, from initial conceptual design trade studies to actual flight, including pre-flight prediction and in-flight analysis of anomalies. Written in FORTRAN 77.

Marking parts to aid robot vision

NASA Technical Reports Server (NTRS)

Bales, J. W.; Barker, L. K.

1981-01-01

The premarking of parts for subsequent identification by a robot vision system appears to be beneficial as an aid in the automation of certain tasks such as construction in space. A simple, color coded marking system is presented which allows a computer vision system to locate an object, calculate its orientation, and determine its identity. Such a system has the potential to operate accurately, and because the computer shape analysis problem has been simplified, it has the ability to operate in real time.

High School Students' Written Argumentation Qualities with Problem-Based Computer-Aided Material (PBCAM) Designed about Human Endocrine System

ERIC Educational Resources Information Center

Vekli, Gülsah Sezen; Çimer, Atilla

2017-01-01

This study investigated development of students' scientific argumentation levels in the applications made with Problem-Based Computer-Aided Material (PBCAM) designed about Human Endocrine System. The case study method was used: The study group was formed of 43 students in the 11th grade of the science high school in Rize. Human Endocrine System…

A Survey of CAD/CAM Technology Applications in the U.S. Shipbuilding Industry

DTIC Science & Technology

1984-01-01

operation for drafting. Computer Aided Engineering (CAE) analysis is used primarily to determine the validity of design characteristics and produc- tion...include time standard generation, sea trial analysis , and group Systems integration While no systems surveyed Aided Design (CAD) is the technology... analysis . is the largest problem involving software packages. are truly integrated, many are interfaced. Computer most interfaced category with links

A progress report on UNICOS misuse detection at Los Alamos

DOE Office of Scientific and Technical Information (OSTI.GOV)

Thompson, J.L.; Jackson, K.A.; Stallings, C.A.

An effective method for detecting computer misuse is the automatic monitoring and analysis of on-line user activity. During the past year, Los Alamos enhanced its Network Anomaly Detection and Intrusion Reporter (NADIR) to include analysis of user activity on Los Alamos` UNICOS Crays. In near real-time, NADIR compares user activity to historical profiles and tests activity against expert rules. The expert rules express Los Alamos` security policy and define improper or suspicious behavior. NADIR reports suspicious behavior to security auditors and provides tools to aid in follow-up investigations. This paper describes the implementation to date of the UNICOS component ofmore » NADIR, along with the operational experiences and future plans for the system.« less

Computer-Aided Transcription in the Courts. Executive Summary. National Center Publication No. R-0058.

ERIC Educational Resources Information Center

National Center for State Courts, Williamsburg, VA.

This report summarizes the findings of the Computer-Aided Transcription (CAT) Project, which conducted a 14-month study of the technology and use of computer systems for translating into English the shorthand notes taken by court reporters on stenotype machines. Included are the state of the art of CAT at the end of 1980 and anticipated future…

System for Computer Automated Typesetting (SCAT) of Computer Authored Texts.

ERIC Educational Resources Information Center

Keeler, F. Laurence

This description of the System for Automated Typesetting (SCAT), an automated system for typesetting text and inserting special graphic symbols in programmed instructional materials created by the computer aided authoring system AUTHOR, provides an outline of the design architecture of the system and an overview including the component…

Navigation-aid power systems

NASA Technical Reports Server (NTRS)

Goltz, G. L.; Kaiser, L. M.; Weiner, H.

1979-01-01

Design synthesis and performance analysis (DSPA) program package is collection of subroutines used for computation of design and performance characteristics of viable solar-array-charged battery powered system for flashing-lamp buoys employed as maritime aids to navigation.

Intelligent tutoring systems research in the training systems division: Space applications

NASA Technical Reports Server (NTRS)

Regian, J. Wesley

1988-01-01

Computer-Aided Instruction (CAI) is a mature technology used to teach students in a wide variety of domains. The introduction of Artificial Intelligence (AI) technology of the field of CAI has prompted research and development efforts in an area known as Intelligent Computer-Aided Instruction (ICAI). In some cases, ICAI has been touted as a revolutionary alternative to traditional CAI. With the advent of powerful, inexpensive school computers, ICAI is emerging as a potential rival to CAI. In contrast to this, one may conceive of Computer-Based Training (CBT) systems as lying along a continuum which runs from CAI to ICAI. Although the key difference between the two is intelligence, there is not commonly accepted definition of what constitutes an intelligent instructional system.

An Automatic Detection System of Lung Nodule Based on Multi-Group Patch-Based Deep Learning Network.

PubMed

Jiang, Hongyang; Ma, He; Qian, Wei; Gao, Mengdi; Li, Yan

2017-07-14

High-efficiency lung nodule detection dramatically contributes to the risk assessment of lung cancer. It is a significant and challenging task to quickly locate the exact positions of lung nodules. Extensive work has been done by researchers around this domain for approximately two decades. However, previous computer aided detection (CADe) schemes are mostly intricate and time-consuming since they may require more image processing modules, such as the computed tomography (CT) image transformation, the lung nodule segmentation and the feature extraction, to construct a whole CADe system. It is difficult for those schemes to process and analyze enormous data when the medical images continue to increase. Besides, some state of the art deep learning schemes may be strict in the standard of database. This study proposes an effective lung nodule detection scheme based on multi-group patches cut out from the lung images, which are enhanced by the Frangi filter. Through combining two groups of images, a four-channel convolution neural networks (CNN) model is designed to learn the knowledge of radiologists for detecting nodules of four levels. This CADe scheme can acquire the sensitivity of 80.06% with 4.7 false positives per scan and the sensitivity of 94% with 15.1 false positives per scan. The results demonstrate that the multi-group patch-based learning system is efficient to improve the performance of lung nodule detection and greatly reduce the false positives under a huge amount of image data.

1000-Case Reader Study of Radiologists' Performance in Interpretation of Automated Breast Volume Scanner Images with a Computer-Aided Detection System.

PubMed

Xu, Xiaojing; Bao, Lingyun; Tan, Yanjuan; Zhu, Luoxi; Kong, Fanlei; Wang, Wei

2018-05-28

The objective of our study was to assess, in a reader study, radiologists' performance in interpretation of automated breast volume scanner (ABVS) images with the aid of a computer-aided detection (CADe) system. Our study is a retrospective observer study with the purpose of investigating the effectiveness of using a CADe system as an aid for radiologists in interpretation of ABVS images. The multiple-reader, multiple-case study was designed to compare the diagnostic performance of radiologists with and without CADe. The study included 1000 cases selected from ABVS examinations in our institution in 2012. Among those cases were 206 malignant, 486 benign and 308 normal cases. The cancer cases were consecutive; the benign and normal cases were randomly selected. All malignant and benign cases were confirmed by biopsy or surgery, and normal cases were confirmed by 2-y follow-up. Reader performance was compared in terms of area under the receiver operating characteristic curve, sensitivity and specificity. Additionally, the reading time per case for each reader was recorded. Nine radiologists from our institution participated in the study. Three had more than 8 y of ultrasound experience and more than 4 y of ABVS experience (group A); 3 had more than 5 y of ultrasound experience (group B), and 3 had more than 1 y of ultrasound experience (group C). Both group B and group C had no ABVS experience. The CADe system used was the QVCAD System (QView Medical, Inc., Los Altos, CA, USA). It is designed to aid radiologists in searching for suspicious areas in ABVS images. CADe results are presented to the reader simultaneously with the ABVS images; that is, the radiologists read the ABVS images concurrently with the CADe results. The cases were randomly assigned for each reader into two equal-size groups, 1 and 2. Initially the readers read their group 1 cases with the aid of CADe and their group 2 cases without CADe. After a 1-mo washout period, they re-read their group 1 cases without CADe and their group 2 cases with CADe. The areas under the receiver operating characteristic curves of all readers were 0.784 for reading with CADe and 0.747 without CADe. Areas under the curves with and without CADe were 0.833 and 0.829 for group A, 0.757 and 0.696 for group B and 0.759 and 0.718 for group C. All differences in areas under the curve were statistically significant (p <0.05), except that for group A. The average reading time was 9.3% (p < < 0.05) faster with CADe for all readers. In summary, CADe improves radiologist performance with respect to both accuracy and reading time for the detection of breast cancer using the ABVS, with the greater benefit for those inexperienced with ABVS. Copyright © 2018 World Federation for Ultrasound in Medicine and Biology. Published by Elsevier Inc. All rights reserved.

Computer-aided auscultation learning system for nursing technique instruction.

PubMed

Hou, Chun-Ju; Chen, Yen-Ting; Hu, Ling-Chen; Chuang, Chih-Chieh; Chiu, Yu-Hsien; Tsai, Ming-Shih

2008-01-01

Pulmonary auscultation is a physical assessment skill learned by nursing students for examining the respiratory system. Generally, a sound simulator equipped mannequin is used to group teach auscultation techniques via classroom demonstration. However, nursing students cannot readily duplicate this learning environment for self-study. The advancement of electronic and digital signal processing technologies facilitates simulating this learning environment. This study aims to develop a computer-aided auscultation learning system for assisting teachers and nursing students in auscultation teaching and learning. This system provides teachers with signal recording and processing of lung sounds and immediate playback of lung sounds for students. A graphical user interface allows teachers to control the measuring device, draw lung sound waveforms, highlight lung sound segments of interest, and include descriptive text. Effects on learning lung sound auscultation were evaluated for verifying the feasibility of the system. Fifteen nursing students voluntarily participated in the repeated experiment. The results of a paired t test showed that auscultative abilities of the students were significantly improved by using the computer-aided auscultation learning system.

Automated detection of red lesions from digital colour fundus photographs.

PubMed

Jaafar, Hussain F; Nandi, Asoke K; Al-Nuaimy, Waleed

2011-01-01

Earliest signs of diabetic retinopathy, the major cause of vision loss, are damage to the blood vessels and the formation of lesions in the retina. Early detection of diabetic retinopathy is essential for the prevention of blindness. In this paper we present a computer-aided system to automatically identify red lesions from retinal fundus photographs. After pre-processing, a morphological technique was used to segment red lesion candidates from the background and other retinal structures. Then a rule-based classifier was used to discriminate actual red lesions from artifacts. A novel method for blood vessel detection is also proposed to refine the detection of red lesions. For a standarised test set of 219 images, the proposed method can detect red lesions with a sensitivity of 89.7% and a specificity of 98.6% (at lesion level). The performance of the proposed method shows considerable promise for detection of red lesions as well as other types of lesions.

Detection of Melanoma Skin Cancer in Dermoscopy Images

NASA Astrophysics Data System (ADS)

Eltayef, Khalid; Li, Yongmin; Liu, Xiaohui

2017-02-01

Malignant melanoma is the most hazardous type of human skin cancer and its incidence has been rapidly increasing. Early detection of malignant melanoma in dermoscopy images is very important and critical, since its detection in the early stage can be helpful to cure it. Computer Aided Diagnosis systems can be very helpful to facilitate the early detection of cancers for dermatologists. In this paper, we present a novel method for the detection of melanoma skin cancer. To detect the hair and several noises from images, pre-processing step is carried out by applying a bank of directional filters. And therefore, Image inpainting method is implemented to fill in the unknown regions. Fuzzy C-Means and Markov Random Field methods are used to delineate the border of the lesion area in the images. The method was evaluated on a dataset of 200 dermoscopic images, and superior results were produced compared to alternative methods.

Human interaction with wearable computer systems: a look at glasses-mounted displays

NASA Astrophysics Data System (ADS)

Revels, Allen R.; Quill, Laurie L.; Kancler, David E.; Masquelier, Barbara L.

1998-09-01

With the advancement of technology and the information explosion, integration of the two into performance aiding systems can have a significant impact on operational and maintenance environments. The Department of Defense and commercial industry have made great strides in digitizing and automating technical manuals and data to be presented on performance aiding systems. These performance aides are computerized interactive systems that provide procedures on how to operate and maintain fielded systems. The idea is to provide the end-user a system which is compatible with their work environment. The purpose of this paper is to show, historically, the progression of wearable computer aiding systems for maintenance environments, and then highlight the work accomplished in the design and development of glasses- mounted displays (GMD). The paper reviews work performed over the last seven years, then highlights, through review of a usability study, the advances made with GMDs. The use of portable computing systems, such as laptop and notebook, computers, does not necessarily increase the accessibility of the displayed information while accomplishing a given task in a hands-busy, mobile work environment. The use of a GMD increases accessibility of the information by placing it in eye sight of the user without obstructing the surrounding environment. Although the potential utility for this type of display is great, hardware and human integration must be refined. Results from the usability study show the usefulness and usability of the GMD in a mobile, hands-free environment.

29 CFR 541.401 - Computer manufacture and repair.

Code of Federal Regulations, 2014 CFR

2014-07-01

..., the use of computers and computer software programs (e.g., engineers, drafters and others skilled in computer-aided design software), but who are not primarily engaged in computer systems analysis and...

29 CFR 541.401 - Computer manufacture and repair.

Code of Federal Regulations, 2012 CFR

2012-07-01

..., the use of computers and computer software programs (e.g., engineers, drafters and others skilled in computer-aided design software), but who are not primarily engaged in computer systems analysis and...

29 CFR 541.401 - Computer manufacture and repair.

Code of Federal Regulations, 2013 CFR

2013-07-01

..., the use of computers and computer software programs (e.g., engineers, drafters and others skilled in computer-aided design software), but who are not primarily engaged in computer systems analysis and...

29 CFR 541.401 - Computer manufacture and repair.

Code of Federal Regulations, 2010 CFR

2010-07-01

..., the use of computers and computer software programs (e.g., engineers, drafters and others skilled in computer-aided design software), but who are not primarily engaged in computer systems analysis and...

F18 FDG positron emission tomography revelation of primary testicular lymphoma with concurrent multiple extra nodal involvement

PubMed Central

Vamsy, Mohana; Dattatreya, PS; Parakh, Megha; Dayal, Monal; Rao, VVS Prabhakar

2013-01-01

Primary testicular lymphoma (PTL) a relatively rare disease of non-Hodgkin's lymphomas occurring with a lesser incidence of 1-2% has a propensity to occur at later ages above 50 years. PTL spreads to extra nodal sites due to deficiency of extra cellular adhesion molecules. We present detection of multiple sites of extra nodal involvement of PTL by F-18 positron emission tomography/computed tomography study aiding early detection of the dissemination thus aiding in staging and management. PMID:24019676

The Use of Computers to Aid Instruction in Beginning Chemistry

ERIC Educational Resources Information Center

Grandey, Robert C.

1971-01-01

Describes computer-aided lessons for determining chemical formulas from composition by weight, quantities from chemical equations, and balancing equations for oxidation-reduction reactions. Lessons were developed and used on the PLATO system at the University of Illinois. A brief analysis of student attitudes and of effectiveness of the programs…

Electronic Computer Aided Design. Its Application in FE.

ERIC Educational Resources Information Center

Further Education Unit, London (England).

A study was conducted at the Electronics Industrial Unit at the Dorset Institute of Higher Education to investigate the feasibility of incorporating computer-aided design (CAD) in electrical and electronic courses. The aim was to investigate the application of CAD to electrical and electronic systems; the extent to which industrial developments…

Computer-Aided Instruction.

ERIC Educational Resources Information Center

Hunt, Graham

This report discusses the impact of and presents guidelines for developing a computer-aided instructional (CAI) system. The first section discusses CAI in terms of the need for the countries of Asia to increase their economic self-sufficiency. The second section examines various theories on the nature of learning with special attention to the role…

Software Engineering Techniques for Computer-Aided Learning.

ERIC Educational Resources Information Center

Ibrahim, Bertrand

1989-01-01

Describes the process for developing tutorials for computer-aided learning (CAL) using a programing language rather than an authoring system. The workstation used is described, the use of graphics is discussed, the role of a local area network (LAN) is explained, and future plans are discussed. (five references) (LRW)

Automatic Detection of Optic Disc in Retinal Image by Using Keypoint Detection, Texture Analysis, and Visual Dictionary Techniques

PubMed Central

Bayır, Şafak

2016-01-01

With the advances in the computer field, methods and techniques in automatic image processing and analysis provide the opportunity to detect automatically the change and degeneration in retinal images. Localization of the optic disc is extremely important for determining the hard exudate lesions or neovascularization, which is the later phase of diabetic retinopathy, in computer aided eye disease diagnosis systems. Whereas optic disc detection is fairly an easy process in normal retinal images, detecting this region in the retinal image which is diabetic retinopathy disease may be difficult. Sometimes information related to optic disc and hard exudate information may be the same in terms of machine learning. We presented a novel approach for efficient and accurate localization of optic disc in retinal images having noise and other lesions. This approach is comprised of five main steps which are image processing, keypoint extraction, texture analysis, visual dictionary, and classifier techniques. We tested our proposed technique on 3 public datasets and obtained quantitative results. Experimental results show that an average optic disc detection accuracy of 94.38%, 95.00%, and 90.00% is achieved, respectively, on the following public datasets: DIARETDB1, DRIVE, and ROC. PMID:27110272

Computer-aided marginal artery detection on computed tomographic colonography

NASA Astrophysics Data System (ADS)

Wei, Zhuoshi; Yao, Jianhua; Wang, Shijun; Liu, Jiamin; Summers, Ronald M.

2012-03-01

Computed tomographic colonography (CTC) is a minimally invasive technique for colonic polyps and cancer screening. The marginal artery of the colon, also known as the marginal artery of Drummond, is the blood vessel that connects the inferior mesenteric artery with the superior mesenteric artery. The marginal artery runs parallel to the colon for its entire length, providing the blood supply to the colon. Detecting the marginal artery may benefit computer-aided detection (CAD) of colonic polyp. It can be used to identify teniae coli based on their anatomic spatial relationship. It can also serve as an alternative marker for colon localization, in case of colon collapse and inability to directly compute the endoluminal centerline. This paper proposes an automatic method for marginal artery detection on CTC. To the best of our knowledge, this is the first work presented for this purpose. Our method includes two stages. The first stage extracts the blood vessels in the abdominal region. The eigenvalue of Hessian matrix is used to detect line-like structures in the images. The second stage is to reduce the false positives in the first step. We used two different masks to exclude the false positive vessel regions. One is a dilated colon mask which is obtained by colon segmentation. The other is an eroded visceral fat mask which is obtained by fat segmentation in the abdominal region. We tested our method on a CTC dataset with 6 cases. Using ratio-of-overlap with manual labeling of the marginal artery as the standard-of-reference, our method yielded true positive, false positive and false negative fractions of 89%, 33%, 11%, respectively.

Computer-aided system for detecting runway incursions

NASA Astrophysics Data System (ADS)

Sridhar, Banavar; Chatterji, Gano B.

1994-07-01

A synthetic vision system for enhancing the pilot's ability to navigate and control the aircraft on the ground is described. The system uses the onboard airport database and images acquired by external sensors. Additional navigation information needed by the system is provided by the Inertial Navigation System and the Global Positioning System. The various functions of the system, such as image enhancement, map generation, obstacle detection, collision avoidance, guidance, etc., are identified. The available technologies, some of which were developed at NASA, that are applicable to the aircraft ground navigation problem are noted. Example images of a truck crossing the runway while the aircraft flies close to the runway centerline are described. These images are from a sequence of images acquired during one of the several flight experiments conducted by NASA to acquire data to be used for the development and verification of the synthetic vision concepts. These experiments provide a realistic database including video and infrared images, motion states from the Inertial Navigation System and the Global Positioning System, and camera parameters.

Application of Particle Swarm Optimization in Computer Aided Setup Planning

NASA Astrophysics Data System (ADS)

Kafashi, Sajad; Shakeri, Mohsen; Abedini, Vahid

2011-01-01

New researches are trying to integrate computer aided design (CAD) and computer aided manufacturing (CAM) environments. The role of process planning is to convert the design specification into manufacturing instructions. Setup planning has a basic role in computer aided process planning (CAPP) and significantly affects the overall cost and quality of machined part. This research focuses on the development for automatic generation of setups and finding the best setup plan in feasible condition. In order to computerize the setup planning process, three major steps are performed in the proposed system: a) Extraction of machining data of the part. b) Analyzing and generation of all possible setups c) Optimization to reach the best setup plan based on cost functions. Considering workshop resources such as machine tool, cutter and fixture, all feasible setups could be generated. Then the problem is adopted with technological constraints such as TAD (tool approach direction), tolerance relationship and feature precedence relationship to have a completely real and practical approach. The optimal setup plan is the result of applying the PSO (particle swarm optimization) algorithm into the system using cost functions. A real sample part is illustrated to demonstrate the performance and productivity of the system.

COMPUTER SUPPORT SYSTEMS FOR ESTIMATING CHEMICAL TOXICITY: PRESENT CAPABILITIES AND FUTURE TRENDS

EPA Science Inventory

Computer Support Systems for Estimating Chemical Toxicity: Present Capabilities and Future Trends

A wide variety of computer-based artificial intelligence (AI) and decision support systems exist currently to aid in the assessment of toxicity for environmental chemicals. T...

Innovative telecommunications for law enforcement

NASA Technical Reports Server (NTRS)

Sohn, R. L.

1976-01-01

The operation of computer-aided dispatch, mobile digital communications, and automatic vehicle location systems used in law enforcement is discussed, and characteristics of systems used by different agencies are compared. With reference to computer-aided dispatch systems, the data base components, dispatcher work load, extent of usage, and design trends are surveyed. The capabilities, levels of communication, and traffic load of mobile digital communications systems are examined. Different automatic vehicle location systems are distinguished, and two systems are evaluated. Other aspects of the application of innovative technology to operational command, control, and communications systems for law enforcement agencies are described.

Air traffic surveillance and control using hybrid estimation and protocol-based conflict resolution

NASA Astrophysics Data System (ADS)

Hwang, Inseok

The continued growth of air travel and recent advances in new technologies for navigation, surveillance, and communication have led to proposals by the Federal Aviation Administration (FAA) to provide reliable and efficient tools to aid Air Traffic Control (ATC) in performing their tasks. In this dissertation, we address four problems frequently encountered in air traffic surveillance and control; multiple target tracking and identity management, conflict detection, conflict resolution, and safety verification. We develop a set of algorithms and tools to aid ATC; These algorithms have the provable properties of safety, computational efficiency, and convergence. Firstly, we develop a multiple-maneuvering-target tracking and identity management algorithm which can keep track of maneuvering aircraft in noisy environments and of their identities. Secondly, we propose a hybrid probabilistic conflict detection algorithm between multiple aircraft which uses flight mode estimates as well as aircraft current state estimates. Our algorithm is based on hybrid models of aircraft, which incorporate both continuous dynamics and discrete mode switching. Thirdly, we develop an algorithm for multiple (greater than two) aircraft conflict avoidance that is based on a closed-form analytic solution and thus provides guarantees of safety. Finally, we consider the problem of safety verification of control laws for safety critical systems, with application to air traffic control systems. We approach safety verification through reachability analysis, which is a computationally expensive problem. We develop an over-approximate method for reachable set computation using polytopic approximation methods and dynamic optimization. These algorithms may be used either in a fully autonomous way, or as supporting tools to increase controllers' situational awareness and to reduce their work load.

An Artificial Neural Network Evaluation of Tuberculosis Using Genetic and Physiological Patient Data

NASA Astrophysics Data System (ADS)

Griffin, William O.; Hanna, Josh; Razorilova, Svetlana; Kitaev, Mikhael; Alisherov, Avtandiil; Darsey, Jerry A.; Tarasenko, Olga

2010-04-01

When doctors see more cases of patients with tell-tale symptoms of a disease, it is hoped that they will be able to recognize an infection administer treatment appropriately, thereby speeding up recovery for sick patients. We hope that our studies can aid in the detection of tuberculosis by using a computer model called an artificial neural network. Our model looks at patients with and without tuberculosis (TB). The data that the neural network examined came from the following: patient' age, gender, place, of birth, blood type, Rhesus (Rh) factor, and genes of the human Leukocyte Antigens (HLA) system (9q34.1) present in the Major Histocompatibility Complex. With availability in genetic data and good research, we hope to give them an advantage in the detection of tuberculosis. We try to mimic the doctor's experience with a computer test, which will learn from patient data the factors that contribute to TB.

COMPUTER-AIDED DRAFTING AND DESIGN, A THREE-WEEK SUMMER INSTITUTE TRAINING PROGRAM (MIAMI-DADE JUNIOR COLLEGE, MIAMI, FLORIDA, JULY 10, 1967 - JULY 28, 1967). FINAL REPORT.

ERIC Educational Resources Information Center

MORPHONIOS, ALEX G.

THIRTY-SIX INSTRUCTORS, SUPERVISORS, AND DEPARTMENT CHAIRMEN IN AREAS OF DRAFTING, ENGINEERING, MANUFACTURING, AND COMPUTER TECHNOLOGY AT JUNIOR COLLEGES, TECHNICAL, AND AREA VOCATIONAL SCHOOLS IN 20 STATES ATTENDED A 3-WEEK SUMMER INSTITUTE TRAINING PROGRAM ON COMPUTER-AIDED DRAFTING AND DESIGN. EXPERIENCE IN PROGRAMING THE IBM SYSTEM 1620 WITH…

Computer-Aided Diagnosis of Different Rotator Cuff Lesions Using Shoulder Musculoskeletal Ultrasound.

PubMed

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.

Superpixel-based segmentation of glottal area from videolaryngoscopy images

NASA Astrophysics Data System (ADS)

Turkmen, H. Irem; Albayrak, Abdulkadir; Karsligil, M. Elif; Kocak, Ismail

2017-11-01

Segmentation of the glottal area with high accuracy is one of the major challenges for the development of systems for computer-aided diagnosis of vocal-fold disorders. We propose a hybrid model combining conventional methods with a superpixel-based segmentation approach. We first employed a superpixel algorithm to reveal the glottal area by eliminating the local variances of pixels caused by bleedings, blood vessels, and light reflections from mucosa. Then, the glottal area was detected by exploiting a seeded region-growing algorithm in a fully automatic manner. The experiments were conducted on videolaryngoscopy images obtained from both patients having pathologic vocal folds as well as healthy subjects. Finally, the proposed hybrid approach was compared with conventional region-growing and active-contour model-based glottal area segmentation algorithms. The performance of the proposed method was evaluated in terms of segmentation accuracy and elapsed time. The F-measure, true negative rate, and dice coefficients of the hybrid method were calculated as 82%, 93%, and 82%, respectively, which are superior to the state-of-art glottal-area segmentation methods. The proposed hybrid model achieved high success rates and robustness, making it suitable for developing a computer-aided diagnosis system that can be used in clinical routines.

Evaluation of computer-aided diagnosis (CAD) software for the detection of lung nodules on multidetector row computed tomography (MDCT): JAFROC study for the improvement in radiologists' diagnostic accuracy.

PubMed

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.

A specialized plug-in software module for computer-aided quantitative measurement of medical images.

PubMed

Wang, Q; Zeng, Y J; Huo, P; Hu, J L; Zhang, J H

2003-12-01

This paper presents a specialized system for quantitative measurement of medical images. Using Visual C++, we developed a computer-aided software based on Image-Pro Plus (IPP), a software development platform. When transferred to the hard disk of a computer by an MVPCI-V3A frame grabber, medical images can be automatically processed by our own IPP plug-in for immunohistochemical analysis, cytomorphological measurement and blood vessel segmentation. In 34 clinical studies, the system has shown its high stability, reliability and ease of utility.

Computer-aided programming for message-passing system; Problems and a solution

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wu, M.Y.; Gajski, D.D.

1989-12-01

As the number of processors and the complexity of problems to be solved increase, programming multiprocessing systems becomes more difficult and error-prone. Program development tools are necessary since programmers are not able to develop complex parallel programs efficiently. Parallel models of computation, parallelization problems, and tools for computer-aided programming (CAP) are discussed. As an example, a CAP tool that performs scheduling and inserts communication primitives automatically is described. It also generates the performance estimates and other program quality measures to help programmers in improving their algorithms and programs.

Bayesian networks and statistical analysis application to analyze the diagnostic test accuracy

NASA Astrophysics Data System (ADS)

Orzechowski, P.; Makal, Jaroslaw; Onisko, A.

2005-02-01

The computer aided BPH diagnosis system based on Bayesian network is described in the paper. First result are compared to a given statistical method. Different statistical methods are used successfully in medicine for years. However, the undoubted advantages of probabilistic methods make them useful in application in newly created systems which are frequent in medicine, but do not have full and competent knowledge. The article presents advantages of the computer aided BPH diagnosis system in clinical practice for urologists.

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.

Case-based lung image categorization and retrieval for interstitial lung diseases: clinical workflows.

PubMed

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.

SU-E-I-30: Image Analysis in Ultrasonography for Diagnosis of Sjoegren's Syndrome Using Dual-Tree Complex Wavelet Transform

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

When and why might a Computer Aided Detection (CAD) system interfere with visual search? An eye-tracking study

PubMed Central

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

Applying Model-Based Reasoning to the FDIR of the Command and Data Handling Subsystem of the International Space Station

NASA Technical Reports Server (NTRS)

Robinson, Peter; Shirley, Mark; Fletcher, Daryl; Alena, Rick; Duncavage, Dan; Lee, Charles

2003-01-01

All of the International Space Station (ISS) systems which require computer control depend upon the hardware and software of the Command and Data Handling System (C&DH) system, currently a network of over 30 386-class computers called Multiplexor/Dimultiplexors (MDMs)[18]. The Caution and Warning System (C&W)[7], a set of software tasks that runs on the MDMs, is responsible for detecting, classifying, and reporting errors in all ISS subsystems including the C&DH. Fault Detection, Isolation and Recovery (FDIR) of these errors is typically handled with a combination of automatic and human effort. We are developing an Advanced Diagnostic System (ADS) to augment the C&W system with decision support tools to aid in root cause analysis as well as resolve differing human and machine C&DH state estimates. These tools which draw from sources in model-based reasoning[ 16,291, will improve the speed and accuracy of flight controllers by reducing the uncertainty in C&DH state estimation, allowing for a more complete assessment of risk. We have run tests with ISS telemetry and focus on those C&W events which relate to the C&DH system itself. This paper describes our initial results and subsequent plans.

Flexible structure control experiments using a real-time workstation for computer-aided control engineering

NASA Technical Reports Server (NTRS)

Stieber, Michael E.

1989-01-01

A Real-Time Workstation for Computer-Aided Control Engineering has been developed jointly by the Communications Research Centre (CRC) and Ruhr-Universitaet Bochum (RUB), West Germany. The system is presently used for the development and experimental verification of control techniques for large space systems with significant structural flexibility. The Real-Time Workstation essentially is an implementation of RUB's extensive Computer-Aided Control Engineering package KEDDC on an INTEL micro-computer running under the RMS real-time operating system. The portable system supports system identification, analysis, control design and simulation, as well as the immediate implementation and test of control systems. The Real-Time Workstation is currently being used by CRC to study control/structure interaction on a ground-based structure called DAISY, whose design was inspired by a reflector antenna. DAISY emulates the dynamics of a large flexible spacecraft with the following characteristics: rigid body modes, many clustered vibration modes with low frequencies and extremely low damping. The Real-Time Workstation was found to be a very powerful tool for experimental studies, supporting control design and simulation, and conducting and evaluating tests withn one integrated environment.

NAVSIM 2: A computer program for simulating aided-inertial navigation for aircraft

NASA Technical Reports Server (NTRS)

Bjorkman, William S.

1987-01-01

NAVSIM II, a computer program for analytical simulation of aided-inertial navigation for aircraft, is described. The description is supported by a discussion of the program's application to the design and analysis of aided-inertial navigation systems as well as instructions for utilizing the program and for modifying it to accommodate new models, constraints, algorithms and scenarios. NAVSIM II simulates an airborne inertial navigation system built around a strapped-down inertial measurement unit and aided in its function by GPS, Doppler radar, altimeter, airspeed, and position-fix measurements. The measurements are incorporated into the navigation estimate via a UD-form Kalman filter. The simulation was designed and implemented using structured programming techniques and with particular attention to user-friendly operation.

Interactive graphical computer-aided design system

NASA Technical Reports Server (NTRS)

Edge, T. M.

1975-01-01

System is used for design, layout, and modification of large-scale-integrated (LSI) metal-oxide semiconductor (MOS) arrays. System is structured around small computer which provides real-time support for graphics storage display unit with keyboard, slave display unit, hard copy unit, and graphics tablet for designer/computer interface.

Computer-aided diagnosis of malignant mammograms using Zernike moments and SVM.

PubMed

Sharma, Shubhi; Khanna, Pritee

2015-02-01

This work is directed toward the development of a computer-aided diagnosis (CAD) system to detect abnormalities or suspicious areas in digital mammograms and classify them as malignant or nonmalignant. Original mammogram is preprocessed to separate the breast region from its background. To work on the suspicious area of the breast, region of interest (ROI) patches of a fixed size of 128×128 are extracted from the original large-sized digital mammograms. For training, patches are extracted manually from a preprocessed mammogram. For testing, patches are extracted from a highly dense area identified by clustering technique. For all extracted patches corresponding to a mammogram, Zernike moments of different orders are computed and stored as a feature vector. A support vector machine (SVM) is used to classify extracted ROI patches. The experimental study shows that the use of Zernike moments with order 20 and SVM classifier gives better results among other studies. The proposed system is tested on Image Retrieval In Medical Application (IRMA) reference dataset and Digital Database for Screening Mammography (DDSM) mammogram database. On IRMA reference dataset, it attains 99% sensitivity and 99% specificity, and on DDSM mammogram database, it obtained 97% sensitivity and 96% specificity. To verify the applicability of Zernike moments as a fitting texture descriptor, the performance of the proposed CAD system is compared with the other well-known texture descriptors namely gray-level co-occurrence matrix (GLCM) and discrete cosine transform (DCT).

Statistical-techniques-based computer-aided diagnosis (CAD) using texture feature analysis: application in computed tomography (CT) imaging to fatty liver disease

NASA Astrophysics Data System (ADS)

Chung, Woon-Kwan; Park, Hyong-Hu; Im, In-Chul; Lee, Jae-Seung; Goo, Eun-Hoe; Dong, Kyung-Rae

2012-09-01

This paper proposes a computer-aided diagnosis (CAD) system based on texture feature analysis and statistical wavelet transformation technology to diagnose fatty liver disease with computed tomography (CT) imaging. In the target image, a wavelet transformation was performed for each lesion area to set the region of analysis (ROA, window size: 50 × 50 pixels) and define the texture feature of a pixel. Based on the extracted texture feature values, six parameters (average gray level, average contrast, relative smoothness, skewness, uniformity, and entropy) were determined to calculate the recognition rate for a fatty liver. In addition, a multivariate analysis of the variance (MANOVA) method was used to perform a discriminant analysis to verify the significance of the extracted texture feature values and the recognition rate for a fatty liver. According to the results, each texture feature value was significant for a comparison of the recognition rate for a fatty liver ( p < 0.05). Furthermore, the F-value, which was used as a scale for the difference in recognition rates, was highest in the average gray level, relatively high in the skewness and the entropy, and relatively low in the uniformity, the relative smoothness and the average contrast. The recognition rate for a fatty liver had the same scale as that for the F-value, showing 100% (average gray level) at the maximum and 80% (average contrast) at the minimum. Therefore, the recognition rate is believed to be a useful clinical value for the automatic detection and computer-aided diagnosis (CAD) using the texture feature value. Nevertheless, further study on various diseases and singular diseases will be needed in the future.

Computer program for design and performance analysis of navigation-aid power systems. Program documentation. Volume 1: Software requirements document

NASA Technical Reports Server (NTRS)

Goltz, G.; Kaiser, L. M.; Weiner, H.

1977-01-01

A computer program has been developed for designing and analyzing the performance of solar array/battery power systems for the U.S. Coast Guard Navigational Aids. This program is called the Design Synthesis/Performance Analysis (DSPA) Computer Program. The basic function of the Design Synthesis portion of the DSPA program is to evaluate functional and economic criteria to provide specifications for viable solar array/battery power systems. The basic function of the Performance Analysis portion of the DSPA program is to simulate the operation of solar array/battery power systems under specific loads and environmental conditions. This document establishes the software requirements for the DSPA computer program, discusses the processing that occurs within the program, and defines the necessary interfaces for operation.

Breast cancer risk assessment and diagnosis model using fuzzy support vector machine based expert system

NASA Astrophysics Data System (ADS)

Dheeba, J.; Jaya, T.; Singh, N. Albert

2017-09-01

Classification of cancerous masses is a challenging task in many computerised detection systems. Cancerous masses are difficult to detect because these masses are obscured and subtle in mammograms. This paper investigates an intelligent classifier - fuzzy support vector machine (FSVM) applied to classify the tissues containing masses on mammograms for breast cancer diagnosis. The algorithm utilises texture features extracted using Laws texture energy measures and a FSVM to classify the suspicious masses. The new FSVM treats every feature as both normal and abnormal samples, but with different membership. By this way, the new FSVM have more generalisation ability to classify the masses in mammograms. The classifier analysed 219 clinical mammograms collected from breast cancer screening laboratory. The tests made on the real clinical mammograms shows that the proposed detection system has better discriminating power than the conventional support vector machine. With the best combination of FSVM and Laws texture features, the area under the Receiver operating characteristic curve reached .95, which corresponds to a sensitivity of 93.27% with a specificity of 87.17%. The results suggest that detecting masses using FSVM contribute to computer-aided detection of breast cancer and as a decision support system for radiologists.

A computer-aided diagnosis system of nuclear cataract.

PubMed

Li, Huiqi; Lim, Joo Hwee; Liu, Jiang; Mitchell, Paul; Tan, Ava Grace; Wang, Jie Jin; Wong, Tien Yin

2010-07-01

Cataracts are the leading cause of blindness worldwide, and nuclear cataract is the most common form of cataract. An algorithm for automatic diagnosis of nuclear cataract is investigated in this paper. Nuclear cataract is graded according to the severity of opacity using slit lamp lens images. Anatomical structure in the lens image is detected using a modified active shape model. On the basis of the anatomical landmark, local features are extracted according to clinical grading protocol. Support vector machine regression is employed for grade prediction. This is the first time that the nucleus region can be detected automatically in slit lamp images. The system is validated using clinical images and clinical ground truth on >5000 images. The success rate of structure detection is 95% and the average grading difference is 0.36 on a 5.0 scale. The automatic diagnosis system can improve the grading objectivity and potentially be used in clinics and population studies to save the workload of ophthalmologists.

A feasibility study of automatic lung nodule detection in chest digital tomosynthesis with machine learning based on support vector machine

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 systems human engineering: A hypermedia tool

NASA Technical Reports Server (NTRS)

Boff, Kenneth R.; Monk, Donald L.; Cody, William J.

1992-01-01

The Computer Aided Systems Human Engineering (CASHE) system, Version 1.0, is a multimedia ergonomics database on CD-ROM for the Apple Macintosh II computer, being developed for use by human system designers, educators, and researchers. It will initially be available on CD-ROM and will allow users to access ergonomics data and models stored electronically as text, graphics, and audio. The CASHE CD-ROM, Version 1.0 will contain the Boff and Lincoln (1988) Engineering Data Compendium, MIL-STD-1472D and a unique, interactive simulation capability, the Perception and Performance Prototyper. Its features also include a specialized data retrieval, scaling, and analysis capability and the state of the art in information retrieval, browsing, and navigation.

Computer aided detection of ureteral stones in thin slice computed tomography volumes using Convolutional Neural Networks.

PubMed

Längkvist, Martin; Jendeberg, Johan; Thunberg, Per; Loutfi, Amy; Lidén, Mats

2018-06-01

Computed tomography (CT) is the method of choice for diagnosing ureteral stones - kidney stones that obstruct the ureter. The purpose of this study is to develop a computer aided detection (CAD) algorithm for identifying a ureteral stone in thin slice CT volumes. The challenge in CAD for urinary stones lies in the similarity in shape and intensity of stones with non-stone structures and how to efficiently deal with large high-resolution CT volumes. We address these challenges by using a Convolutional Neural Network (CNN) that works directly on the high resolution CT volumes. The method is evaluated on a large data base of 465 clinically acquired high-resolution CT volumes of the urinary tract with labeling of ureteral stones performed by a radiologist. The best model using 2.5D input data and anatomical information achieved a sensitivity of 100% and an average of 2.68 false-positives per patient on a test set of 88 scans. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

On the convergence of nanotechnology and Big Data analysis for computer-aided diagnosis.

PubMed

Rodrigues, Jose F; Paulovich, Fernando V; de Oliveira, Maria Cf; de Oliveira, Osvaldo N

2016-04-01

An overview is provided of the challenges involved in building computer-aided diagnosis systems capable of precise medical diagnostics based on integration and interpretation of data from different sources and formats. The availability of massive amounts of data and computational methods associated with the Big Data paradigm has brought hope that such systems may soon be available in routine clinical practices, which is not the case today. We focus on visual and machine learning analysis of medical data acquired with varied nanotech-based techniques and on methods for Big Data infrastructure. Because diagnosis is essentially a classification task, we address the machine learning techniques with supervised and unsupervised classification, making a critical assessment of the progress already made in the medical field and the prospects for the near future. We also advocate that successful computer-aided diagnosis requires a merge of methods and concepts from nanotechnology and Big Data analysis.

NASA Tech Briefs, June 2000. Volume 24, No. 6

NASA Technical Reports Server (NTRS)

2000-01-01

Topics include: Computer-Aided Design and Engineering; Electronic Components and Circuits; Electronic Systems; Test and Measurement; Physical Sciences; Materials; Computer Programs; Computers and Peripherals;

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.

Computer-aided detection of brain metastasis on 3D MR imaging: Observer performance study.

PubMed

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.

Investigation of Air Transportation Technology at Princeton University, 1989-1990

NASA Technical Reports Server (NTRS)

Stengel, Robert F.

1990-01-01

The Air Transportation Technology Program at Princeton University proceeded along six avenues during the past year: microburst hazards to aircraft; machine-intelligent, fault tolerant flight control; computer aided heuristics for piloted flight; stochastic robustness for flight control systems; neural networks for flight control; and computer aided control system design. These topics are briefly discussed, and an annotated bibliography of publications that appeared between January 1989 and June 1990 is given.

Computer-Aided Diagnosis of Acute Lymphoblastic Leukaemia

PubMed Central

2018-01-01

Leukaemia is a form of blood cancer which affects the white blood cells and damages the bone marrow. Usually complete blood count (CBC) and bone marrow aspiration are used to diagnose the acute lymphoblastic leukaemia. It can be a fatal disease if not diagnosed at the earlier stage. In practice, manual microscopic evaluation of stained sample slide is used for diagnosis of leukaemia. But manual diagnostic methods are time-consuming, less accurate, and prone to errors due to various human factors like stress, fatigue, and so forth. Therefore, different automated systems have been proposed to wrestle the glitches in the manual diagnostic methods. In recent past, some computer-aided leukaemia diagnosis methods are presented. These automated systems are fast, reliable, and accurate as compared to manual diagnosis methods. This paper presents review of computer-aided diagnosis systems regarding their methodologies that include enhancement, segmentation, feature extraction, classification, and accuracy. PMID:29681996

Computer-Aided Drafting. Education for Technology Employment.

ERIC Educational Resources Information Center

Northern Illinois Univ., De Kalb. Dept. of Technology.

This computer-aided drafting (CAD) curriculum was developed to provide drafting instructors in Illinois with a useful guide for relating an important new technological advance to the vocational classroom. The competency-based learning activity guides are written to be used with any CAD system being used at the secondary and postsecondary levels.…

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…

Computer-aided system of evaluation for population-based all-in-one service screening (CASE-PASS): from study design to outcome analysis with bias adjustment.

PubMed

Chen, Li-Sheng; Yen, Amy Ming-Fang; Duffy, Stephen W; Tabar, Laszlo; Lin, Wen-Chou; Chen, Hsiu-Hsi

2010-10-01

Population-based routine service screening has gained popularity following an era of randomized controlled trials. The evaluation of these service screening programs is subject to study design, data availability, and the precise data analysis for adjusting bias. We developed a computer-aided system that allows the evaluation of population-based service screening to unify these aspects and facilitate and guide the program assessor to efficiently perform an evaluation. This system underpins two experimental designs: the posttest-only non-equivalent design and the one-group pretest-posttest design and demonstrates the type of data required at both the population and individual levels. Three major analyses were developed that included a cumulative mortality analysis, survival analysis with lead-time adjustment, and self-selection bias adjustment. We used SAS AF software to develop a graphic interface system with a pull-down menu style. We demonstrate the application of this system with data obtained from a Swedish population-based service screen and a population-based randomized controlled trial for the screening of breast, colorectal, and prostate cancer, and one service screening program for cervical cancer with Pap smears. The system provided automated descriptive results based on the various sources of available data and cumulative mortality curves corresponding to the study designs. The comparison of cumulative survival between clinically and screen-detected cases without a lead-time adjustment are also demonstrated. The intention-to-treat and noncompliance analysis with self-selection bias adjustments are also shown to assess the effectiveness of the population-based service screening program. Model validation was composed of a comparison between our adjusted self-selection bias estimates and the empirical results on effectiveness reported in the literature. We demonstrate a computer-aided system allowing the evaluation of population-based service screening programs with an adjustment for self-selection and lead-time bias. This is achieved by providing a tutorial guide from the study design to the data analysis, with bias adjustment. Copyright © 2010 Elsevier Inc. All rights reserved.

Computer-aided engineering of semiconductor integrated circuits

NASA Astrophysics Data System (ADS)

Meindl, J. D.; Dutton, R. W.; Gibbons, J. F.; Helms, C. R.; Plummer, J. D.; Tiller, W. A.; Ho, C. P.; Saraswat, K. C.; Deal, B. E.; Kamins, T. I.

1980-07-01

Economical procurement of small quantities of high performance custom integrated circuits for military systems is impeded by inadequate process, device and circuit models that handicap low cost computer aided design. The principal objective of this program is to formulate physical models of fabrication processes, devices and circuits to allow total computer-aided design of custom large-scale integrated circuits. The basic areas under investigation are (1) thermal oxidation, (2) ion implantation and diffusion, (3) chemical vapor deposition of silicon and refractory metal silicides, (4) device simulation and analytic measurements. This report discusses the fourth year of the program.

CAD system for footwear design based on whole real 3D data of last surface

NASA Astrophysics Data System (ADS)

Song, Wanzhong; Su, Xianyu

2000-10-01

Two major parts of application of CAD in footwear design are studied: the development of last surface; computer-aided design of planar shoe-template. A new quasi-experiential development algorithm of last surface based on triangulation approximation is presented. This development algorithm consumes less time and does not need any interactive operation for precisely development compared with other development algorithm of last surface. Based on this algorithm, a software, SHOEMAKERTM, which contains computer aided automatic measurement, automatic development of last surface and computer aide design of shoe-template has been developed.

Implementing Computer Algebra Enabled Questions for the Assessment and Learning of Mathematics

ERIC Educational Resources Information Center

Sangwin, Christopher J.; Naismith, Laura

2008-01-01

We present principles for the design of an online system to support computer algebra enabled questions for use within the teaching and learning of mathematics in higher education. The introduction of a computer algebra system (CAS) into a computer aided assessment (CAA) system affords sophisticated response processing of student provided answers.…

Development and Verification of Body Armor Target Geometry Created Using Computed Tomography Scans

DTIC Science & Technology

2017-07-13

designated by other authorized documents. Citation of manufacturer’s or trade names does not constitute an official endorsement or approval of...modeling consisted of manual measurement of armor systems and translating those measurements to computer-aided design geometry, which can be tedious and...computer-aided design (CAD) human geometry model (referred to throughout as ORCA man) that is used in the Operational Requirement-based Casualty Assessment

A Review on Recent Developments for Detection of Diabetic Retinopathy.

PubMed

Amin, Javeria; Sharif, Muhammad; Yasmin, Mussarat

2016-01-01

Diabetic retinopathy is caused by the retinal micro vasculature which may be formed as a result of diabetes mellitus. Blindness may appear as a result of unchecked and severe cases of diabetic retinopathy. Manual inspection of fundus images to check morphological changes in microaneurysms, exudates, blood vessels, hemorrhages, and macula is a very time-consuming and tedious work. It can be made easily with the help of computer-aided system and intervariability for the observer. In this paper, several techniques for detecting microaneurysms, hemorrhages, and exudates are discussed for ultimate detection of nonproliferative diabetic retinopathy. Blood vessels detection techniques are also discussed for the diagnosis of proliferative diabetic retinopathy. Furthermore, the paper elaborates a discussion on the experiments accessed by authors for the detection of diabetic retinopathy. This work will be helpful for the researchers and technical persons who want to utilize the ongoing research in this area.

A Review on Recent Developments for Detection of Diabetic Retinopathy

PubMed Central

2016-01-01

Diabetic retinopathy is caused by the retinal micro vasculature which may be formed as a result of diabetes mellitus. Blindness may appear as a result of unchecked and severe cases of diabetic retinopathy. Manual inspection of fundus images to check morphological changes in microaneurysms, exudates, blood vessels, hemorrhages, and macula is a very time-consuming and tedious work. It can be made easily with the help of computer-aided system and intervariability for the observer. In this paper, several techniques for detecting microaneurysms, hemorrhages, and exudates are discussed for ultimate detection of nonproliferative diabetic retinopathy. Blood vessels detection techniques are also discussed for the diagnosis of proliferative diabetic retinopathy. Furthermore, the paper elaborates a discussion on the experiments accessed by authors for the detection of diabetic retinopathy. This work will be helpful for the researchers and technical persons who want to utilize the ongoing research in this area. PMID:27777811

Two methods of Haustral fold detection from computed tomographic virtual colonoscopy images

NASA Astrophysics Data System (ADS)

Chowdhury, Ananda S.; Tan, Sovira; Yao, Jianhua; Linguraru, Marius G.; Summers, Ronald M.

2009-02-01

Virtual colonoscopy (VC) has gained popularity as a new colon diagnostic method over the last decade. VC is a new, less invasive alternative to the usually practiced optical colonoscopy for colorectal polyp and cancer screening, the second major cause of cancer related deaths in industrial nations. Haustral (colonic) folds serve as important landmarks for virtual endoscopic navigation in the existing computer-aided-diagnosis (CAD) system. In this paper, we propose and compare two different methods of haustral fold detection from volumetric computed tomographic virtual colonoscopy images. The colon lumen is segmented from the input using modified region growing and fuzzy connectedness. The first method for fold detection uses a level set that evolves on a mesh representation of the colon surface. The colon surface is obtained from the segmented colon lumen using the Marching Cubes algorithm. The second method for fold detection, based on a combination of heat diffusion and fuzzy c-means algorithm, is employed on the segmented colon volume. Folds obtained on the colon volume using this method are then transferred to the corresponding colon surface. After experimentation with different datasets, results are found to be promising. The results also demonstrate that the first method has a tendency of slight under-segmentation while the second method tends to slightly over-segment the folds.

Application of Adaptive Decision Aiding Systems to Computer-Assisted Instruction. Final Report, January-December 1974.

ERIC Educational Resources Information Center

May, Donald M.; And Others

The minicomputer-based Computerized Diagnostic and Decision Training (CDDT) system described combines the principles of artificial intelligence, decision theory, and adaptive computer assisted instruction for training in electronic troubleshooting. The system incorporates an adaptive computer program which learns the student's diagnostic and…

Computer-Aided Instruction in Automated Instrumentation.

ERIC Educational Resources Information Center

Stephenson, David T.

1986-01-01

Discusses functions of automated instrumentation systems, i.e., systems which combine electrical measuring instruments and a controlling computer to measure responses of a unit under test. The computer-assisted tutorial then described is programmed for use on such a system--a modern microwave spectrum analyzer--to introduce engineering students to…

Computational Approaches for Analyzing Tradeoffs between Training and Aiding. Final Technical Paper for Period February-December 1989.

ERIC Educational Resources Information Center

Rouse, William B.; Johnson, William B.

A methodological framework is presented for representing tradeoffs among alternative combinations of training and aiding for personnel in complex situations. In general, more highly trained people need less aid, and those with less training need more aid. Balancing training and aiding to accomplish the objectives of the system in a cost effective…

Specification of Computer Systems by Objectives.

ERIC Educational Resources Information Center

Eltoft, Douglas

1989-01-01

Discusses the evolution of mainframe and personal computers, and presents a case study of a network developed at the University of Iowa called the Iowa Computer-Aided Engineering Network (ICAEN) that combines Macintosh personal computers with Apollo workstations. Functional objectives are stressed as the best measure of system performance. (LRW)

Computer aided system for parametric design of combination die

NASA Astrophysics Data System (ADS)

Naranje, Vishal G.; Hussein, H. M. A.; Kumar, S.

2017-09-01

In this paper, a computer aided system for parametric design of combination dies is presented. The system is developed using knowledge based system technique of artificial intelligence. The system is capable to design combination dies for production of sheet metal parts having punching and cupping operations. The system is coded in Visual Basic and interfaced with AutoCAD software. The low cost of the proposed system will help die designers of small and medium scale sheet metal industries for design of combination dies for similar type of products. The proposed system is capable to reduce design time and efforts of die designers for design of combination dies.

Hardware synthesis from DDL. [Digital Design Language for computer aided design and test of LSI

NASA Technical Reports Server (NTRS)

Shah, A. M.; Shiva, S. G.

1981-01-01

The details of the digital systems can be conveniently input into the design automation system by means of Hardware Description Languages (HDL). The Computer Aided Design and Test (CADAT) system at NASA MSFC is used for the LSI design. The Digital Design Language (DDL) has been selected as HDL for the CADAT System. DDL translator output can be used for the hardware implementation of the digital design. This paper addresses problems of selecting the standard cells from the CADAT standard cell library to realize the logic implied by the DDL description of the system.

School Finance Equalization Management System: An Overview.

ERIC Educational Resources Information Center

Educational Testing Service, Princeton, NJ. Education Policy Research Institute.

This overview acquaints prospective users with the School Finance Equalization Management System (SFEMS), a computer-based system designed to answer questions about state aid distribution. SFEMS can determine such things as the current pattern of aid distribution, the current pattern of tax effort, or the effect of alternative expenditure and…

Connecting the virtual world of computers to the real world of medicinal chemistry.

PubMed

Glen, Robert C

2011-03-01

Drug discovery involves the simultaneous optimization of chemical and biological properties, usually in a single small molecule, which modulates one of nature's most complex systems: the balance between human health and disease. The increased use of computer-aided methods is having a significant impact on all aspects of the drug-discovery and development process and with improved methods and ever faster computers, computer-aided molecular design will be ever more central to the discovery process.

Integrating aerodynamic surface modeling for computational fluid dynamics with computer aided structural analysis, design, and manufacturing

NASA Technical Reports Server (NTRS)

Thorp, Scott A.

1992-01-01

This presentation will discuss the development of a NASA Geometry Exchange Specification for transferring aerodynamic surface geometry between LeRC systems and grid generation software used for computational fluid dynamics research. The proposed specification is based on a subset of the Initial Graphics Exchange Specification (IGES). The presentation will include discussion of how the NASA-IGES standard will accommodate improved computer aided design inspection methods and reverse engineering techniques currently being developed. The presentation is in viewgraph format.

Cerebral microbleed detection in traumatic brain injury patients using 3D convolutional neural networks

NASA Astrophysics Data System (ADS)

Standvoss, K.; Crijns, T.; Goerke, L.; Janssen, D.; Kern, S.; van Niedek, T.; van Vugt, J.; Alfonso Burgos, N.; Gerritse, E. J.; Mol, J.; van de Vooren, D.; Ghafoorian, M.; van den Heuvel, T. L. A.; Manniesing, R.

2018-02-01

The number and location of cerebral microbleeds (CMBs) in patients with traumatic brain injury (TBI) is important to determine the severity of trauma and may hold prognostic value for patient outcome. However, manual assessment is subjective and time-consuming due to the resemblance of CMBs to blood vessels, the possible presence of imaging artifacts, and the typical heterogeneity of trauma imaging data. In this work, we present a computer aided detection system based on 3D convolutional neural networks for detecting CMBs in 3D susceptibility weighted images. Network architectures with varying depth were evaluated. Data augmentation techniques were employed to improve the networks' generalization ability and selective sampling was implemented to handle class imbalance. The predictions of the models were clustered using a connected component analysis. The system was trained on ten annotated scans and evaluated on an independent test set of eight scans. Despite this limited data set, the system reached a sensitivity of 0.87 at 16.75 false positives per scan (2.5 false positives per CMB), outperforming related work on CMB detection in TBI patients.

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.

Hyperspectral imaging for melanoma screening

NASA Astrophysics Data System (ADS)

Martin, Justin; Krueger, James; Gareau, Daniel

2014-03-01

The 5-year survival rate for patients diagnosed with Melanoma, a deadly form of skin cancer, in its latest stages is about 15%, compared to over 90% for early detection and treatment. We present an imaging system and algorithm that can be used to automatically generate a melanoma risk score to aid clinicians in the early identification of this form of skin cancer. Our system images the patient's skin at a series of different wavelengths and then analyzes several key dermoscopic features to generate this risk score. We have found that shorter wavelengths of light are sensitive to information in the superficial areas of the skin while longer wavelengths can be used to gather information at greater depths. This accompanying diagnostic computer algorithm has demonstrated much higher sensitivity and specificity than the currently commercialized system in preliminary trials and has the potential to improve the early detection of melanoma.

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

Computer aided diagnosis of diabetic peripheral neuropathy

NASA Astrophysics Data System (ADS)

Chekh, Viktor; Soliz, Peter; McGrew, Elizabeth; Barriga, Simon; Burge, Mark; Luan, Shuang

2014-03-01

Diabetic peripheral neuropathy (DPN) refers to the nerve damage that can occur in diabetes patients. It most often affects the extremities, such as the feet, and can lead to peripheral vascular disease, deformity, infection, ulceration, and even amputation. The key to managing diabetic foot is prevention and early detection. Unfortunately, current existing diagnostic techniques are mostly based on patient sensations and exhibit significant inter- and intra-observer differences. We have developed a computer aided diagnostic (CAD) system for diabetic peripheral neuropathy. The thermal response of the feet of diabetic patients following cold stimulus is captured using an infrared camera. The plantar foot in the images from a thermal video are segmented and registered for tracking points or specific regions. The temperature recovery of each point on the plantar foot is extracted using our bio-thermal model and analyzed. The regions that exhibit abnormal ability to recover are automatically identified to aid the physicians to recognize problematic areas. The key to our CAD system is the segmentation of infrared video. The main challenges for segmenting infrared video compared to normal digital video are (1) as the foot warms up, it also warms up the surrounding, creating an ever changing contrast; and (2) there may be significant motion during imaging. To overcome this, a hybrid segmentation algorithm was developed based on a number of techniques such as continuous max-flow, model based segmentation, shape preservation, convex hull, and temperature normalization. Verifications of the automatic segmentation and registration using manual segmentation and markers show good agreement.

The integration of automated knowledge acquisition with computer-aided software engineering for space shuttle expert systems

NASA Technical Reports Server (NTRS)

Modesitt, Kenneth L.

1990-01-01

A prediction was made that the terms expert systems and knowledge acquisition would begin to disappear over the next several years. This is not because they are falling into disuse; it is rather that practitioners are realizing that they are valuable adjuncts to software engineering, in terms of problem domains addressed, user acceptance, and in development methodologies. A specific problem was discussed, that of constructing an automated test analysis system for the Space Shuttle Main Engine. In this domain, knowledge acquisition was part of requirements systems analysis, and was performed with the aid of a powerful inductive ESBT in conjunction with a computer aided software engineering (CASE) tool. The original prediction is not a very risky one -- it has already been accomplished.

ACSYNT - A standards-based system for parametric, computer aided conceptual design of aircraft

NASA Technical Reports Server (NTRS)

Jayaram, S.; Myklebust, A.; Gelhausen, P.

1992-01-01

A group of eight US aerospace companies together with several NASA and NAVY centers, led by NASA Ames Systems Analysis Branch, and Virginia Tech's CAD Laboratory agreed, through the assistance of Americal Technology Initiative, in 1990 to form the ACSYNT (Aircraft Synthesis) Institute. The Institute is supported by a Joint Sponsored Research Agreement to continue the research and development in computer aided conceptual design of aircraft initiated by NASA Ames Research Center and Virginia Tech's CAD Laboratory. The result of this collaboration, a feature-based, parametric computer aided aircraft conceptual design code called ACSYNT, is described. The code is based on analysis routines begun at NASA Ames in the early 1970's. ACSYNT's CAD system is based entirely on the ISO standard Programmer's Hierarchical Interactive Graphics System and is graphics-device independent. The code includes a highly interactive graphical user interface, automatically generated Hermite and B-Spline surface models, and shaded image displays. Numerous features to enhance aircraft conceptual design are described.

NDE: A key to engine rotor life prediction

NASA Technical Reports Server (NTRS)

Doherty, J. E.

1977-01-01

A key ingredient in the establishment of safe life times for critical components is the means of reliably detecting flaws which may potentially exist. Currently used nondestructive evaluation procedures are successful in detecting life limiting defects; however, the development of automated and computer aided NDE technology permits even greater assurance of flight safety.

Reliability model derivation of a fault-tolerant, dual, spare-switching, digital computer system

NASA Technical Reports Server (NTRS)

1974-01-01

A computer based reliability projection aid, tailored specifically for application in the design of fault-tolerant computer systems, is described. Its more pronounced characteristics include the facility for modeling systems with two distinct operational modes, measuring the effect of both permanent and transient faults, and calculating conditional system coverage factors. The underlying conceptual principles, mathematical models, and computer program implementation are presented.

The robot's eyes - Stereo vision system for automated scene analysis

NASA Technical Reports Server (NTRS)

Williams, D. S.

1977-01-01

Attention is given to the robot stereo vision system which maintains the image produced by solid-state detector television cameras in a dynamic random access memory called RAPID. The imaging hardware consists of sensors (two solid-state image arrays using a charge injection technique), a video-rate analog-to-digital converter, the RAPID memory, and various types of computer-controlled displays, and preprocessing equipment (for reflexive actions, processing aids, and object detection). The software is aimed at locating objects and transversibility. An object-tracking algorithm is discussed and it is noted that tracking speed is in the 50-75 pixels/s range.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Jianfei; Wang, Shijun; Turkbey, Evrim B.

Purpose: Renal calculi are common extracolonic incidental findings on computed tomographic colonography (CTC). This work aims to develop a fully automated computer-aided diagnosis system to accurately detect renal calculi on CTC images. Methods: The authors developed a total variation (TV) flow method to reduce image noise within the kidneys while maintaining the characteristic appearance of renal calculi. Maximally stable extremal region (MSER) features were then calculated to robustly identify calculi candidates. Finally, the authors computed texture and shape features that were imported to support vector machines for calculus classification. The method was validated on a dataset of 192 patients andmore » compared to a baseline approach that detects calculi by thresholding. The authors also compared their method with the detection approaches using anisotropic diffusion and nonsmoothing. Results: At a false positive rate of 8 per patient, the sensitivities of the new method and the baseline thresholding approach were 69% and 35% (p < 1e − 3) on all calculi from 1 to 433 mm{sup 3} in the testing dataset. The sensitivities of the detection methods using anisotropic diffusion and nonsmoothing were 36% and 0%, respectively. The sensitivity of the new method increased to 90% if only larger and more clinically relevant calculi were considered. Conclusions: Experimental results demonstrated that TV-flow and MSER features are efficient means to robustly and accurately detect renal calculi on low-dose, high noise CTC images. Thus, the proposed method can potentially improve diagnosis.« less

Space Derived Health Aids (AID, Heart Monitor)

NASA Technical Reports Server (NTRS)

1981-01-01

CPI's spinoff from miniaturized pace circuitry is the new heart-assist device, the AID implantable automatic pulse generator. AID pulse generator monitors the heart continuously, recognizes onset of fibrillation, then administers a corrective electrical shock. A mini- computer, a power source, and two electrodes which sense heart activity are included in the unit. An associated system was also developed. It includes an external recorder to be worn by AID patients and a physician's console to display the data stored by the recorder. System provides a record of fibrillation occurrences and the ensuing defibrillation.

Expert Systems: Tutors, Tools, and Tutees.

ERIC Educational Resources Information Center

Lippert, Renate C.

1989-01-01

Discusses the current status, research, and practical implications of artificial intelligence and expert systems in education. Topics discussed include computer-assisted instruction; intelligent computer-assisted instruction; intelligent tutoring systems; instructional strategies involving the creation of knowledge bases; decision aids;…

Automated detection of pulmonary nodules in CT images with support vector machines

NASA Astrophysics Data System (ADS)

Liu, Lu; Liu, Wanyu; Sun, Xiaoming

2008-10-01

Many methods have been proposed to avoid radiologists fail to diagnose small pulmonary nodules. Recently, support vector machines (SVMs) had received an increasing attention for pattern recognition. In this paper, we present a computerized system aimed at pulmonary nodules detection; it identifies the lung field, extracts a set of candidate regions with a high sensitivity ratio and then classifies candidates by the use of SVMs. The Computer Aided Diagnosis (CAD) system presented in this paper supports the diagnosis of pulmonary nodules from Computed Tomography (CT) images as inflammation, tuberculoma, granuloma..sclerosing hemangioma, and malignant tumor. Five texture feature sets were extracted for each lesion, while a genetic algorithm based feature selection method was applied to identify the most robust features. The selected feature set was fed into an ensemble of SVMs classifiers. The achieved classification performance was 100%, 92.75% and 90.23% in the training, validation and testing set, respectively. It is concluded that computerized analysis of medical images in combination with artificial intelligence can be used in clinical practice and may contribute to more efficient diagnosis.

3D Surgical Simulation

PubMed Central

Cevidanes, Lucia; Tucker, Scott; Styner, Martin; Kim, Hyungmin; Chapuis, Jonas; Reyes, Mauricio; Proffit, William; Turvey, Timothy; Jaskolka, Michael

2009-01-01

This paper discusses the development of methods for computer-aided jaw surgery. Computer-aided jaw surgery allows us to incorporate the high level of precision necessary for transferring virtual plans into the operating room. We also present a complete computer-aided surgery (CAS) system developed in close collaboration with surgeons. Surgery planning and simulation include construction of 3D surface models from Cone-beam CT (CBCT), dynamic cephalometry, semi-automatic mirroring, interactive cutting of bone and bony segment repositioning. A virtual setup can be used to manufacture positioning splints for intra-operative guidance. The system provides further intra-operative assistance with the help of a computer display showing jaw positions and 3D positioning guides updated in real-time during the surgical procedure. The CAS system aids in dealing with complex cases with benefits for the patient, with surgical practice, and for orthodontic finishing. Advanced software tools for diagnosis and treatment planning allow preparation of detailed operative plans, osteotomy repositioning, bone reconstructions, surgical resident training and assessing the difficulties of the surgical procedures prior to the surgery. CAS has the potential to make the elaboration of the surgical plan a more flexible process, increase the level of detail and accuracy of the plan, yield higher operative precision and control, and enhance documentation of cases. Supported by NIDCR DE017727, and DE018962 PMID:20816308

Proceedings of the 1993 Conference on Intelligent Computer-Aided Training and Virtual Environment Technology

NASA Technical Reports Server (NTRS)

Hyde, Patricia R.; Loftin, R. Bowen

1993-01-01

The volume 2 proceedings from the 1993 Conference on Intelligent Computer-Aided Training and Virtual Environment Technology are presented. Topics discussed include intelligent computer assisted training (ICAT) systems architectures, ICAT educational and medical applications, virtual environment (VE) training and assessment, human factors engineering and VE, ICAT theory and natural language processing, ICAT military applications, VE engineering applications, ICAT knowledge acquisition processes and applications, and ICAT aerospace applications.

Facilitating Integration of Electron Beam Lithography Devices with Interactive Videodisc, Computer-Based Simulation and Job Aids.

ERIC Educational Resources Information Center

Von Der Linn, Robert Christopher

A needs assessment of the Grumman E-Beam Systems Group identified the requirement for additional skill mastery for the engineers who assemble, integrate, and maintain devices used to manufacture integrated circuits. Further analysis of the tasks involved led to the decision to develop interactive videodisc, computer-based job aids to enable…

Virtual Reality-Based Technologies in Dental Medicine: Knowledge, Attitudes and Practice among Students and Practitioners

ERIC Educational Resources Information Center

Sabalic, Maja; Schoener, Jason D.

2017-01-01

Virtual reality-based technologies have been used in dentistry for almost two decades. Dental simulators, planning software and CAD/CAM (computer-aided design/computer-aided manufacturing) systems have significantly developed over the years and changed both dental education and clinical practice. This study aimed to assess the knowledge, attitudes…

Caesy: A software tool for computer-aided engineering

NASA Technical Reports Server (NTRS)

Wette, Matt

1993-01-01

A new software tool, Caesy, is described. This tool provides a strongly typed programming environment for research in the development of algorithms and software for computer-aided control system design. A description of the user language and its implementation as they currently stand are presented along with a description of work in progress and areas of future work.

A Selective Bibliography of Building Environment and Service Systems with Particular Reference to Computer Applications. Computer Report CR20.

ERIC Educational Resources Information Center

Forwood, Bruce S.

This bibliography has been produced as part of a research program attempting to develop a new approach to building environment and service systems design using computer-aided design techniques. As such it not only classifies available literature on the service systems themselves, but also contains sections on the application of computers and…

Recent development on computer aided tissue engineering--a review.

PubMed

Sun, Wei; Lal, Pallavi

2002-02-01

The utilization of computer-aided technologies in tissue engineering has evolved in the development of a new field of computer-aided tissue engineering (CATE). This article reviews recent development and application of enabling computer technology, imaging technology, computer-aided design and computer-aided manufacturing (CAD and CAM), and rapid prototyping (RP) technology in tissue engineering, particularly, in computer-aided tissue anatomical modeling, three-dimensional (3-D) anatomy visualization and 3-D reconstruction, CAD-based anatomical modeling, computer-aided tissue classification, computer-aided tissue implantation and prototype modeling assisted surgical planning and reconstruction.

Computer-aided system design

NASA Technical Reports Server (NTRS)

Walker, Carrie K.

1991-01-01

A technique has been developed for combining features of a systems architecture design and assessment tool and a software development tool. This technique reduces simulation development time and expands simulation detail. The Architecture Design and Assessment System (ADAS), developed at the Research Triangle Institute, is a set of computer-assisted engineering tools for the design and analysis of computer systems. The ADAS system is based on directed graph concepts and supports the synthesis and analysis of software algorithms mapped to candidate hardware implementations. Greater simulation detail is provided by the ADAS functional simulator. With the functional simulator, programs written in either Ada or C can be used to provide a detailed description of graph nodes. A Computer-Aided Software Engineering tool developed at the Charles Stark Draper Laboratory (CSDL CASE) automatically generates Ada or C code from engineering block diagram specifications designed with an interactive graphical interface. A technique to use the tools together has been developed, which further automates the design process.

29 CFR 541.401 - Computer manufacture and repair.

Code of Federal Regulations, 2011 CFR

2011-07-01

... DEFINING AND DELIMITING THE EXEMPTIONS FOR EXECUTIVE, ADMINISTRATIVE, PROFESSIONAL, COMPUTER AND OUTSIDE..., the use of computers and computer software programs (e.g., engineers, drafters and others skilled in computer-aided design software), but who are not primarily engaged in computer systems analysis and...

Models and techniques for evaluating the effectiveness of aircraft computing systems

NASA Technical Reports Server (NTRS)

Meyer, J. F.

1978-01-01

Progress in the development of system models and techniques for the formulation and evaluation of aircraft computer system effectiveness is reported. Topics covered include: analysis of functional dependence: a prototype software package, METAPHOR, developed to aid the evaluation of performability; and a comprehensive performability modeling and evaluation exercise involving the SIFT computer.

Surface Modeling, Solid Modeling and Finite Element Modeling. Analysis Capabilities of Computer-Assisted Design and Manufacturing Systems.

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)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hentschke, Clemens M., E-mail: clemens.hentschke@gmail.com; Tönnies, Klaus D.; Beuing, Oliver

Purpose: The early detection of cerebral aneurysms plays a major role in preventing subarachnoid hemorrhage. The authors present a system to automatically detect cerebral aneurysms in multimodal 3D angiographic data sets. The authors’ system is parametrizable for contrast-enhanced magnetic resonance angiography (CE-MRA), time-of-flight magnetic resonance angiography (TOF-MRA), and computed tomography angiography (CTA). Methods: Initial volumes of interest are found by applying a multiscale sphere-enhancing filter. Several features are combined in a linear discriminant function (LDF) to distinguish between true aneurysms and false positives. The features include shape information, spatial information, and probability information. The LDF can either be parametrized bymore » domain experts or automatically by training. Vessel segmentation is avoided as it could heavily influence the detection algorithm. Results: The authors tested their method with 151 clinical angiographic data sets containing 112 aneurysms. The authors reach a sensitivity of 95% with CE-MRA data sets at an average false positive rate per data set (FP{sub DS}) of 8.2. For TOF-MRA, we achieve 95% sensitivity at 11.3 FP{sub DS}. For CTA, we reach a sensitivity of 95% at 22.8 FP{sub DS}. For all modalities, the expert parametrization led to similar or better results than the trained parametrization eliminating the need for training. 93% of aneurysms that were smaller than 5 mm were found. The authors also showed that their algorithm is capable of detecting aneurysms that were previously overlooked by radiologists. Conclusions: The authors present an automatic system to detect cerebral aneurysms in multimodal angiographic data sets. The system proved as a suitable computer-aided detection tool to help radiologists find cerebral aneurysms.« less

Assessment of Chair-side Computer-Aided Design and Computer-Aided Manufacturing Restorations: A Review of the Literature

PubMed Central

Baroudi, Kusai; Ibraheem, Shukran Nasser

2015-01-01

Background: This paper aimed to evaluate the application of computer-aided design and computer-aided manufacturing (CAD-CAM) technology and the factors that affect the survival of restorations. Materials and Methods: A thorough literature search using PubMed, Medline, Embase, Science Direct, Wiley Online Library and Grey literature were performed from the year 2004 up to June 2014. Only relevant research was considered. Results: The use of chair-side CAD/CAM systems is promising in all dental branches in terms of minimizing time and effort made by dentists, technicians and patients for restoring and maintaining patient oral function and aesthetic, while providing high quality outcome. Conclusion: The way of producing and placing the restorations made with the chair-side CAD/CAM (CEREC and E4D) devices is better than restorations made by conventional laboratory procedures. PMID:25954082

Detection of endoscopic looping during colonoscopy procedure by using embedded bending sensors

PubMed Central

Bruce, Michael; Choi, JungHun

2018-01-01

Background Looping of the colonoscope shaft during procedure is one of the most common obstacles encountered by colonoscopists. It occurs in 91% of cases with the N-sigmoid loop being the most common, occurring in 79% of cases. Purpose Herein, a novel system is developed that will give a complete three-dimensional (3D) vector image of the shaft as it passes through the colon, to aid the colonoscopist in detecting loops before they form. Patients and methods A series of connected links spans the middle 50% of the shaft, where loops are likely to form. Two potentiometers are attached at each joint to measure angular deflection in two directions to allow for 3D positioning. This 3D positioning is converted into a 3D vector image using computer software. MATLAB software has been used to display the image on a computer monitor. For the different configuration of the colon model, the system determined the looping status. Results Different configurations (N loop, reverse gamma loop, and reverse splenic flexure) of the loops were well defined using 3D vector image. Conclusion The novel sensory system can accurately define the various configuration of the colon during the colonoscopy procedure. PMID:29849469

Automatic Classification of Specific Melanocytic Lesions Using Artificial Intelligence

PubMed Central

Jaworek-Korjakowska, Joanna; Kłeczek, Paweł

2016-01-01

Background. Given its propensity to metastasize, and lack of effective therapies for most patients with advanced disease, early detection of melanoma is a clinical imperative. Different computer-aided diagnosis (CAD) systems have been proposed to increase the specificity and sensitivity of melanoma detection. Although such computer programs are developed for different diagnostic algorithms, to the best of our knowledge, a system to classify different melanocytic lesions has not been proposed yet. Method. In this research we present a new approach to the classification of melanocytic lesions. This work is focused not only on categorization of skin lesions as benign or malignant but also on specifying the exact type of a skin lesion including melanoma, Clark nevus, Spitz/Reed nevus, and blue nevus. The proposed automatic algorithm contains the following steps: image enhancement, lesion segmentation, feature extraction, and selection as well as classification. Results. The algorithm has been tested on 300 dermoscopic images and achieved accuracy of 92% indicating that the proposed approach classified most of the melanocytic lesions correctly. Conclusions. A proposed system can not only help to precisely diagnose the type of the skin mole but also decrease the amount of biopsies and reduce the morbidity related to skin lesion excision. PMID:26885520

Automatic Classification of Specific Melanocytic Lesions Using Artificial Intelligence.

PubMed

Jaworek-Korjakowska, Joanna; Kłeczek, Paweł

2016-01-01

Given its propensity to metastasize, and lack of effective therapies for most patients with advanced disease, early detection of melanoma is a clinical imperative. Different computer-aided diagnosis (CAD) systems have been proposed to increase the specificity and sensitivity of melanoma detection. Although such computer programs are developed for different diagnostic algorithms, to the best of our knowledge, a system to classify different melanocytic lesions has not been proposed yet. In this research we present a new approach to the classification of melanocytic lesions. This work is focused not only on categorization of skin lesions as benign or malignant but also on specifying the exact type of a skin lesion including melanoma, Clark nevus, Spitz/Reed nevus, and blue nevus. The proposed automatic algorithm contains the following steps: image enhancement, lesion segmentation, feature extraction, and selection as well as classification. The algorithm has been tested on 300 dermoscopic images and achieved accuracy of 92% indicating that the proposed approach classified most of the melanocytic lesions correctly. A proposed system can not only help to precisely diagnose the type of the skin mole but also decrease the amount of biopsies and reduce the morbidity related to skin lesion excision.

CTN summary of DSREDS, EDCARS, EDMICS CALS readiness testing. [Computer-aided Acquisition and Logistic Support (CALS) CALS Test Network (CTN), Digital Storage Retrieval Eng. Data System (DSREDS), Eng. Data Computer Assisted Retrieval System (EDCARS), Eng. Data Management Information and Control System (EDMICS)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mitschkowetz, N.; Vickers, D.L.

This report provides a summary of the Computer-aided Acquisition and Logistic Support (CALS) Test Network (CTN) Laboratory Acceptance Test (LAT) and User Application Test (UAT) activities undertaken to evaluate the CALS capabilities being implemented as part of the Department of Defense (DOD) engineering repositories. Although the individual testing activities provided detailed reports for each repository, a synthesis of the results, conclusions, and recommendations is offered to provide a more concise presentation of the issues and the strategies, as viewed from the CTN perspective.

Integrating computer programs for engineering analysis and design

NASA Technical Reports Server (NTRS)

Wilhite, A. W.; Crisp, V. K.; Johnson, S. C.

1983-01-01

The design of a third-generation system for integrating computer programs for engineering and design has been developed for the Aerospace Vehicle Interactive Design (AVID) system. This system consists of an engineering data management system, program interface software, a user interface, and a geometry system. A relational information system (ARIS) was developed specifically for the computer-aided engineering system. It is used for a repository of design data that are communicated between analysis programs, for a dictionary that describes these design data, for a directory that describes the analysis programs, and for other system functions. A method is described for interfacing independent analysis programs into a loosely-coupled design system. This method emphasizes an interactive extension of analysis techniques and manipulation of design data. Also, integrity mechanisms exist to maintain database correctness for multidisciplinary design tasks by an individual or a team of specialists. Finally, a prototype user interface program has been developed to aid in system utilization.

Data engineering systems: Computerized modeling and data bank capabilities for engineering analysis

NASA Technical Reports Server (NTRS)

Kopp, H.; Trettau, R.; Zolotar, B.

1984-01-01

The Data Engineering System (DES) is a computer-based system that organizes technical data and provides automated mechanisms for storage, retrieval, and engineering analysis. The DES combines the benefits of a structured data base system with automated links to large-scale analysis codes. While the DES provides the user with many of the capabilities of a computer-aided design (CAD) system, the systems are actually quite different in several respects. A typical CAD system emphasizes interactive graphics capabilities and organizes data in a manner that optimizes these graphics. On the other hand, the DES is a computer-aided engineering system intended for the engineer who must operationally understand an existing or planned design or who desires to carry out additional technical analysis based on a particular design. The DES emphasizes data retrieval in a form that not only provides the engineer access to search and display the data but also links the data automatically with the computer analysis codes.

Student Financial Aid Delivery System.

ERIC Educational Resources Information Center

O'Neal, John R.; Carpenter, Catharine A.

1983-01-01

Ohio University's use of computer programing for the need analysis and internal accounting functions in financial aid is described. A substantial improvement of services resulted, with 6,000-10,000 students and the offices of financial aid, bursar, registration, student records, housing, admissions, and controller assisted in the process. Costs…

Can computer-aided diagnosis (CAD) help radiologists find mammographically missed screening cancers?

NASA Astrophysics Data System (ADS)

Nishikawa, Robert M.; Giger, Maryellen L.; Schmidt, Robert A.; Papaioannou, John

2001-06-01

We present data from a pilot observer study whose goal is design a study to test the hypothesis that computer-aided diagnosis (CAD) can improve radiologists' performance in reading screening mammograms. In a prospective evaluation of our computer detection schemes, we have analyzed over 12,000 clinical exams. Retrospective review of the negative screening mammograms for all cancer cases found an indication of the cancer in 23 of these negative cases. The computer found 54% of these in our prospective testing. We added to these cases normal exams to create a dataset of 75 cases. Four radiologists experienced in mammography read the cases and gave their BI-RADS assessment and their confidence that the patient should be called back for diagnostic mammography. They did so once reading the films only and a second time reading with the computer aid. Three radiologists had no change in area under the ROC curve (mean Az of 0.73) and one improved from 0.73 to 0.78, but this difference failed to reach statistical significance (p equals 0.23). These data are being used to plan a larger more powerful study.

Developing a Computer Touch-Screen Interactive Colorectal Screening Decision Aid for a Low-Literacy African American Population: Lessons Learned

PubMed Central

Bass, Sarah Bauerle; Gordon, Thomas F.; Ruzek, Sheryl Burt; Wolak, Caitlin; Ruggieri, Dominique; Mora, Gabriella; Rovito, Michael J.; Britto, Johnson; Parameswaran, Lalitha; Abedin, Zainab; Ward, Stephanie; Paranjape, Anuradha; Lin, Karen; Meyer, Brian; Pitts, Khaliah

2017-01-01

African Americans have higher colorectal cancer (CRC) mortality than White Americans and yet have lower rates of CRC screening. Increased screening aids in early detection and higher survival rates. Coupled with low literacy rates, the burden of CRC morbidity and mortality is exacerbated in this population, making it important to develop culturally and literacy appropriate aids to help low-literacy African Americans make informed decisions about CRC screening. This article outlines the development of a low-literacy computer touch-screen colonoscopy decision aid using an innovative marketing method called perceptual mapping and message vector modeling. This method was used to mathematically model key messages for the decision aid, which were then used to modify an existing CRC screening tutorial with different messages. The final tutorial was delivered through computer touch-screen technology to increase access and ease of use for participants. Testing showed users were not only more comfortable with the touch-screen technology but were also significantly more willing to have a colonoscopy compared with a “usual care group.” Results confirm the importance of including participants in planning and that the use of these innovative mapping and message design methods can lead to significant CRC screening attitude change. PMID:23132838

Getting Mental Models and Computer Models to Cooperate

NASA Technical Reports Server (NTRS)

Sheridan, T. B.; Roseborough, J.; Charney, L.; Mendel, M.

1984-01-01

A qualitative theory of supervisory control is outlined wherein the mental models of one or more human operators are related to the knowledge representations within automatic controllers (observers, estimators) and operator decision aids (expert systems, advice-givers). Methods of quantifying knowledge and the calibration of one knowledge representation to another (human, computer, or objective truth) are discussed. Ongoing experiments in the use of decision aids for exploring one's own objective function or exploring system constraints and control strategies are described.

Computer-Aided Remote Driving

NASA Technical Reports Server (NTRS)

Wilcox, Brian H.

1994-01-01

System for remote control of robotic land vehicle requires only small radio-communication bandwidth. Twin video cameras on vehicle create stereoscopic images. Operator views cross-polarized images on two cathode-ray tubes through correspondingly polarized spectacles. By use of cursor on frozen image, remote operator designates path. Vehicle proceeds to follow path, by use of limited degree of autonomous control to cope with unexpected conditions. System concept, called "computer-aided remote driving" (CARD), potentially useful in exploration of other planets, military surveillance, firefighting, and clean-up of hazardous materials.

Applying a new computer-aided detection scheme generated imaging marker to predict short-term breast cancer risk

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.

Comprehensive automatic assessment of retinal vascular abnormalities for computer-assisted retinopathy grading.

PubMed

Joshi, Vinayak; Agurto, Carla; VanNess, Richard; Nemeth, Sheila; Soliz, Peter; Barriga, Simon

2014-01-01

One of the most important signs of systemic disease that presents on the retina is vascular abnormalities such as in hypertensive retinopathy. Manual analysis of fundus images by human readers is qualitative and lacks in accuracy, consistency and repeatability. Present semi-automatic methods for vascular evaluation are reported to increase accuracy and reduce reader variability, but require extensive reader interaction; thus limiting the software-aided efficiency. Automation thus holds a twofold promise. First, decrease variability while increasing accuracy, and second, increasing the efficiency. In this paper we propose fully automated software as a second reader system for comprehensive assessment of retinal vasculature; which aids the readers in the quantitative characterization of vessel abnormalities in fundus images. This system provides the reader with objective measures of vascular morphology such as tortuosity, branching angles, as well as highlights of areas with abnormalities such as artery-venous nicking, copper and silver wiring, and retinal emboli; in order for the reader to make a final screening decision. To test the efficacy of our system, we evaluated the change in performance of a newly certified retinal reader when grading a set of 40 color fundus images with and without the assistance of the software. The results demonstrated an improvement in reader's performance with the software assistance, in terms of accuracy of detection of vessel abnormalities, determination of retinopathy, and reading time. This system enables the reader in making computer-assisted vasculature assessment with high accuracy and consistency, at a reduced reading time.

A computer-aided movement analysis system.

PubMed

Fioretti, S; Leo, T; Pisani, E; Corradini, M L

1990-08-01

Interaction with biomechanical data concerning human movement analysis implies the adoption of various experimental equipments and the choice of suitable models, data processing, and graphical data restitution techniques. The integration of measurement setups with the associated experimental protocols and the relative software procedures constitutes a computer-aided movement analysis (CAMA) system. In the present paper such integration is mapped onto the causes that limit the clinical acceptance of movement analysis methods. The structure of the system is presented. A specific CAMA system devoted to posture analysis is described in order to show the attainable features. Scientific results obtained with the support of the described system are also reported.

Decision support systems for ecosystem management: An evaluation of existing systems

Treesearch

H. Todd Mowrer; Klaus Barber; Joe Campbell; Nick Crookston; Cathy Dahms; John Day; Jim Laacke; Jim Merzenich; Steve Mighton; Mike Rauscher; Rick Sojda; Joyce Thompson; Peter Trenchi; Mark Twery

1997-01-01

This report evaluated 24 computer-aided decision support systems (DSS) that can support management decision-making in forest ecosystems. It compares the scope of each system, spatial capabilities, computational methods, development status, input and output requirements, user support availability, and system performance. Questionnaire responses from the DSS developers (...

Automatic lung nodule graph cuts segmentation with deep learning false positive reduction

NASA Astrophysics Data System (ADS)

Sun, Wenqing; Huang, Xia; Tseng, Tzu-Liang Bill; Qian, Wei

2017-03-01

To automatic detect lung nodules from CT images, we designed a two stage computer aided detection (CAD) system. The first stage is graph cuts segmentation to identify and segment the nodule candidates, and the second stage is convolutional neural network for false positive reduction. The dataset contains 595 CT cases randomly selected from Lung Image Database Consortium and Image Database Resource Initiative (LIDC/IDRI) and the 305 pulmonary nodules achieved diagnosis consensus by all four experienced radiologists were our detection targets. Consider each slice as an individual sample, 2844 nodules were included in our database. The graph cuts segmentation was conducted in a two-dimension manner, 2733 lung nodule ROIs are successfully identified and segmented. With a false positive reduction by a seven-layer convolutional neural network, 2535 nodules remain detected while the false positive dropped to 31.6%. The average F-measure of segmented lung nodule tissue is 0.8501.

Automated detection of microcalcification clusters in mammograms

NASA Astrophysics Data System (ADS)

Karale, Vikrant A.; Mukhopadhyay, Sudipta; Singh, Tulika; Khandelwal, Niranjan; Sadhu, Anup

2017-03-01

Mammography is the most efficient modality for detection of breast cancer at early stage. Microcalcifications are tiny bright spots in mammograms and can often get missed by the radiologist during diagnosis. The presence of microcalcification clusters in mammograms can act as an early sign of breast cancer. This paper presents a completely automated computer-aided detection (CAD) system for detection of microcalcification clusters in mammograms. Unsharp masking is used as a preprocessing step which enhances the contrast between microcalcifications and the background. The preprocessed image is thresholded and various shape and intensity based features are extracted. Support vector machine (SVM) classifier is used to reduce the false positives while preserving the true microcalcification clusters. The proposed technique is applied on two different databases i.e DDSM and private database. The proposed technique shows good sensitivity with moderate false positives (FPs) per image on both databases.

Computer aided detection system for Osteoporosis using low dose thoracic 3D CT images

NASA Astrophysics Data System (ADS)

Tsuji, Daisuke; Matsuhiro, Mikio; Suzuki, Hidenobu; Kawata, Yoshiki; Niki, Noboru; Nakano, Yasutaka; Harada, Masafumi; Kusumoto, Masahiko; Tsuchida, Takaaki; Eguchi, Kenji; Kaneko, Masahiro

2018-02-01

The patient of osteoporosis is about 13 million people in Japan and it is one of healthy life problems in the aging society. It is necessary to do early stage detection and treatment in order to prevent the osteoporosis. Multi-slice CT technology has been improving the three dimensional (3D) image analysis with higher resolution and shorter scan time. The 3D image analysis of thoracic vertebra can be used for supporting to diagnosis of osteoporosis. This analysis can be used for lung cancer detection at the same time. We develop method of shape analysis and CT values of spongy bone for the detection osteoporosis. Osteoporosis and lung cancer screening show high extraction rate by the thoracic vertebral evaluation CT images. In addition, we created standard pattern of CT value per thoracic vertebra for male age group using 298 low dose data.

Clustering microcalcifications techniques in digital mammograms

NASA Astrophysics Data System (ADS)

Díaz, Claudia. C.; Bosco, Paolo; Cerello, Piergiorgio

2008-11-01

Breast cancer has become a serious public health problem around the world. However, this pathology can be treated if it is detected in early stages. This task is achieved by a radiologist, who should read a large amount of mammograms per day, either for a screening or diagnostic purpose in mammography. However human factors could affect the diagnosis. Computer Aided Detection is an automatic system, which can help to specialists in the detection of possible signs of malignancy in mammograms. Microcalcifications play an important role in early detection, so we focused on their study. The two mammographic features that indicate the microcalcifications could be probably malignant are small size and clustered distribution. We worked with density techniques for automatic clustering, and we applied them on a mammography CAD prototype developed at INFN-Turin, Italy. An improvement of performance is achieved analyzing images from a Perugia-Assisi Hospital, in Italy.

Computer Aided Conceptual Design of Submarines

DTIC Science & Technology

1984-06-01

Department 5f i ngi eering . May 19134 Certified by: Thesi Supervisor Accepted Y.’.I Cr’rman, (IeaV gineer ing Departmental Comimitte C - nuusý"(Xwa has...the equilibrium polygon. The Package interfaces with a pressure hull design module developed separately in an O.E. thesis by Marvin Meade. Interactive...computers or computer aided design systems. c- A𔃺ccession -or4 Thesis Supervisor: Dr. David V. Burke NI R~ Title: Professor of Ocean Engineering DTIC

A Fully Distributed Approach to the Design of a KBIT/SEC VHF Packet Radio Network,

DTIC Science & Technology

1984-02-01

topological change and consequent out-modea routing data. Algorithm development has been aided by computer simulation using a finite state machine technique...development has been aided by computer simulation using a finite state machine technique to model a realistic network of up to fifty nodes. This is...use of computer based equipments in weapons systems and their associated sensors and command and control elements and the trend from voice to data

A novel computer system for the evaluation of nasolabial morphology, symmetry and aesthetics after cleft lip and palate treatment. Part 1: General concept and validation.

PubMed

Pietruski, Piotr; Majak, Marcin; Debski, Tomasz; Antoszewski, Boguslaw

2017-04-01

The need for a widely accepted method suitable for a multicentre quantitative evaluation of facial aesthetics after surgical treatment of cleft lip and palate (CLP) has been emphasized for years. The aim of this study was to validate a novel computer system 'Analyse It Doc' (A.I.D.) as a tool for objective anthropometric analysis of the nasolabial region. An indirect anthropometric analysis of facial photographs was conducted with the A.I.D. system and Adobe Photoshop/ImageJ software. Intra-rater and inter-rater reliability and the time required for the analysis were estimated separately for each method and compared. Analysis with A.I.D. system was nearly 10-fold faster than that with the reference evaluation method. The A.I.D. system provided strong inter-rater and intra-rater correlations for linear, angular and area measurements of the nasolabial region, as well as a significantly higher accuracy and reproducibility of angular measurements in submental view. No statistically significant inter-method differences were found for other measurements. The hereby presented novel computer system is suitable for simple, time-efficient and reliable multicenter photogrammetric analyses of the nasolabial region in CLP patients and healthy subjects. Copyright © 2017 European Association for Cranio-Maxillo-Facial Surgery. Published by Elsevier Ltd. All rights reserved.

Computer-aided engineering system for design of sequence arrays and lithographic masks

DOEpatents

Hubbell, Earl A.; Lipshutz, Robert J.; Morris, Macdonald S.; Winkler, James L.

1997-01-01

An improved set of computer tools for forming arrays. According to one aspect of the invention, a computer system is used to select probes and design the layout of an array of DNA or other polymers with certain beneficial characteristics. According to another aspect of the invention, a computer system uses chip design files to design and/or generate lithographic masks.

Computer Aided Design of Computer Generated Holograms for electron beam fabrication

NASA Technical Reports Server (NTRS)

Urquhart, Kristopher S.; Lee, Sing H.; Guest, Clark C.; Feldman, Michael R.; Farhoosh, Hamid

1989-01-01

Computer Aided Design (CAD) systems that have been developed for electrical and mechanical design tasks are also effective tools for the process of designing Computer Generated Holograms (CGHs), particularly when these holograms are to be fabricated using electron beam lithography. CAD workstations provide efficient and convenient means of computing, storing, displaying, and preparing for fabrication many of the features that are common to CGH designs. Experience gained in the process of designing CGHs with various types of encoding methods is presented. Suggestions are made so that future workstations may further accommodate the CGH design process.

Optical tomographic detection of rheumatoid arthritis with computer-aided classification schemes

NASA Astrophysics Data System (ADS)

Klose, Christian D.; Klose, Alexander D.; Netz, Uwe; Beuthan, Jürgen; Hielscher, Andreas H.

2009-02-01

A recent research study has shown that combining multiple parameters, drawn from optical tomographic images, leads to better classification results to identifying human finger joints that are affected or not affected by rheumatic arthritis RA. Building up on the research findings of the previous study, this article presents an advanced computer-aided classification approach for interpreting optical image data to detect RA in finger joints. Additional data are used including, for example, maximum and minimum values of the absorption coefficient as well as their ratios and image variances. Classification performances obtained by the proposed method were evaluated in terms of sensitivity, specificity, Youden index and area under the curve AUC. Results were compared to different benchmarks ("gold standard"): magnet resonance, ultrasound and clinical evaluation. Maximum accuracies (AUC=0.88) were reached when combining minimum/maximum-ratios and image variances and using ultrasound as gold standard.

Computer Aided Drafting Curriculum for Vocational Drafting. A Competency Based Unit of Instruction. Final Report.

ERIC Educational Resources Information Center

Peck, Greg

This document contains (1) the final report of a project to develop a computer-aided drafting (CAD) curriculum and (2) a competency-based unit of instruction for use with the CADAPPLE system. The final report states the problem and project objective, presents conclusions and recommendations, and includes survey instruments. The unit is designed…

Influence of Computer-Aided Assessment on Ways of Working with Mathematics

ERIC Educational Resources Information Center

Rønning, Frode

2017-01-01

This paper is based on an on-going project for modernizing the basic education in mathematics for engineers at the Norwegian University of Science and Technology. One of the components in the project is using a computer-aided assessment system (Maple T.A.) for handling students' weekly hand-ins. Successful completion of a certain number of problem…

Computer-Aided Medical Diagnosis. Literature Review

DTIC Science & Technology

1978-12-15

Croft found a 13% difference in diagnostic accuracy. He considered this difference insignificant in relation to the diagnostic differences caused ...type of diseases diagnosed probably are the major cause of cross-study variability in diagnostic accuracy. The consistency of diagnostic accuracy...REFERENCES ALPEROVITCH, A. and FRAGU, P., A suggestion for an effective use of a computer-aided diagnosis system in screening for hyperthyroidism , Method

NASA Tech Briefs, February 2000. Volume 24, No. 2

NASA Technical Reports Server (NTRS)

2000-01-01

Topics covered include: Test and Measurement; Computer-Aided Design and Engineering; Electronic Components and Circuits; Electronic Systems; Physical Sciences; Materials; Computer Programs; Mechanics; Bio-Medical; Mathematics and Information Sciences; Computers and Peripherals.

A computer-aided diagnosis system to detect pathologies in temporal subtraction images of chest radiographs

NASA Astrophysics Data System (ADS)

Looper, Jared; Harrison, Melanie; Armato, Samuel G.

2016-03-01

Radiologists often compare sequential radiographs to identify areas of pathologic change; however, this process is prone to error, as human anatomy can obscure the regions of change, causing the radiologists to overlook pathology. Temporal subtraction (TS) images can provide enhanced visualization of regions of change in sequential radiographs and allow radiologists to better detect areas of change in radiographs. Not all areas of change shown in TS images, however, are actual pathology. The purpose of this study was to create a computer-aided diagnostic (CAD) system that identifies which regions of change are caused by pathology and which are caused by misregistration of the radiographs used to create the TS image. The dataset used in this study contained 120 images with 74 pathologic regions on 54 images outlined by an experienced radiologist. High and low ("light" and "dark") gray-level candidate regions were extracted from the images using gray-level thresholding. Then, sampling techniques were used to address the class imbalance problem between "true" and "false" candidate regions. Next, the datasets of light candidate regions, dark candidate regions, and the combined set of light and dark candidate regions were used as training and testing data for classifiers by using five-fold cross validation. Of the classifiers tested (support vector machines, discriminant analyses, logistic regression, and k-nearest neighbors), the support vector machine on the combined candidates using synthetic minority oversampling technique (SMOTE) performed best with an area under the receiver operating characteristic curve value of 0.85, a sensitivity of 85%, and a specificity of 84%.

A human visual based binarization technique for histological images

NASA Astrophysics Data System (ADS)

Shreyas, Kamath K. M.; Rajendran, Rahul; Panetta, Karen; Agaian, Sos

2017-05-01

In the field of vision-based systems for object detection and classification, thresholding is a key pre-processing step. Thresholding is a well-known technique for image segmentation. Segmentation of medical images, such as Computed Axial Tomography (CAT), Magnetic Resonance Imaging (MRI), X-Ray, Phase Contrast Microscopy, and Histological images, present problems like high variability in terms of the human anatomy and variation in modalities. Recent advances made in computer-aided diagnosis of histological images help facilitate detection and classification of diseases. Since most pathology diagnosis depends on the expertise and ability of the pathologist, there is clearly a need for an automated assessment system. Histological images are stained to a specific color to differentiate each component in the tissue. Segmentation and analysis of such images is problematic, as they present high variability in terms of color and cell clusters. This paper presents an adaptive thresholding technique that aims at segmenting cell structures from Haematoxylin and Eosin stained images. The thresholded result can further be used by pathologists to perform effective diagnosis. The effectiveness of the proposed method is analyzed by visually comparing the results to the state of art thresholding methods such as Otsu, Niblack, Sauvola, Bernsen, and Wolf. Computer simulations demonstrate the efficiency of the proposed method in segmenting critical information.

Computer-Assisted Classification Patterns in Autoimmune Diagnostics: The AIDA Project

PubMed Central

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

Computer-aided diagnosis of breast cancer via Gabor wavelet bank and binary-class SVM in mammographic images

NASA Astrophysics Data System (ADS)

Torrents-Barrena, Jordina; Puig, Domenec; Melendez, Jaime; Valls, Aida

2016-03-01

Breast cancer is one of the most dangerous diseases that attack women in their 40s worldwide. Due to this fact, it is estimated that one in eight women will develop a malignant carcinoma during their life. In addition, the carelessness of performing regular screenings is an important reason for the increase of mortality. However, computer-aided diagnosis systems attempt to enhance the quality of mammograms as well as the detection of early signs related to the disease. In this paper we propose a bank of Gabor filters to calculate the mean, standard deviation, skewness and kurtosis features by four-sized evaluation windows. Therefore, an active strategy is used to select the most relevant pixels. Finally, a supervised classification stage using two-class support vector machines is utilised through an accurate estimation of kernel parameters. In order to show the development of our methodology based on mammographic image analysis, two main experiments are fulfilled: abnormal/normal breast tissue classification and the ability to detect the different breast cancer types. Moreover, the public screen-film mini-MIAS database is compared with a digitised breast cancer database to evaluate the method robustness. The area under the receiver operating characteristic curve is used to measure the performance of the method. Furthermore, both confusion matrix and accuracy are calculated to assess the results of the proposed algorithm.

Data management and language enhancement for generalized set theory computer language for operation of large relational databases

NASA Technical Reports Server (NTRS)

Finley, Gail T.

1988-01-01

This report covers the study of the relational database implementation in the NASCAD computer program system. The existing system is used primarily for computer aided design. Attention is also directed to a hidden-surface algorithm for final drawing output.

An attempt at the computer-aided management of HIV infection

NASA Astrophysics Data System (ADS)

Ida, A.; Oharu, Y.; Sankey, O.

2007-07-01

The immune system is a complex and diverse system in the human body and HIV virus disrupts and destroys it through extremely complicated but surprisingly logical process. The purpose of this paper is to make an attempt to present a method for the computer-aided management of HIV infection process by means of a mathematical model describing the dynamics of the host pathogen interaction with HIV-1. Treatments for the AIDS disease must be changed to more efficient ones in accordance with the disease progression and the status of the immune system. The level of progression and the status are represented by parameters which are governed by our mathematical model. It is then exhibited that our model is numerically stable and uniquely solvable. With this knowledge, our mathematical model for HIV disease progression is formulated and physiological interpretations are provided. The results of our numerical simulations are visualized, and it is seen that our results agree with medical aspects from the point of view of antiretroviral therapy. It is then expected that our approach will take to address practical clinical issues and will be applied to the computer-aided management of antiretroviral therapies.

A dimension reduction strategy for improving the efficiency of computer-aided detection for CT colonography

NASA Astrophysics Data System (ADS)

Song, Bowen; Zhang, Guopeng; Wang, Huafeng; Zhu, Wei; Liang, Zhengrong

2013-02-01

Various types of features, e.g., geometric features, texture features, projection features etc., have been introduced for polyp detection and differentiation tasks via computer aided detection and diagnosis (CAD) for computed tomography colonography (CTC). Although these features together cover more information of the data, some of them are statistically highly-related to others, which made the feature set redundant and burdened the computation task of CAD. In this paper, we proposed a new dimension reduction method which combines hierarchical clustering and principal component analysis (PCA) for false positives (FPs) reduction task. First, we group all the features based on their similarity using hierarchical clustering, and then PCA is employed within each group. Different numbers of principal components are selected from each group to form the final feature set. Support vector machine is used to perform the classification. The results show that when three principal components were chosen from each group we can achieve an area under the curve of receiver operating characteristics of 0.905, which is as high as the original dataset. Meanwhile, the computation time is reduced by 70% and the feature set size is reduce by 77%. It can be concluded that the proposed method captures the most important information of the feature set and the classification accuracy is not affected after the dimension reduction. The result is promising and further investigation, such as automatically threshold setting, are worthwhile and are under progress.

Accuracy of five intraoral scanners compared to indirect digitalization.

PubMed

Güth, Jan-Frederik; Runkel, Cornelius; Beuer, Florian; Stimmelmayr, Michael; Edelhoff, Daniel; Keul, Christine

2017-06-01

Direct and indirect digitalization offer two options for computer-aided design (CAD)/ computer-aided manufacturing (CAM)-generated restorations. The aim of this study was to evaluate the accuracy of different intraoral scanners and compare them to the process of indirect digitalization. A titanium testing model was directly digitized 12 times with each intraoral scanner: (1) CS 3500 (CS), (2) Zfx Intrascan (ZFX), (3) CEREC AC Bluecam (BLU), (4) CEREC AC Omnicam (OC) and (5) True Definition (TD). As control, 12 polyether impressions were taken and the referring plaster casts were digitized indirectly with the D-810 laboratory scanner (CON). The accuracy (trueness/precision) of the datasets was evaluated by an analysing software (Geomagic Qualify 12.1) using a "best fit alignment" of the datasets with a highly accurate reference dataset of the testing model, received from industrial computed tomography. Direct digitalization using the TD showed the significant highest overall "trueness", followed by CS. Both performed better than CON. BLU, ZFX and OC showed higher differences from the reference dataset than CON. Regarding the overall "precision", the CS 3500 intraoral scanner and the True Definition showed the best performance. CON, BLU and OC resulted in significantly higher precision than ZFX did. Within the limitations of this in vitro study, the accuracy of the ascertained datasets was dependent on the scanning system. The direct digitalization was not superior to indirect digitalization for all tested systems. Regarding the accuracy, all tested intraoral scanning technologies seem to be able to reproduce a single quadrant within clinical acceptable accuracy. However, differences were detected between the tested systems.

A situation-response model for intelligent pilot aiding

NASA Technical Reports Server (NTRS)

Schudy, Robert; Corker, Kevin

1987-01-01

An intelligent pilot aiding system needs models of the pilot information processing to provide the computational basis for successful cooperation between the pilot and the aiding system. By combining artificial intelligence concepts with the human information processing model of Rasmussen, an abstraction hierarchy of states of knowledge, processing functions, and shortcuts are developed, which is useful for characterizing the information processing both of the pilot and of the aiding system. This approach is used in the conceptual design of a real time intelligent aiding system for flight crews of transport aircraft. One promising result was the tentative identification of a particular class of information processing shortcuts, from situation characterizations to appropriate responses, as the most important reliable pathway for dealing with complex time critical situations.

Use of Parallel Micro-Platform for the Simulation the Space Exploration

NASA Astrophysics Data System (ADS)

Velasco Herrera, Victor Manuel; Velasco Herrera, Graciela; Rosano, Felipe Lara; Rodriguez Lozano, Salvador; Lucero Roldan Serrato, Karen

The purpose of this work is to create a parallel micro-platform, that simulates the virtual movements of a space exploration in 3D. One of the innovations presented in this design consists of the application of a lever mechanism for the transmission of the movement. The development of such a robot is a challenging task very different of the industrial manipulators due to a totally different target system of requirements. This work presents the study and simulation, aided by computer, of the movement of this parallel manipulator. The development of this model has been developed using the platform of computer aided design Unigraphics, in which it was done the geometric modeled of each one of the components and end assembly (CAD), the generation of files for the computer aided manufacture (CAM) of each one of the pieces and the kinematics simulation of the system evaluating different driving schemes. We used the toolbox (MATLAB) of aerospace and create an adaptive control module to simulate the system.

Miscellaneous Topics in Computer-Aided Drug Design: Synthetic Accessibility and GPU Computing, and Other Topics.

PubMed

Fukunishi, Yoshifumi; Mashimo, Tadaaki; Misoo, Kiyotaka; Wakabayashi, Yoshinori; Miyaki, Toshiaki; Ohta, Seiji; Nakamura, Mayu; Ikeda, Kazuyoshi

2016-01-01

Computer-aided drug design is still a state-of-the-art process in medicinal chemistry, and the main topics in this field have been extensively studied and well reviewed. These topics include compound databases, ligand-binding pocket prediction, protein-compound docking, virtual screening, target/off-target prediction, physical property prediction, molecular simulation and pharmacokinetics/pharmacodynamics (PK/PD) prediction. Message and Conclusion: However, there are also a number of secondary or miscellaneous topics that have been less well covered. For example, methods for synthesizing and predicting the synthetic accessibility (SA) of designed compounds are important in practical drug development, and hardware/software resources for performing the computations in computer-aided drug design are crucial. Cloud computing and general purpose graphics processing unit (GPGPU) computing have been used in virtual screening and molecular dynamics simulations. Not surprisingly, there is a growing demand for computer systems which combine these resources. In the present review, we summarize and discuss these various topics of drug design.

Miscellaneous Topics in Computer-Aided Drug Design: Synthetic Accessibility and GPU Computing, and Other Topics

PubMed Central

Fukunishi, Yoshifumi; Mashimo, Tadaaki; Misoo, Kiyotaka; Wakabayashi, Yoshinori; Miyaki, Toshiaki; Ohta, Seiji; Nakamura, Mayu; Ikeda, Kazuyoshi

2016-01-01

Abstract: Background Computer-aided drug design is still a state-of-the-art process in medicinal chemistry, and the main topics in this field have been extensively studied and well reviewed. These topics include compound databases, ligand-binding pocket prediction, protein-compound docking, virtual screening, target/off-target prediction, physical property prediction, molecular simulation and pharmacokinetics/pharmacodynamics (PK/PD) prediction. Message and Conclusion: However, there are also a number of secondary or miscellaneous topics that have been less well covered. For example, methods for synthesizing and predicting the synthetic accessibility (SA) of designed compounds are important in practical drug development, and hardware/software resources for performing the computations in computer-aided drug design are crucial. Cloud computing and general purpose graphics processing unit (GPGPU) computing have been used in virtual screening and molecular dynamics simulations. Not surprisingly, there is a growing demand for computer systems which combine these resources. In the present review, we summarize and discuss these various topics of drug design. PMID:27075578

Pre-Processed Recursive Lattice Reduction for Complexity Reduction in Spatially and Temporally Correlated MIMO Channels

NASA Astrophysics Data System (ADS)

An, Chan-Ho; Yang, Janghoon; Jang, Seunghun; Kim, Dong Ku

In this letter, a pre-processed lattice reduction (PLR) scheme is developed for the lattice reduction aided (LRA) detection of multiple input multiple-output (MIMO) systems in spatially correlated channel. The PLR computes the LLL-reduced matrix of the equivalent matrix, which is the product of the present channel matrix and unimodular transformation matrix for LR of spatial correlation matrix, rather than the present channel matrix itself. In conjunction with PLR followed by recursive lattice reduction (RLR) scheme [7], pre-processed RLR (PRLR) is shown to efficiently carry out the LR of the channel matrix, especially for the burst packet message in spatially and temporally correlated channel while matching the performance of conventional LRA detection.

Detection of breast cancer in automated 3D breast ultrasound

NASA Astrophysics Data System (ADS)

Tan, Tao; Platel, Bram; Mus, Roel; Karssemeijer, Nico

2012-03-01

Automated 3D breast ultrasound (ABUS) is a novel imaging modality, in which motorized scans of the breasts are made with a wide transducer through a membrane under modest compression. The technology has gained high interest and may become widely used in screening of dense breasts, where sensitivity of mammography is poor. ABUS has a high sensitivity for detecting solid breast lesions. However, reading ABUS images is time consuming, and subtle abnormalities may be missed. Therefore, we are developing a computer aided detection (CAD) system to help reduce reading time and errors. In the multi-stage system we propose, segmentations of the breast and nipple are performed, providing landmarks for the detection algorithm. Subsequently, voxel features characterizing coronal spiculation patterns, blobness, contrast, and locations with respect to landmarks are extracted. Using an ensemble of classifiers, a likelihood map indicating potential malignancies is computed. Local maxima in the likelihood map are determined using a local maxima detector and form a set of candidate lesions in each view. These candidates are further processed in a second detection stage, which includes region segmentation, feature extraction and a final classification. Region segmentation is performed using a 3D spiral-scanning dynamic programming method. Region features include descriptors of shape, acoustic behavior and texture. Performance was determined using a 78-patient dataset with 93 images, including 50 malignant lesions. We used 10-fold cross-validation. Using FROC analysis we found that the system obtains a lesion sensitivity of 60% and 70% at 2 and 4 false positives per image respectively.

Simultaneous detection and classification of breast masses in digital mammograms via a deep learning YOLO-based CAD system.

PubMed

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.

Integrated Computer System of Management in Logistics

NASA Astrophysics Data System (ADS)

Chwesiuk, Krzysztof

2011-06-01

This paper aims at presenting a concept of an integrated computer system of management in logistics, particularly in supply and distribution chains. Consequently, the paper includes the basic idea of the concept of computer-based management in logistics and components of the system, such as CAM and CIM systems in production processes, and management systems for storage, materials flow, and for managing transport, forwarding and logistics companies. The platform which integrates computer-aided management systems is that of electronic data interchange.

[Computer-aided prescribing: from utopia to reality].

PubMed

Suárez-Varela Ubeda, J; Beltrán Calvo, C; Molina López, T; Navarro Marín, P

2005-05-31

To determine whether the introduction of computer-aided prescribing helped reduce the administrative burden at primary care centers. Descriptive, cross-sectional design. Torreblanca Health Center in the province of Seville, southern Spain. From 29 October 2003 to the present a pilot project involving nine pharmacies in the basic health zone served by this health center has been running to evaluate computer-aided prescribing (the Receta XXI project) with real patients. All patients on the center's list of patients who came to the center for an administrative consultation to renew prescriptions for medications or supplies for long-term treatment. Total number of administrative visits per patient for patients who came to the center to renew prescriptions for long-term treatment, as recorded by the Diraya system (Historia Clinica Digital del Ciudadano, or Citizen's Digital Medical Record) during the period from February to July 2004. Total number of the same type of administrative visits recorded by the previous system (TASS) during the period from February to July 2003. The mean number of administrative visits per month during the period from February to July 2003 was 160, compared to a mean number of 64 visits during the period from February to July 2004. The reduction in the number of visits for prescription renewal was 60%. Introducing a system for computer-aided prescribing significantly reduced the number of administrative visits for prescription renewal for long-term treatment. This could help reduce the administrative burden considerably in primary care if the system were used in all centers.

Biomedical Informatics for Computer-Aided Decision Support Systems: A Survey

PubMed Central

Belle, Ashwin; Kon, Mark A.; Najarian, Kayvan

2013-01-01

The volumes of current patient data as well as their complexity make clinical decision making more challenging than ever for physicians and other care givers. This situation calls for the use of biomedical informatics methods to process data and form recommendations and/or predictions to assist such decision makers. The design, implementation, and use of biomedical informatics systems in the form of computer-aided decision support have become essential and widely used over the last two decades. This paper provides a brief review of such systems, their application protocols and methodologies, and the future challenges and directions they suggest. PMID:23431259

Computer-Aided Diagnosis of Breast Cancer: A Multi-Center Demonstrator

DTIC Science & Technology

1998-10-01

Artificial Neural Network (ANN) approach to computer aided diagnosis of breast cancer from mammographic findings. An ANN has been developed to provide support for the clinical decision to perform breast biopsy. The system is designed to aid in the decision to biopsy those patients who have suspicious mammographic findings. The decision to biopsy can be viewed as a two stage process: 1)the mammographer views the mammogram and determines the presence or absence of image features such as calcifications and masses, 2) the presence and description of these features

Creating an Electronic Reference and Information Database for Computer-aided ECM Design

NASA Astrophysics Data System (ADS)

Nekhoroshev, M. V.; Pronichev, N. D.; Smirnov, G. V.

2018-01-01

The paper presents a review on electrochemical shaping. An algorithm has been developed to implement a computer shaping model applicable to pulse electrochemical machining. For that purpose, the characteristics of pulse current occurring in electrochemical machining of aviation materials have been studied. Based on integrating the experimental results and comprehensive electrochemical machining process data modeling, a subsystem for computer-aided design of electrochemical machining for gas turbine engine blades has been developed; the subsystem was implemented in the Teamcenter PLM system.

Crowdsourcing lung nodules detection and annotation

NASA Astrophysics Data System (ADS)

Boorboor, Saeed; Nadeem, Saad; Park, Ji Hwan; Baker, Kevin; Kaufman, Arie

2018-03-01

We present crowdsourcing as an additional modality to aid radiologists in the diagnosis of lung cancer from clinical chest computed tomography (CT) scans. More specifically, a complete work flow is introduced which can help maximize the sensitivity of lung nodule detection by utilizing the collective intelligence of the crowd. We combine the concept of overlapping thin-slab maximum intensity projections (TS-MIPs) and cine viewing to render short videos that can be outsourced as an annotation task to the crowd. These videos are generated by linearly interpolating overlapping TS-MIPs of CT slices through the depth of each quadrant of a patient's lung. The resultant videos are outsourced to an online community of non-expert users who, after a brief tutorial, annotate suspected nodules in these video segments. Using our crowdsourcing work flow, we achieved a lung nodule detection sensitivity of over 90% for 20 patient CT datasets (containing 178 lung nodules with sizes between 1-30mm), and only 47 false positives from a total of 1021 annotations on nodules of all sizes (96% sensitivity for nodules>4mm). These results show that crowdsourcing can be a robust and scalable modality to aid radiologists in screening for lung cancer, directly or in combination with computer-aided detection (CAD) algorithms. For CAD algorithms, the presented work flow can provide highly accurate training data to overcome the high false-positive rate (per scan) problem. We also provide, for the first time, analysis on nodule size and position which can help improve CAD algorithms.

Computer aided reliability, availability, and safety modeling for fault-tolerant computer systems with commentary on the HARP program

NASA Technical Reports Server (NTRS)

Shooman, Martin L.

1991-01-01

Many of the most challenging reliability problems of our present decade involve complex distributed systems such as interconnected telephone switching computers, air traffic control centers, aircraft and space vehicles, and local area and wide area computer networks. In addition to the challenge of complexity, modern fault-tolerant computer systems require very high levels of reliability, e.g., avionic computers with MTTF goals of one billion hours. Most analysts find that it is too difficult to model such complex systems without computer aided design programs. In response to this need, NASA has developed a suite of computer aided reliability modeling programs beginning with CARE 3 and including a group of new programs such as: HARP, HARP-PC, Reliability Analysts Workbench (Combination of model solvers SURE, STEM, PAWS, and common front-end model ASSIST), and the Fault Tree Compiler. The HARP program is studied and how well the user can model systems using this program is investigated. One of the important objectives will be to study how user friendly this program is, e.g., how easy it is to model the system, provide the input information, and interpret the results. The experiences of the author and his graduate students who used HARP in two graduate courses are described. Some brief comparisons were made with the ARIES program which the students also used. Theoretical studies of the modeling techniques used in HARP are also included. Of course no answer can be any more accurate than the fidelity of the model, thus an Appendix is included which discusses modeling accuracy. A broad viewpoint is taken and all problems which occurred in the use of HARP are discussed. Such problems include: computer system problems, installation manual problems, user manual problems, program inconsistencies, program limitations, confusing notation, long run times, accuracy problems, etc.

Survey of Intelligent Computer-Aided Training

NASA Technical Reports Server (NTRS)

Loftin, R. B.; Savely, Robert T.

1992-01-01

Intelligent Computer-Aided Training (ICAT) systems integrate artificial intelligence and simulation technologies to deliver training for complex, procedural tasks in a distributed, workstation-based environment. Such systems embody both the knowledge of how to perform a task and how to train someone to perform that task. This paper briefly reviews the antecedents of ICAT systems and describes the approach to their creation developed at the NASA Lyndon B. Johnson Space Center. In addition to the general ICAT architecture, specific ICAT applications that have been or are currently under development are discussed. ICAT systems can offer effective solutions to a number of training problems of interest to the aerospace community.

CT Colonography with Computer-aided Detection: Recognizing the Causes of False-Positive Reader Results

PubMed Central

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

Algorithms and data structures for automated change detection and classification of sidescan sonar imagery

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.

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.

Automatic detection of axillary lymphadenopathy on CT scans of untreated chronic lymphocytic leukemia patients

NASA Astrophysics Data System (ADS)

Liu, Jiamin; Hua, Jeremy; Chellappa, Vivek; Petrick, Nicholas; Sahiner, Berkman; Farooqui, Mohammed; Marti, Gerald; Wiestner, Adrian; Summers, Ronald M.

2012-03-01

Patients with chronic lymphocytic leukemia (CLL) have an increased frequency of axillary lymphadenopathy. Pretreatment CT scans can be used to upstage patients at the time of presentation and post-treatment CT scans can reduce the number of complete responses. In the current clinical workflow, the detection and diagnosis of lymph nodes is usually performed manually by examining all slices of CT images, which can be time consuming and highly dependent on the observer's experience. A system for automatic lymph node detection and measurement is desired. We propose a computer aided detection (CAD) system for axillary lymph nodes on CT scans in CLL patients. The lung is first automatically segmented and the patient's body in lung region is extracted to set the search region for lymph nodes. Multi-scale Hessian based blob detection is then applied to detect potential lymph nodes within the search region. Next, the detected potential candidates are segmented by fast level set method. Finally, features are calculated from the segmented candidates and support vector machine (SVM) classification is utilized for false positive reduction. Two blobness features, Frangi's and Li's, are tested and their free-response receiver operating characteristic (FROC) curves are generated to assess system performance. We applied our detection system to 12 patients with 168 axillary lymph nodes measuring greater than 10 mm. All lymph nodes are manually labeled as ground truth. The system achieved sensitivities of 81% and 85% at 2 false positives per patient for Frangi's and Li's blobness, respectively.

Computer-aided engineering system for design of sequence arrays and lithographic masks

DOEpatents

Hubbell, Earl A.; Morris, MacDonald S.; Winkler, James L.

1999-01-05

An improved set of computer tools for forming arrays. According to one aspect of the invention, a computer system (100) is used to select probes and design the layout of an array of DNA or other polymers with certain beneficial characteristics. According to another aspect of the invention, a computer system uses chip design files (104) to design and/or generate lithographic masks (110).

Computer-aided engineering system for design of sequence arrays and lithographic masks

DOEpatents

Hubbell, Earl A.; Morris, MacDonald S.; Winkler, James L.

1996-01-01

An improved set of computer tools for forming arrays. According to one aspect of the invention, a computer system (100) is used to select probes and design the layout of an array of DNA or other polymers with certain beneficial characteristics. According to another aspect of the invention, a computer system uses chip design files (104) to design and/or generate lithographic masks (110).

Computer-aided engineering system for design of sequence arrays and lithographic masks

DOEpatents

Hubbell, E.A.; Morris, M.S.; Winkler, J.L.

1999-01-05

An improved set of computer tools for forming arrays is disclosed. According to one aspect of the invention, a computer system is used to select probes and design the layout of an array of DNA or other polymers with certain beneficial characteristics. According to another aspect of the invention, a computer system uses chip design files to design and/or generate lithographic masks. 14 figs.

Computer-aided engineering system for design of sequence arrays and lithographic masks

DOEpatents

Hubbell, E.A.; Lipshutz, R.J.; Morris, M.S.; Winkler, J.L.

1997-01-14

An improved set of computer tools for forming arrays is disclosed. According to one aspect of the invention, a computer system is used to select probes and design the layout of an array of DNA or other polymers with certain beneficial characteristics. According to another aspect of the invention, a computer system uses chip design files to design and/or generate lithographic masks. 14 figs.

Computer-aided engineering system for design of sequence arrays and lithographic masks

DOEpatents

Hubbell, E.A.; Morris, M.S.; Winkler, J.L.

1996-11-05

An improved set of computer tools for forming arrays is disclosed. According to one aspect of the invention, a computer system is used to select probes and design the layout of an array of DNA or other polymers with certain beneficial characteristics. According to another aspect of the invention, a computer system uses chip design files to design and/or generate lithographic masks. 14 figs.

Battlefield Object Control via Internet Architecture

DTIC Science & Technology

2002-01-01

superiority is the best way to reach the goal of competition superiority. Using information technology (IT) in data processing, including computer hardware... technologies : Global Positioning System (GPS), Geographic Information System (GIS), Battlefield Information Transmission System (BITS), and Intelligent...operational environment. Keywords: C4ISR Systems, Information Superiority, Battlefield Objects, Computer - Aided Prototyping System (CAPS), IP-based

Reduction of lymph tissue false positives in pulmonary embolism detection

NASA Astrophysics Data System (ADS)

Ghanem, Bernard; Liang, Jianming; Bi, Jinbo; Salganicoff, Marcos; Krishnan, Arun

2008-03-01

Pulmonary embolism (PE) is a serious medical condition, characterized by the partial/complete blockage of an artery within the lungs. We have previously developed a fast yet effective approach for computer aided detection of PE in computed topographic pulmonary angiography (CTPA),1 which is capable of detecting both acute and chronic PEs, achieving a benchmark performance of 78% sensitivity at 4 false positives (FPs) per volume. By reviewing the FPs generated by this system, we found the most dominant type of FP, roughly one third of all FPs, to be lymph/connective tissue. In this paper, we propose a novel approach that specifically aims at reducing this FP type. Our idea is to explicitly exploit the anatomical context configuration of PE and lymph tissue in the lungs: a lymph FP connects to the airway and is located outside the artery, while a true PE should not connect to the airway and must be inside the artery. To realize this idea, given a detected candidate (i.e. a cluster of suspicious voxels), we compute a set of contextual features, including its distance to the airway based on local distance transform and its relative position to the artery based on fast tensor voting and Hessian "vesselness" scores. Our tests on unseen cases show that these features can reduce the lymph FPs by 59%, while improving the overall sensitivity by 3.4%.

Computer-aided dental prostheses construction using reverse engineering.

PubMed

Solaberrieta, E; Minguez, R; Barrenetxea, L; Sierra, E; Etxaniz, O

2014-01-01

The implementation of computer-aided design/computer-aided manufacturing (CAD/CAM) systems with virtual articulators, which take into account the kinematics, constitutes a breakthrough in the construction of customised dental prostheses. This paper presents a multidisciplinary protocol involving CAM techniques to produce dental prostheses. This protocol includes a step-by-step procedure using innovative reverse engineering technologies to transform completely virtual design processes into customised prostheses. A special emphasis is placed on a novel method that permits a virtual location of the models. The complete workflow includes the optical scanning of the patient, the use of reverse engineering software and, if necessary, the use of rapid prototyping to produce CAD temporary prostheses.

A Fast Approach to Automatic Detection of Brain Lesions

PubMed Central

Koley, Subhranil; Chakraborty, Chandan; Mainero, Caterina; Fischl, Bruce; Aganj, Iman

2017-01-01

Template matching is a popular approach to computer-aided detection of brain lesions from magnetic resonance (MR) images. The outcomes are often sufficient for localizing lesions and assisting clinicians in diagnosis. However, processing large MR volumes with three-dimensional (3D) templates is demanding in terms of computational resources, hence the importance of the reduction of computational complexity of template matching, particularly in situations in which time is crucial (e.g. emergent stroke). In view of this, we make use of 3D Gaussian templates with varying radii and propose a new method to compute the normalized cross-correlation coefficient as a similarity metric between the MR volume and the template to detect brain lesions. Contrary to the conventional fast Fourier transform (FFT) based approach, whose runtime grows as O(N logN) with the number of voxels, the proposed method computes the cross-correlation in O(N). We show through our experiments that the proposed method outperforms the FFT approach in terms of computational time, and retains comparable accuracy. PMID:29082383

Deep learning aided decision support for pulmonary nodules diagnosing: a review.

PubMed

Yang, Yixin; Feng, Xiaoyi; Chi, Wenhao; Li, Zhengyang; Duan, Wenzhe; Liu, Haiping; Liang, Wenhua; Wang, Wei; Chen, Ping; He, Jianxing; Liu, Bo

2018-04-01

Deep learning techniques have recently emerged as promising decision supporting approaches to automatically analyze medical images for different clinical diagnosing purposes. Diagnosing of pulmonary nodules by using computer-assisted diagnosing has received considerable theoretical, computational, and empirical research work, and considerable methods have been developed for detection and classification of pulmonary nodules on different formats of images including chest radiographs, computed tomography (CT), and positron emission tomography in the past five decades. The recent remarkable and significant progress in deep learning for pulmonary nodules achieved in both academia and the industry has demonstrated that deep learning techniques seem to be promising alternative decision support schemes to effectively tackle the central issues in pulmonary nodules diagnosing, including feature extraction, nodule detection, false-positive reduction, and benign-malignant classification for the huge volume of chest scan data. The main goal of this investigation is to provide a comprehensive state-of-the-art review of the deep learning aided decision support for pulmonary nodules diagnosing. As far as the authors know, this is the first time that a review is devoted exclusively to deep learning techniques for pulmonary nodules diagnosing.

On computer vision in wireless sensor networks.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Berry, Nina M.; Ko, Teresa H.

Wireless sensor networks allow detailed sensing of otherwise unknown and inaccessible environments. While it would be beneficial to include cameras in a wireless sensor network because images are so rich in information, the power cost of transmitting an image across the wireless network can dramatically shorten the lifespan of the sensor nodes. This paper describe a new paradigm for the incorporation of imaging into wireless networks. Rather than focusing on transmitting images across the network, we show how an image can be processed locally for key features using simple detectors. Contrasted with traditional event detection systems that trigger an imagemore » capture, this enables a new class of sensors which uses a low power imaging sensor to detect a variety of visual cues. Sharing these features among relevant nodes cues specific actions to better provide information about the environment. We report on various existing techniques developed for traditional computer vision research which can aid in this work.« less