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

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

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

Enormous knowledge base of disease diagnosis criteria.

PubMed

Xiao, Z H; Xiao, Y H; Pei, J H

1995-01-01

One of the problems in the development of the medical knowledge systems is the limitations of the system's knowledge. It is a common expectation to increase the number of diseases contained in a system. Using a high density knowledge representation method designed by us, we have developed the Enormous Knowledge Base of Disease Diagnosis Criteria (EKBDDC). It contains diagnostic criteria of 1,001 diagnostic entities and describes nearly 4,000 items of diagnostic indicators. It is the core of a huge medical project--the Electronic-Brain Medical Erudite (EBME). This enormous knowledge base was implemented initially on a low-cost popular microcomputer, which can aid in the prompting of typical disease and in teaching of diagnosis. The knowledge base is easy to expand. One of the main goals of EKBDDC is to increase the number of diseases included in it as far as possible using a low-cost computer with a comparatively small storage capacity. For this, we have designed a high density knowledge representation method. Criteria of various diagnostic entities are respectively stored in different records of the knowledge base. Each diagnostic entity corresponds to a diagnostic criterion data set; each data set consists of some diagnostic criterion data values (Table 1); each data is composed of two parts: integer and decimal; the integral part is the coding number of the given diagnostic information, and the decimal part is the diagnostic value of this information to the disease indicated by corresponding record number. For example, 75.02: the integer 75 is the coding number of "hemorrhagic skin rash"; the decimal 0.02 is the diagnostic value of this manifestation for diagnosing allergic purpura. TABULAR DATA, SEE PUBLISHED ABSTRACT. The algebraic sum method, a special form of the weighted summation, is adopted as mathematical model. In EKBDDC, the diagnostic values, which represent the significance of the disease manifestations for diagnosing corresponding diseases, were determined empirically. It is of a great economical, practical, and technical significance to realize enormous knowledge bases of disease diagnosis criteria on a low-cost popular microcomputer. This is beneficial for the developing countries to popularize medical informatics. To create the enormous international computer-aided diagnosis system, one may jointly develop the unified modules of disease diagnosis criteria used to "inlay" relevant computer-aided diagnosis systems. It is just like assembling a house using prefabricated panels.

Intelligent Computer-Aided Instruction for Medical Diagnosis

PubMed Central

Clancey, William J.; Shortliffe, Edward H.; Buchanan, Bruce G.

1979-01-01

An intelligent computer-aided instruction (ICAI) program, named GUIDON, has been developed for teaching infectious disease diagnosis.* ICAI programs use artificial intelligence techniques for representing both subject material and teaching strategies. This paper briefly outlines the difference between traditional instructional programs and ICAI. We then illustrate how GUIDON makes contributions in areas important to medical CAI: interacting with the student in a mixed-initiative dialogue (including the problems of feedback and realism), teaching problem-solving strategies, and assembling a computer-based curriculum.

Computer-aided diagnosis of early knee osteoarthritis based on MRI T2 mapping.

PubMed

Wu, Yixiao; Yang, Ran; Jia, Sen; Li, Zhanjun; Zhou, Zhiyang; Lou, Ting

2014-01-01

This work was aimed at studying the method of computer-aided diagnosis of early knee OA (OA: osteoarthritis). Based on the technique of MRI (MRI: Magnetic Resonance Imaging) T2 Mapping, through computer image processing, feature extraction, calculation and analysis via constructing a classifier, an effective computer-aided diagnosis method for knee OA was created to assist doctors in their accurate, timely and convenient detection of potential risk of OA. In order to evaluate this method, a total of 1380 data from the MRI images of 46 samples of knee joints were collected. These data were then modeled through linear regression on an offline general platform by the use of the ImageJ software, and a map of the physical parameter T2 was reconstructed. After the image processing, the T2 values of ten regions in the WORMS (WORMS: Whole-organ Magnetic Resonance Imaging Score) areas of the articular cartilage were extracted to be used as the eigenvalues in data mining. Then,a RBF (RBF: Radical Basis Function) network classifier was built to classify and identify the collected data. The classifier exhibited a final identification accuracy of 75%, indicating a good result of assisting diagnosis. Since the knee OA classifier constituted by a weights-directly-determined RBF neural network didn't require any iteration, our results demonstrated that the optimal weights, appropriate center and variance could be yielded through simple procedures. Furthermore, the accuracy for both the training samples and the testing samples from the normal group could reach 100%. Finally, the classifier was superior both in time efficiency and classification performance to the frequently used classifiers based on iterative learning. Thus it was suitable to be used as an aid to computer-aided diagnosis of early knee OA.

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

Enhancements in medicine by integrating content based image retrieval in computer-aided diagnosis

NASA Astrophysics Data System (ADS)

Aggarwal, Preeti; Sardana, H. K.

2010-02-01

Computer-aided diagnosis (CAD) has become one of the major research subjects in medical imaging and diagnostic radiology. With cad, radiologists use the computer output as a "second opinion" and make the final decisions. Retrieving images is a useful tool to help radiologist to check medical image and diagnosis. The impact of contentbased access to medical images is frequently reported but existing systems are designed for only a particular context of diagnosis. The challenge in medical informatics is to develop tools for analyzing the content of medical images and to represent them in a way that can be efficiently searched and compared by the physicians. CAD is a concept established by taking into account equally the roles of physicians and computers. To build a successful computer aided diagnostic system, all the relevant technologies, especially retrieval need to be integrated in such a manner that should provide effective and efficient pre-diagnosed cases with proven pathology for the current case at the right time. In this paper, it is suggested that integration of content-based image retrieval (CBIR) in cad can bring enormous results in medicine especially in diagnosis. This approach is also compared with other approaches by highlighting its advantages over those approaches.

The Perceived Effect of HIV/AIDS on Other Identities

ERIC Educational Resources Information Center

Baumgartner, Lisa M; Niemi, Eric

2013-01-01

The onset of a chronic disease influences other roles or identities. For example, an HIV or AIDS diagnosis can affect a person's work identity (Bedell, 1997). In this article, we explored how living with HIV/AIDS shapes other identities. Thirty-six individuals living with HIV/AIDS (PLWHAs) participated in semi-structured interviews. Participants'…

Multiphasic Health Testing in the Clinic Setting

PubMed Central

LaDou, Joseph

1971-01-01

The economy of automated multiphasic health testing (amht) activities patterned after the high-volume Kaiser program can be realized in low-volume settings. amht units have been operated at daily volumes of 20 patients in three separate clinical environments. These programs have displayed economics entirely compatible with cost figures published by the established high-volume centers. This experience, plus the expanding capability of small, general purpose, digital computers (minicomputers) indicates that a group of six or more physicians generating 20 laboratory appraisals per day can economically justify a completely automated multiphasic health testing facility. This system would reside in the clinic or hospital where it is used and can be configured to do analyses such as electrocardiography and generate laboratory reports, and communicate with large computer systems in university medical centers. Experience indicates that the most effective means of implementing these benefits of automation is to make them directly available to the medical community with the physician playing the central role. Economic justification of a dedicated computer through low-volume health testing then allows, as a side benefit, automation of administrative as well as other diagnostic activities—for example, patient billing, computer-aided diagnosis, and computer-aided therapeutics. PMID:4935771

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 diagnosis model for lung tumor based on ensemble convolutional neural network].

PubMed

Wang, Yuanyuan; Zhou, Tao; Lu, Huiling; Wu, Cuiying; Yang, Pengfei

2017-08-01

The convolutional neural network (CNN) could be used on computer-aided diagnosis of lung tumor with positron emission tomography (PET)/computed tomography (CT), which can provide accurate quantitative analysis to compensate for visual inertia and defects in gray-scale sensitivity, and help doctors diagnose accurately. Firstly, parameter migration method is used to build three CNNs (CT-CNN, PET-CNN, and PET/CT-CNN) for lung tumor recognition in CT, PET, and PET/CT image, respectively. Then, we aimed at CT-CNN to obtain the appropriate model parameters for CNN training through analysis the influence of model parameters such as epochs, batchsize and image scale on recognition rate and training time. Finally, three single CNNs are used to construct ensemble CNN, and then lung tumor PET/CT recognition was completed through relative majority vote method and the performance between ensemble CNN and single CNN was compared. The experiment results show that the ensemble CNN is better than single CNN on computer-aided diagnosis of lung tumor.

Combining destination diversion decisions and critical in-flight event diagnosis in computer aided testing of pilots

NASA Technical Reports Server (NTRS)

Rockwell, T. H.; Giffin, W. C.; Romer, D. J.

1984-01-01

Rockwell and Giffin (1982) and Giffin and Rockwell (1983) have discussed the use of computer aided testing (CAT) in the study of pilot response to critical in-flight events. The present investigation represents an extension of these earlier studies. In testing pilot responses to critical in-flight events, use is made of a Plato-touch CRT system operating on a menu based format. In connection with the typical diagnostic problem, the pilot was presented with symptoms within a flight scenario. In one problem, the pilot has four minutes for obtaining the information which is needed to make a diagnosis of the problem. In the reported research, the attempt has been made to combine both diagnosis and diversion scenario into a single computer aided test. Tests with nine subjects were conducted. The obtained results and their significance are discussed.

Sinus barotrauma--late diagnosis and treatment with computer-aided endoscopic surgery.

PubMed

Larsen, Anders Schermacher; Buchwald, Christian; Vesterhauge, Søren

2003-02-01

Sinus barotrauma is usually easy to diagnose, and treatment achieves good results. We present two severe cases where delayed diagnosis caused significant morbidity. The signs and symptoms were atypical and neither the patients themselves, nor the initial examiners recognized that the onset of symptoms coincided with descent in a commercial airliner. CT and MRI scans of the brain were normal, but in both cases showed opafication of the sphenoid sinuses, which lead to the correct diagnosis. Subsequent surgical intervention consisting of endoscopic computer-aided surgery showed blood and petechia in the affected sinuses. This procedure provided immediate relief.

Development of a Computer-Aided Diagnosis System for Early Detection of Masses Using Retrospectively Detected Cancers on Prior Mammograms

DTIC Science & Technology

2006-06-01

Hadjiiski, and N. Petrick, "Computerized nipple identification for multiple image analysis in computer-aided diagnosis," Medical Physics 31, 2871...candidates, 3 identification of suspicious objects, 4 feature extraction and analysis, and 5 FP reduc- tion by classification of normal tissue...detection of microcalcifi- cations on digitized mammograms.41 An illustration of a La- placian decomposition tree is shown on the left-hand side of Fig. 4

[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.

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.

Computer-aided testing of pilot response to critical in-flight events

NASA Technical Reports Server (NTRS)

Giffin, W. C.; Rockwell, T. H.

1984-01-01

This research on pilot response to critical in-flight events employs a unique methodology including an interactive computer-aided scenario-testing system. Navigation displays, instrument-panel displays, and assorted textual material are presented on a touch-sensitive CRT screen. Problem diagnosis scenarios, destination-diversion scenarios and combined destination/diagnostic tests are available. A complete time history of all data inquiries and responses is maintained. Sample results of diagnosis scenarios obtained from testing 38 licensed pilots are presented and discussed.

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.

Evaluation of computer-aided detection and diagnosis systems.

PubMed

Petrick, Nicholas; Sahiner, Berkman; Armato, Samuel G; Bert, Alberto; Correale, Loredana; Delsanto, Silvia; Freedman, Matthew T; Fryd, David; Gur, David; Hadjiiski, Lubomir; Huo, Zhimin; Jiang, Yulei; Morra, Lia; Paquerault, Sophie; Raykar, Vikas; Samuelson, Frank; Summers, Ronald M; Tourassi, Georgia; Yoshida, Hiroyuki; Zheng, Bin; Zhou, Chuan; Chan, Heang-Ping

2013-08-01

Computer-aided detection and diagnosis (CAD) systems are increasingly being used as an aid by clinicians for detection and interpretation of diseases. Computer-aided detection systems mark regions of an image that may reveal specific abnormalities and are used to alert clinicians to these regions during image interpretation. Computer-aided diagnosis systems provide an assessment of a disease using image-based information alone or in combination with other relevant diagnostic data and are used by clinicians as a decision support in developing their diagnoses. While CAD systems are commercially available, standardized approaches for evaluating and reporting their performance have not yet been fully formalized in the literature or in a standardization effort. This deficiency has led to difficulty in the comparison of CAD devices and in understanding how the reported performance might translate into clinical practice. To address these important issues, the American Association of Physicists in Medicine (AAPM) formed the Computer Aided Detection in Diagnostic Imaging Subcommittee (CADSC), in part, to develop recommendations on approaches for assessing CAD system performance. The purpose of this paper is to convey the opinions of the AAPM CADSC members and to stimulate the development of consensus approaches and "best practices" for evaluating CAD systems. Both the assessment of a standalone CAD system and the evaluation of the impact of CAD on end-users are discussed. It is hoped that awareness of these important evaluation elements and the CADSC recommendations will lead to further development of structured guidelines for CAD performance assessment. Proper assessment of CAD system performance is expected to increase the understanding of a CAD system's effectiveness and limitations, which is expected to stimulate further research and development efforts on CAD technologies, reduce problems due to improper use, and eventually improve the utility and efficacy of CAD in clinical practice.

Evaluation of computer-aided detection and diagnosis systemsa)

PubMed Central

Petrick, Nicholas; Sahiner, Berkman; Armato, Samuel G.; Bert, Alberto; Correale, Loredana; Delsanto, Silvia; Freedman, Matthew T.; Fryd, David; Gur, David; Hadjiiski, Lubomir; Huo, Zhimin; Jiang, Yulei; Morra, Lia; Paquerault, Sophie; Raykar, Vikas; Samuelson, Frank; Summers, Ronald M.; Tourassi, Georgia; Yoshida, Hiroyuki; Zheng, Bin; Zhou, Chuan; Chan, Heang-Ping

2013-01-01

Computer-aided detection and diagnosis (CAD) systems are increasingly being used as an aid by clinicians for detection and interpretation of diseases. Computer-aided detection systems mark regions of an image that may reveal specific abnormalities and are used to alert clinicians to these regions during image interpretation. Computer-aided diagnosis systems provide an assessment of a disease using image-based information alone or in combination with other relevant diagnostic data and are used by clinicians as a decision support in developing their diagnoses. While CAD systems are commercially available, standardized approaches for evaluating and reporting their performance have not yet been fully formalized in the literature or in a standardization effort. This deficiency has led to difficulty in the comparison of CAD devices and in understanding how the reported performance might translate into clinical practice. To address these important issues, the American Association of Physicists in Medicine (AAPM) formed the Computer Aided Detection in Diagnostic Imaging Subcommittee (CADSC), in part, to develop recommendations on approaches for assessing CAD system performance. The purpose of this paper is to convey the opinions of the AAPM CADSC members and to stimulate the development of consensus approaches and “best practices” for evaluating CAD systems. Both the assessment of a standalone CAD system and the evaluation of the impact of CAD on end-users are discussed. It is hoped that awareness of these important evaluation elements and the CADSC recommendations will lead to further development of structured guidelines for CAD performance assessment. Proper assessment of CAD system performance is expected to increase the understanding of a CAD system's effectiveness and limitations, which is expected to stimulate further research and development efforts on CAD technologies, reduce problems due to improper use, and eventually improve the utility and efficacy of CAD in clinical practice. PMID:23927365

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

NASA Astrophysics Data System (ADS)

Satoh, Hitoshi; Niki, Noboru; Eguchi, Kenji; Moriyama, Noriyuki; Ohmatsu, Hironobu; Masuda, Hideo; Machida, Suguru

2008-03-01

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. 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, 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 function 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. 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.

Computer-Assisted Digital Image Analysis of Plus Disease in Retinopathy of Prematurity.

PubMed

Kemp, Pavlina S; VanderVeen, Deborah K

2016-01-01

The objective of this study is to review the current state and role of computer-assisted analysis in diagnosis of plus disease in retinopathy of prematurity. Diagnosis and documentation of retinopathy of prematurity are increasingly being supplemented by digital imaging. The incorporation of computer-aided techniques has the potential to add valuable information and standardization regarding the presence of plus disease, an important criterion in deciding the necessity of treatment of vision-threatening retinopathy of prematurity. A review of literature found that several techniques have been published examining the process and role of computer aided analysis of plus disease in retinopathy of prematurity. These techniques use semiautomated image analysis techniques to evaluate retinal vascular dilation and tortuosity, using calculated parameters to evaluate presence or absence of plus disease. These values are then compared with expert consensus. The study concludes that computer-aided image analysis has the potential to use quantitative and objective criteria to act as a supplemental tool in evaluating for plus disease in the setting of retinopathy of prematurity.

Development of a Computer-aided Diagnosis System for Early Detection of Masses Using Retrospectively Detected Cancers on Prior Mammograms

DTIC Science & Technology

2009-06-01

131 cases with 131 biopsy proven masses, of which 27 were malignant and 104 benign. The true locations of the masses were identified by an experi- enced ...two acquisitions would cause differ- ences in the subtlety of the masses on the FFDMs and SFMs. However, assuming that the differences are ran- dom... Lado , M. Souto, and J. J. Vidal, “Computer-aided diagnosis: Automatic detection of malignant masses in digitized mammograms,” Med. Phys. 25, 957–964

Development of a Computer-Aided Diagnosis System for Early Detection of Masses Using Retrospectively Detected Cancers on Prior Mammograms

DTIC Science & Technology

2007-06-01

the masses were identified by an experi- enced Mammography Quality Standards Act (MQSA) radiologist. The no-mass data set contained 98 cases. The time...force, and the difference in time between the two acquisitions would cause differ- ences in the subtlety of the masses on the FFDMs and SFMs. However...images," Medical Physics 18, 955-963 (1991). 20A. J. Mendez, P. G. Tahoces, M. J. Lado , M. Souto, and J. J. Vidal, "Computer-aided diagnosis: Automatic

Computer-aided classification of optical images for diagnosis of osteoarthritis in the finger joints.

PubMed

Zhang, Jiang; Wang, James Z; Yuan, Zhen; Sobel, Eric S; Jiang, Huabei

2011-01-01

This study presents a computer-aided classification method to distinguish osteoarthritis finger joints from healthy ones based on the functional images captured by x-ray guided diffuse optical tomography. Three imaging features, joint space width, optical absorption, and scattering coefficients, are employed to train a Least Squares Support Vector Machine (LS-SVM) classifier for osteoarthritis classification. The 10-fold validation results show that all osteoarthritis joints are clearly identified and all healthy joints are ruled out by the LS-SVM classifier. The best sensitivity, specificity, and overall accuracy of the classification by experienced technicians based on manual calculation of optical properties and visual examination of optical images are only 85%, 93%, and 90%, respectively. Therefore, our LS-SVM based computer-aided classification is a considerably improved method for osteoarthritis diagnosis.

Computer-Aided Characterization of Breast Masses on Volumetric Ultrasound Images: An Adjunct to Mammography

DTIC Science & Technology

2005-10-01

nearly setting-independent features and artificial neural networks. Radiology 2003; 226:504-514. 14. Horsch K, Giger ML, Venta LA, Vyborny CJ...Giger ML, Vyborny CJ, Venta LA. Performance of computer-aided diagnosis in the interpretation of lesions on breast sonography. Acad. Radiol. 2004; 11:272

Computer-aided US diagnosis of breast lesions by using cell-based contour grouping.

PubMed

Cheng, Jie-Zhi; Chou, Yi-Hong; Huang, Chiun-Sheng; Chang, Yeun-Chung; Tiu, Chui-Mei; Chen, Kuei-Wu; Chen, Chung-Ming

2010-06-01

To develop a computer-aided diagnostic algorithm with automatic boundary delineation for differential diagnosis of benign and malignant breast lesions at ultrasonography (US) and investigate the effect of boundary quality on the performance of a computer-aided diagnostic algorithm. This was an institutional review board-approved retrospective study with waiver of informed consent. A cell-based contour grouping (CBCG) segmentation algorithm was used to delineate the lesion boundaries automatically. Seven morphologic features were extracted. The classifier was a logistic regression function. Five hundred twenty breast US scans were obtained from 520 subjects (age range, 15-89 years), including 275 benign (mean size, 15 mm; range, 5-35 mm) and 245 malignant (mean size, 18 mm; range, 8-29 mm) lesions. The newly developed computer-aided diagnostic algorithm was evaluated on the basis of boundary quality and differentiation performance. The segmentation algorithms and features in two conventional computer-aided diagnostic algorithms were used for comparative study. The CBCG-generated boundaries were shown to be comparable with the manually delineated boundaries. The area under the receiver operating characteristic curve (AUC) and differentiation accuracy were 0.968 +/- 0.010 and 93.1% +/- 0.7, respectively, for all 520 breast lesions. At the 5% significance level, the newly developed algorithm was shown to be superior to the use of the boundaries and features of the two conventional computer-aided diagnostic algorithms in terms of AUC (0.974 +/- 0.007 versus 0.890 +/- 0.008 and 0.788 +/- 0.024, respectively). The newly developed computer-aided diagnostic algorithm that used a CBCG segmentation method to measure boundaries achieved a high differentiation performance. Copyright RSNA, 2010

Multimedia Image Technology and Computer Aided Manufacturing Engineering Analysis

NASA Astrophysics Data System (ADS)

Nan, Song

2018-03-01

Since the reform and opening up, with the continuous development of science and technology in China, more and more advanced science and technology have emerged under the trend of diversification. Multimedia imaging technology, for example, has a significant and positive impact on computer aided manufacturing engineering in China. From the perspective of scientific and technological advancement and development, the multimedia image technology has a very positive influence on the application and development of computer-aided manufacturing engineering, whether in function or function play. Therefore, this paper mainly starts from the concept of multimedia image technology to analyze the application of multimedia image technology in computer aided manufacturing engineering.

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,…

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

Decision support in psychiatry – a comparison between the diagnostic outcomes using a computerized decision support system versus manual diagnosis

PubMed Central

Bergman, Lars G; Fors, Uno GH

2008-01-01

Background Correct diagnosis in psychiatry may be improved by novel diagnostic procedures. Computerized Decision Support Systems (CDSS) are suggested to be able to improve diagnostic procedures, but some studies indicate possible problems. Therefore, it could be important to investigate CDSS systems with regard to their feasibility to improve diagnostic procedures as well as to save time. Methods This study was undertaken to compare the traditional 'paper and pencil' diagnostic method SCID1 with the computer-aided diagnostic system CB-SCID1 to ascertain processing time and accuracy of diagnoses suggested. 63 clinicians volunteered to participate in the study and to solve two paper-based cases using either a CDSS or manually. Results No major difference between paper and pencil and computer-supported diagnosis was found. Where a difference was found it was in favour of paper and pencil. For example, a significantly shorter time was found for paper and pencil for the difficult case, as compared to computer support. A significantly higher number of correct diagnoses were found in the diffilt case for the diagnosis 'Depression' using the paper and pencil method. Although a majority of the clinicians found the computer method supportive and easy to use, it took a longer time and yielded fewer correct diagnoses than with paper and pencil. Conclusion This study could not detect any major difference in diagnostic outcome between traditional paper and pencil methods and computer support for psychiatric diagnosis. Where there were significant differences, traditional paper and pencil methods were better than the tested CDSS and thus we conclude that CDSS for diagnostic procedures may interfere with diagnosis accuracy. A limitation was that most clinicians had not previously used the CDSS system under study. The results of this study, however, confirm that CDSS development for diagnostic purposes in psychiatry has much to deal with before it can be used for routine clinical purposes. PMID:18261222

A novel approach to malignant-benign classification of pulmonary nodules by using ensemble learning classifiers.

PubMed

Tartar, A; Akan, A; Kilic, N

2014-01-01

Computer-aided detection systems can help radiologists to detect pulmonary nodules at an early stage. In this paper, a novel Computer-Aided Diagnosis system (CAD) is proposed for the classification of pulmonary nodules as malignant and benign. The proposed CAD system using ensemble learning classifiers, provides an important support to radiologists at the diagnosis process of the disease, achieves high classification performance. The proposed approach with bagging classifier results in 94.7 %, 90.0 % and 77.8 % classification sensitivities for benign, malignant and undetermined classes (89.5 % accuracy), respectively.

[Computer-aided Diagnosis and New Electronic Stethoscope].

PubMed

Huang, Mei; Liu, Hongying; Pi, Xitian; Ao, Yilu; Wang, Zi

2017-05-30

Auscultation is an important method in early-diagnosis of cardiovascular disease and respiratory system disease. This paper presents a computer-aided diagnosis of new electronic auscultation system. It has developed an electronic stethoscope based on condenser microphone and the relevant intelligent analysis software. It has implemented many functions that combined with Bluetooth, OLED, SD card storage technologies, such as real-time heart and lung sounds auscultation in three modes, recording and playback, auscultation volume control, wireless transmission. The intelligent analysis software based on PC computer utilizes C# programming language and adopts SQL Server as the background database. It has realized play and waveform display of the auscultation sound. By calculating the heart rate, extracting the characteristic parameters of T1, T2, T12, T11, it can analyze whether the heart sound is normal, and then generate diagnosis report. Finally the auscultation sound and diagnosis report can be sent to mailbox of other doctors, which can carry out remote diagnosis. The whole system has features of fully function, high portability, good user experience, and it is beneficial to promote the use of electronic stethoscope in the hospital, at the same time, the system can also be applied to auscultate teaching and other occasions.

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…

A Visual Tool for Computer Supported Learning: The Robot Motion Planning Example

ERIC Educational Resources Information Center

Elnagar, Ashraf; Lulu, Leena

2007-01-01

We introduce an effective computer aided learning visual tool (CALVT) to teach graph-based applications. We present the robot motion planning problem as an example of such applications. The proposed tool can be used to simulate and/or further to implement practical systems in different areas of computer science such as graphics, computational…

Bayes' theorem application in the measure information diagnostic value assessment

NASA Astrophysics Data System (ADS)

Orzechowski, Piotr D.; Makal, Jaroslaw; Nazarkiewicz, Andrzej

2006-03-01

The paper presents Bayesian method application in the measure information diagnostic value assessment that is used in the computer-aided diagnosis system. The computer system described here has been created basing on the Bayesian Network and is used in Benign Prostatic Hyperplasia (BPH) diagnosis. The graphic diagnostic model enables to juxtapose experts' knowledge with data.

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.

Implementation of a low-cost mobile devices to support medical diagnosis.

PubMed

García Sánchez, Carlos; Botella Juan, Guillermo; Ayuso Márquez, Fermín; González Rodríguez, Diego; Prieto-Matías, Manuel; Tirado Fernández, Francisco

2013-01-01

Medical imaging has become an absolutely essential diagnostic tool for clinical practices; at present, pathologies can be detected with an earliness never before known. Its use has not only been relegated to the field of radiology but also, increasingly, to computer-based imaging processes prior to surgery. Motion analysis, in particular, plays an important role in analyzing activities or behaviors of live objects in medicine. This short paper presents several low-cost hardware implementation approaches for the new generation of tablets and/or smartphones for estimating motion compensation and segmentation in medical images. These systems have been optimized for breast cancer diagnosis using magnetic resonance imaging technology with several advantages over traditional X-ray mammography, for example, obtaining patient information during a short period. This paper also addresses the challenge of offering a medical tool that runs on widespread portable devices, both on tablets and/or smartphones to aid in patient diagnostics.

Implementation of a Low-Cost Mobile Devices to Support Medical Diagnosis

PubMed Central

García Sánchez, Carlos; Botella Juan, Guillermo; Ayuso Márquez, Fermín; González Rodríguez, Diego; Prieto-Matías, Manuel; Tirado Fernández, Francisco

2013-01-01

Medical imaging has become an absolutely essential diagnostic tool for clinical practices; at present, pathologies can be detected with an earliness never before known. Its use has not only been relegated to the field of radiology but also, increasingly, to computer-based imaging processes prior to surgery. Motion analysis, in particular, plays an important role in analyzing activities or behaviors of live objects in medicine. This short paper presents several low-cost hardware implementation approaches for the new generation of tablets and/or smartphones for estimating motion compensation and segmentation in medical images. These systems have been optimized for breast cancer diagnosis using magnetic resonance imaging technology with several advantages over traditional X-ray mammography, for example, obtaining patient information during a short period. This paper also addresses the challenge of offering a medical tool that runs on widespread portable devices, both on tablets and/or smartphones to aid in patient diagnostics. PMID:24489600

Deep learning for cardiac computer-aided diagnosis: benefits, issues & solutions.

PubMed

Loh, Brian C S; Then, Patrick H H

2017-01-01

Cardiovascular diseases are one of the top causes of deaths worldwide. In developing nations and rural areas, difficulties with diagnosis and treatment are made worse due to the deficiency of healthcare facilities. A viable solution to this issue is telemedicine, which involves delivering health care and sharing medical knowledge at a distance. Additionally, mHealth, the utilization of mobile devices for medical care, has also proven to be a feasible choice. The integration of telemedicine, mHealth and computer-aided diagnosis systems with the fields of machine and deep learning has enabled the creation of effective services that are adaptable to a multitude of scenarios. The objective of this review is to provide an overview of heart disease diagnosis and management, especially within the context of rural healthcare, as well as discuss the benefits, issues and solutions of implementing deep learning algorithms to improve the efficacy of relevant medical applications.

Deep learning for cardiac computer-aided diagnosis: benefits, issues & solutions

PubMed Central

Then, Patrick H. H.

2017-01-01

Cardiovascular diseases are one of the top causes of deaths worldwide. In developing nations and rural areas, difficulties with diagnosis and treatment are made worse due to the deficiency of healthcare facilities. A viable solution to this issue is telemedicine, which involves delivering health care and sharing medical knowledge at a distance. Additionally, mHealth, the utilization of mobile devices for medical care, has also proven to be a feasible choice. The integration of telemedicine, mHealth and computer-aided diagnosis systems with the fields of machine and deep learning has enabled the creation of effective services that are adaptable to a multitude of scenarios. The objective of this review is to provide an overview of heart disease diagnosis and management, especially within the context of rural healthcare, as well as discuss the benefits, issues and solutions of implementing deep learning algorithms to improve the efficacy of relevant medical applications. PMID:29184897

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.

Computer-aided diagnosis of HIE based on segmentation of MRI

NASA Astrophysics Data System (ADS)

Sun, Ziguang; Li, Chungui; Wang, Qin

2009-10-01

Computer-aided diagnosis has become one of the major research subjects in medical imaging and diagnostic radiology. Hypoxic-ischemic encephalopathy (HIE), remains a serious condition that causes significant mortality and long-term morbidity to neonates. We adopt self-organizing feature maps to segment the tissues, such as white matter and grey matter in the magnetic resonance images. The borderline between white matter and grey matter can be found and the doubtful regions along with the borderline can be localized, then the feature in doubtful regions can be quantified. The method can assist doctors to easily diagnose whether a neonate is ill with mild HIE.

Computer-Aided Diagnosis of Anterior Segment Eye Abnormalities using Visible Wavelength Image Analysis Based Machine Learning.

PubMed

S V, Mahesh Kumar; R, Gunasundari

2018-06-02

Eye disease is a major health problem among the elderly people. Cataract and corneal arcus are the major abnormalities that exist in the anterior segment eye region of aged people. Hence, computer-aided diagnosis of anterior segment eye abnormalities will be helpful for mass screening and grading in ophthalmology. In this paper, we propose a multiclass computer-aided diagnosis (CAD) system using visible wavelength (VW) eye images to diagnose anterior segment eye abnormalities. In the proposed method, the input VW eye images are pre-processed for specular reflection removal and the iris circle region is segmented using a circular Hough Transform (CHT)-based approach. The first-order statistical features and wavelet-based features are extracted from the segmented iris circle and used for classification. The Support Vector Machine (SVM) by Sequential Minimal Optimization (SMO) algorithm was used for the classification. In experiments, we used 228 VW eye images that belong to three different classes of anterior segment eye abnormalities. The proposed method achieved a predictive accuracy of 96.96% with 97% sensitivity and 99% specificity. The experimental results show that the proposed method has significant potential for use in clinical applications.

Computer-aided dermoscopy for diagnosis of melanoma

PubMed Central

Barzegari, Masoomeh; Ghaninezhad, Haiedeh; Mansoori, Parisa; Taheri, Arash; Naraghi, Zahra S; Asgari, Masood

2005-01-01

Background Computer-aided dermoscopy using artificial neural networks has been reported to be an accurate tool for the evaluation of pigmented skin lesions. We set out to determine the sensitivity and specificity of a computer-aided dermoscopy system for diagnosis of melanoma in Iranian patients. Methods We studied 122 pigmented skin lesions which were referred for diagnostic evaluation or cosmetic reasons. Each lesion was examined by two clinicians with naked eyes and all of their clinical diagnostic considerations were recorded. The lesions were analyzed using a microDERM® dermoscopy unit. The output value of the software for each lesion was a score between 0 and 10. All of the lesions were excised and examined histologically. Results Histopathological examination revealed melanoma in six lesions. Considering only the most likely clinical diagnosis, sensitivity and specificity of clinical examination for diagnosis of melanoma were 83% and 96%, respectively. Considering all clinical diagnostic considerations, the sensitivity and specificity were 100% and 89%. Choosing a cut-off point of 7.88 for dermoscopy score, the sensitivity and specificity of the score for diagnosis of melanoma were 83% and 96%, respectively. Setting the cut-off point at 7.34, the sensitivity and specificity were 100% and 90%. Conclusion The diagnostic accuracy of the dermoscopy system was at the level of clinical examination by dermatologists with naked eyes. This system may represent a useful tool for screening of melanoma, particularly at centers not experienced in the field of pigmented skin lesions. PMID:16000171

Advanced decision aiding techniques applicable to space

NASA Technical Reports Server (NTRS)

Kruchten, Robert J.

1987-01-01

RADC has had an intensive program to show the feasibility of applying advanced technology to Air Force decision aiding situations. Some aspects of the program, such as Satellite Autonomy, are directly applicable to space systems. For example, RADC has shown the feasibility of decision aids that combine the advantages of laser disks and computer generated graphics; decision aids that interface object-oriented programs with expert systems; decision aids that solve path optimization problems; etc. Some of the key techniques that could be used in space applications are reviewed. Current applications are reviewed along with their advantages and disadvantages, and examples are given of possible space applications. The emphasis is to share RADC experience in decision aiding techniques.

The Problem of Feedback in Hearing Aids.

ERIC Educational Resources Information Center

Kates, James M.

1991-01-01

This paper discusses the problem of feedback in hearing aids and offers examples based on a computer simulation of hearing aid behavior. The available technology for dealing with feedback is reviewed, and the new digital signal-processing approaches which may finally solve the feedback problem are described. (Author/DB)

Computer-aided drug discovery.

PubMed

Bajorath, Jürgen

2015-01-01

Computational approaches are an integral part of interdisciplinary drug discovery research. Understanding the science behind computational tools, their opportunities, and limitations is essential to make a true impact on drug discovery at different levels. If applied in a scientifically meaningful way, computational methods improve the ability to identify and evaluate potential drug molecules, but there remain weaknesses in the methods that preclude naïve applications. Herein, current trends in computer-aided drug discovery are reviewed, and selected computational areas are discussed. Approaches are highlighted that aid in the identification and optimization of new drug candidates. Emphasis is put on the presentation and discussion of computational concepts and methods, rather than case studies or application examples. As such, this contribution aims to provide an overview of the current methodological spectrum of computational drug discovery for a broad audience.

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.

Designing Efficient Self-Diagnosis Activities in the Physics Classroom

ERIC Educational Resources Information Center

Safadi, Rafi'

2017-01-01

Self-diagnosis (SD) activities require students to self-diagnose their solutions to problems that they solved on their own. This involves identifying where they went wrong and then explaining the nature of their errors--why they went wrong--aided by some form of support. Worked examples (WEs) are often used to support students in SD activities. A…

Dynamic MRI-based computer aided diagnostic systems for early detection of kidney transplant rejection: A survey

NASA Astrophysics Data System (ADS)

Mostapha, Mahmoud; Khalifa, Fahmi; Alansary, Amir; Soliman, Ahmed; Gimel'farb, Georgy; El-Baz, Ayman

2013-10-01

Early detection of renal transplant rejection is important to implement appropriate medical and immune therapy in patients with transplanted kidneys. In literature, a large number of computer-aided diagnostic (CAD) systems using different image modalities, such as ultrasound (US), magnetic resonance imaging (MRI), computed tomography (CT), and radionuclide imaging, have been proposed for early detection of kidney diseases. A typical CAD system for kidney diagnosis consists of a set of processing steps including: motion correction, segmentation of the kidney and/or its internal structures (e.g., cortex, medulla), construction of agent kinetic curves, functional parameter estimation, diagnosis, and assessment of the kidney status. In this paper, we survey the current state-of-the-art CAD systems that have been developed for kidney disease diagnosis using dynamic MRI. In addition, the paper addresses several challenges that researchers face in developing efficient, fast and reliable CAD systems for the early detection of kidney diseases.

EEG-Based Computer Aided Diagnosis of Autism Spectrum Disorder Using Wavelet, Entropy, and ANN

PubMed Central

AlSharabi, Khalil; Ibrahim, Sutrisno; Alsuwailem, Abdullah

2017-01-01

Autism spectrum disorder (ASD) is a type of neurodevelopmental disorder with core impairments in the social relationships, communication, imagination, or flexibility of thought and restricted repertoire of activity and interest. In this work, a new computer aided diagnosis (CAD) of autism ‎based on electroencephalography (EEG) signal analysis is investigated. The proposed method is based on discrete wavelet transform (DWT), entropy (En), and artificial neural network (ANN). DWT is used to decompose EEG signals into approximation and details coefficients to obtain EEG subbands. The feature vector is constructed by computing Shannon entropy values from each EEG subband. ANN classifies the corresponding EEG signal into normal or autistic based on the extracted features. The experimental results show the effectiveness of the proposed method for assisting autism diagnosis. A receiver operating characteristic (ROC) curve metric is used to quantify the performance of the proposed method. The proposed method obtained promising results tested using real dataset provided by King Abdulaziz Hospital, Jeddah, Saudi Arabia. PMID:28484720

Morphometric information to reduce the semantic gap in the characterization of microscopic images of thyroid nodules.

PubMed

Macedo, Alessandra A; Pessotti, Hugo C; Almansa, Luciana F; Felipe, Joaquim C; Kimura, Edna T

2016-07-01

The analyses of several systems for medical-imaging processing typically support the extraction of image attributes, but do not comprise some information that characterizes images. For example, morphometry can be applied to find new information about the visual content of an image. The extension of information may result in knowledge. Subsequently, results of mappings can be applied to recognize exam patterns, thus improving the accuracy of image retrieval and allowing a better interpretation of exam results. Although successfully applied in breast lesion images, the morphometric approach is still poorly explored in thyroid lesions due to the high subjectivity thyroid examinations. This paper presents a theoretical-practical study, considering Computer Aided Diagnosis (CAD) and Morphometry, to reduce the semantic discontinuity between medical image features and human interpretation of image content. The proposed method aggregates the content of microscopic images characterized by morphometric information and other image attributes extracted by traditional object extraction algorithms. This method carries out segmentation, feature extraction, image labeling and classification. Morphometric analysis was included as an object extraction method in order to verify the improvement of its accuracy for automatic classification of microscopic images. To validate this proposal and verify the utility of morphometric information to characterize thyroid images, a CAD system was created to classify real thyroid image-exams into Papillary Cancer, Goiter and Non-Cancer. Results showed that morphometric information can improve the accuracy and precision of image retrieval and the interpretation of results in computer-aided diagnosis. For example, in the scenario where all the extractors are combined with the morphometric information, the CAD system had its best performance (70% of precision in Papillary cases). Results signalized a positive use of morphometric information from images to reduce semantic discontinuity between human interpretation and image characterization. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

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.

[Usefulness of imaging examinations in preoperative diagnosis of acute appendicitis].

PubMed

Nitoń, Tomasz; Górecka-Nitoń, Aleksandra

2014-01-01

Acute appendicitis (AA) is the cause one of most operations perform in department of general surgery on emergency ward. Frequency of acute appendicitis range from 6-8% of population. Clinical presentation is frequently unspecified and despite common occurence leads to many difficulties in diagnosis. Diagnosis of acute appendicitis includes clinical examination, laboratory tests, diagnostic scoring systems, computer programs as physisian aids and imaging examinations. About 30-45% patients suspected of acute appendicitis have untypical clinical presentation and here use of US or CT is very helpful. Longstanding use of US resulted in high AA evaluation accuracy with high sensitivity (75-90%) and specificity (84-100%). CT demonstrates above 95% ratio of correct diagnoses, reduces negative appendectomy rates and perforation rates as well as unnecessary observations. CT sensitivity and specificity CT is estimated between 83-100% among different authors. Expedited AA diagnosis, surgery and reduced hospitalization time are possible advantages of imaging tests. Additionally these tests can detect alternative deseases imitating acute appnedicitis. Use of imaging tests especially CT is beneficial in fertile women because of frequent genito-urinary disorders leading to the most diagnostic errors. However thera are contraindications in use of CT, for example it can not be performed in early pregnancy etc...

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

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.

Optic cup segmentation from fundus images for glaucoma diagnosis.

PubMed

Hu, Man; Zhu, Chenghao; Li, Xiaoxing; Xu, Yongli

2017-01-02

Glaucoma is a serious disease that can cause complete, permanent blindness, and its early diagnosis is very difficult. In recent years, computer-aided screening and diagnosis of glaucoma has made considerable progress. The optic cup segmentation from fundus images is an extremely important part for the computer-aided screening and diagnosis of glaucoma. This paper presented an automatic optic cup segmentation method that used both color difference information and vessel bends information from fundus images to determine the optic cup boundary. During the implementation of this algorithm, not only were the locations of the 2 types of information points used, but also the confidences of the information points were evaluated. In this way, the information points with higher confidence levels contributed more to the determination of the final cup boundary. The proposed method was evaluated using a public database for fundus images. The experimental results demonstrated that the cup boundaries obtained by the proposed method were more consistent than existing methods with the results obtained by ophthalmologists.

Model–Free Visualization of Suspicious Lesions in Breast MRI Based on Supervised and Unsupervised Learning

PubMed Central

Twellmann, Thorsten; Meyer-Baese, Anke; Lange, Oliver; Foo, Simon; Nattkemper, Tim W.

2008-01-01

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) has become an important tool in breast cancer diagnosis, but evaluation of multitemporal 3D image data holds new challenges for human observers. To aid the image analysis process, we apply supervised and unsupervised pattern recognition techniques for computing enhanced visualizations of suspicious lesions in breast MRI data. These techniques represent an important component of future sophisticated computer-aided diagnosis (CAD) systems and support the visual exploration of spatial and temporal features of DCE-MRI data stemming from patients with confirmed lesion diagnosis. By taking into account the heterogeneity of cancerous tissue, these techniques reveal signals with malignant, benign and normal kinetics. They also provide a regional subclassification of pathological breast tissue, which is the basis for pseudo-color presentations of the image data. Intelligent medical systems are expected to have substantial implications in healthcare politics by contributing to the diagnosis of indeterminate breast lesions by non-invasive imaging. PMID:19255616

Optic cup segmentation from fundus images for glaucoma diagnosis

PubMed Central

Hu, Man; Zhu, Chenghao; Li, Xiaoxing; Xu, Yongli

2017-01-01

ABSTRACT Glaucoma is a serious disease that can cause complete, permanent blindness, and its early diagnosis is very difficult. In recent years, computer-aided screening and diagnosis of glaucoma has made considerable progress. The optic cup segmentation from fundus images is an extremely important part for the computer-aided screening and diagnosis of glaucoma. This paper presented an automatic optic cup segmentation method that used both color difference information and vessel bends information from fundus images to determine the optic cup boundary. During the implementation of this algorithm, not only were the locations of the 2 types of information points used, but also the confidences of the information points were evaluated. In this way, the information points with higher confidence levels contributed more to the determination of the final cup boundary. The proposed method was evaluated using a public database for fundus images. The experimental results demonstrated that the cup boundaries obtained by the proposed method were more consistent than existing methods with the results obtained by ophthalmologists. PMID:27764542

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

The LISS--a public database of common imaging signs of lung diseases for computer-aided detection and diagnosis research and medical education.

PubMed

Han, Guanghui; Liu, Xiabi; Han, Feifei; Santika, I Nyoman Tenaya; Zhao, Yanfeng; Zhao, Xinming; Zhou, Chunwu

2015-02-01

Lung computed tomography (CT) imaging signs play important roles in the diagnosis of lung diseases. In this paper, we review the significance of CT imaging signs in disease diagnosis and determine the inclusion criterion of CT scans and CT imaging signs of our database. We develop the software of abnormal regions annotation and design the storage scheme of CT images and annotation data. Then, we present a publicly available database of lung CT imaging signs, called LISS for short, which contains 271 CT scans and 677 abnormal regions in them. The 677 abnormal regions are divided into nine categories of common CT imaging signs of lung disease (CISLs). The ground truth of these CISLs regions and the corresponding categories are provided. Furthermore, to make the database publicly available, all private data in CT scans are eliminated or replaced with provisioned values. The main characteristic of our LISS database is that it is developed from a new perspective of CT imaging signs of lung diseases instead of commonly considered lung nodules. Thus, it is promising to apply to computer-aided detection and diagnosis research and medical education.

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.

Artificial Intelligence: An Analysis of Potential Applications to Training, Performance Measurement, and Job Performance Aiding.

DTIC Science & Technology

1983-09-01

AD-Ali33 592 ARTIFICIAL INTELLIGENCE: AN ANALYSIS OF POTENTIAL 1/1 APPLICATIONS TO TRAININ..(U) DENVER RESEARCH INST CO JRICHARDSON SEP 83 AFHRL-TP...83-28 b ’ 3 - 4. TITLE (aied Suhkie) 5. TYPE OF REPORT & PERIOD COVERED ARTIFICIAL INTEL11GENCE: AN ANALYSIS OF Interim POTENTIAL APPLICATIONS TO...8217 sde if neceseamy end ides*f by black naumber) artificial intelligence military research * computer-aided diagnosis performance tests computer

Assessing Mathematics Automatically Using Computer Algebra and the Internet

ERIC Educational Resources Information Center

Sangwin, Chris

2004-01-01

This paper reports some recent developments in mathematical computer-aided assessment which employs computer algebra to evaluate students' work using the Internet. Technical and educational issues raised by this use of computer algebra are addressed. Working examples from core calculus and algebra which have been used with first year university…

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

PubMed Central

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. PMID:27807415

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.

Using the Disease State Fingerprint Tool for Differential Diagnosis of Frontotemporal Dementia and Alzheimer's Disease

PubMed Central

Muñoz-Ruiz, Miguel Ángel; Hall, Anette; Mattila, Jussi; Koikkalainen, Juha; Herukka, Sanna-Kaisa; Husso, Minna; Hänninen, Tuomo; Vanninen, Ritva; Liu, Yawu; Hallikainen, Merja; Lötjönen, Jyrki; Remes, Anne M.; Alafuzoff, Irina; Soininen, Hilkka; Hartikainen, Päivi

2016-01-01

Background Disease State Index (DSI) and its visualization, Disease State Fingerprint (DSF), form a computer-assisted clinical decision making tool that combines patient data and compares them with cases with known outcomes. Aims To investigate the ability of the DSI to diagnose frontotemporal dementia (FTD) and Alzheimer's disease (AD). Methods The study cohort consisted of 38 patients with FTD, 57 with AD and 22 controls. Autopsy verification of FTD with TDP-43 positive pathology was available for 14 and AD pathology for 12 cases. We utilized data from neuropsychological tests, volumetric magnetic resonance imaging, single-photon emission tomography, cerebrospinal fluid biomarkers and the APOE genotype. The DSI classification results were calculated with a combination of leave-one-out cross-validation and bootstrapping. A DSF visualization of a FTD patient is presented as an example. Results The DSI distinguishes controls from FTD (area under the receiver-operator curve, AUC = 0.99) and AD (AUC = 1.00) very well and achieves a good differential diagnosis between AD and FTD (AUC = 0.89). In subsamples of autopsy-confirmed cases (AUC = 0.97) and clinically diagnosed cases (AUC = 0.94), differential diagnosis of AD and FTD performs very well. Conclusions DSI is a promising computer-assisted biomarker approach for aiding in the diagnostic process of dementing diseases. Here, DSI separates controls from dementia and differentiates between AD and FTD. PMID:27703465

Computer Aided Reading Diagnosis.

ERIC Educational Resources Information Center

McEneaney, John E.

Computer technologies are having an ever-increasing influence on educational research and practice in Russia and the United States. In Russia, a number of recent papers have focused on the application of the computer as a teaching tool and on its influence in instructional organization and planning. In the United States, there is a great deal of…

GUIDON. Technical Report #9.

ERIC Educational Resources Information Center

Clancey, William J.

GUIDON is an intelligent computer-aided instruction (ICAI) program for teaching diagnosis, which has been tested using the infectious disease diagnosis rules of the MYCIN consultation system developed at the Stanford University School of Medicine. GUIDON engages a student in a dialogue about a patient suspected of having an infection and thus…

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.

Computer-Based Tutoring of Visual Concepts: From Novice to Experts.

ERIC Educational Resources Information Center

Sharples, Mike

1991-01-01

Description of ways in which computers might be used to teach visual concepts discusses hypermedia systems; describes computer-generated tutorials; explains the use of computers to create learning aids such as concept maps, feature spaces, and structural models; and gives examples of visual concept teaching in medical education. (10 references)…

Computer-aided drug design for AMP-activated protein kinase activators.

PubMed

Wang, Zhanli; Huo, Jianxin; Sun, Lidan; Wang, Yongfu; Jin, Hongwei; Yu, Hui; Zhang, Liangren; Zhou, Lishe

2011-09-01

AMP-activated protein kinase (AMPK) is an important therapeutic target for the potential treatment of metabolic disorders, cardiovascular disease and cancer. Recently, various classes of compounds that activate AMPK by direct or indirect interactions have been reported. The importance of computer-aided drug design approaches in the search for potent activators of AMPK is now established, including structure-based design, ligand-based design, fragment-based design, as well as structural analysis. This review article highlights the computer-aided drug design approaches utilized to discover of activators targeting AMPK. The principles, advantages or limitation of the different methods are also being discussed together with examples of applications taken from the literatures.

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 drug discovery research at a global contract research organization

NASA Astrophysics Data System (ADS)

Kitchen, Douglas B.

2017-03-01

Computer-aided drug discovery started at Albany Molecular Research, Inc in 1997. Over nearly 20 years the role of cheminformatics and computational chemistry has grown throughout the pharmaceutical industry and at AMRI. This paper will describe the infrastructure and roles of CADD throughout drug discovery and some of the lessons learned regarding the success of several methods. Various contributions provided by computational chemistry and cheminformatics in chemical library design, hit triage, hit-to-lead and lead optimization are discussed. Some frequently used computational chemistry techniques are described. The ways in which they may contribute to discovery projects are presented based on a few examples from recent publications.

Computer-aided drug discovery research at a global contract research organization.

PubMed

Kitchen, Douglas B

2017-03-01

Computer-aided drug discovery started at Albany Molecular Research, Inc in 1997. Over nearly 20 years the role of cheminformatics and computational chemistry has grown throughout the pharmaceutical industry and at AMRI. This paper will describe the infrastructure and roles of CADD throughout drug discovery and some of the lessons learned regarding the success of several methods. Various contributions provided by computational chemistry and cheminformatics in chemical library design, hit triage, hit-to-lead and lead optimization are discussed. Some frequently used computational chemistry techniques are described. The ways in which they may contribute to discovery projects are presented based on a few examples from recent publications.

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 non-linear programming approach to the computer-aided design of regulators using a linear-quadratic formulation

NASA Technical Reports Server (NTRS)

Fleming, P.

1985-01-01

A design technique is proposed for linear regulators in which a feedback controller of fixed structure is chosen to minimize an integral quadratic objective function subject to the satisfaction of integral quadratic constraint functions. Application of a non-linear programming algorithm to this mathematically tractable formulation results in an efficient and useful computer-aided design tool. Particular attention is paid to computational efficiency and various recommendations are made. Two design examples illustrate the flexibility of the approach and highlight the special insight afforded to the designer.

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.

Unusual Radiographic Presentation of Pneumocystis Pneumonia in a Patient with AIDS.

PubMed

Block, Brian L; Mehta, Tejas; Ortiz, Gabriel M; Ferris, Sean P; Vu, Thienkhai H; Huang, Laurence; Cattamanchi, Adithya

2017-01-01

Pneumocystis jirovecii pneumonia (PCP) typically presents as an interstitial and alveolar process with ground glass opacities on chest computed tomography (CT). The absence of ground glass opacities on chest CT is thought to have a high negative predictive value for PCP in individuals with AIDS. Here, we report a case of PCP in a man with AIDS who presented to our hospital with subacute shortness of breath and a nonproductive cough. While his chest CT revealed diffuse nodular rather than ground glass opacities, bronchoscopy with bronchoalveolar lavage and transbronchial biopsies confirmed the diagnosis of PCP and did not identify additional pathogens. PCP was not the expected diagnosis based on chest CT, but it otherwise fit well with the patient's clinical and laboratory presentation. In the era of combination antiretroviral therapy, routine prophylaxis for PCP, and increased use of computed tomography, it may be that PCP will increasingly present with nonclassical chest radiographic patterns. Clinicians should be aware of this presentation when selecting diagnostic and management strategies.

Unusual Radiographic Presentation of Pneumocystis Pneumonia in a Patient with AIDS

PubMed Central

Mehta, Tejas; Ortiz, Gabriel M.; Ferris, Sean P.; Vu, Thienkhai H.; Huang, Laurence; Cattamanchi, Adithya

2017-01-01

Pneumocystis jirovecii pneumonia (PCP) typically presents as an interstitial and alveolar process with ground glass opacities on chest computed tomography (CT). The absence of ground glass opacities on chest CT is thought to have a high negative predictive value for PCP in individuals with AIDS. Here, we report a case of PCP in a man with AIDS who presented to our hospital with subacute shortness of breath and a nonproductive cough. While his chest CT revealed diffuse nodular rather than ground glass opacities, bronchoscopy with bronchoalveolar lavage and transbronchial biopsies confirmed the diagnosis of PCP and did not identify additional pathogens. PCP was not the expected diagnosis based on chest CT, but it otherwise fit well with the patient's clinical and laboratory presentation. In the era of combination antiretroviral therapy, routine prophylaxis for PCP, and increased use of computed tomography, it may be that PCP will increasingly present with nonclassical chest radiographic patterns. Clinicians should be aware of this presentation when selecting diagnostic and management strategies. PMID:29362681

Computer-Aided Diagnosis System for Alzheimer's Disease Using Different Discrete Transform Techniques.

PubMed

Dessouky, Mohamed M; Elrashidy, Mohamed A; Taha, Taha E; Abdelkader, Hatem M

2016-05-01

The different discrete transform techniques such as discrete cosine transform (DCT), discrete sine transform (DST), discrete wavelet transform (DWT), and mel-scale frequency cepstral coefficients (MFCCs) are powerful feature extraction techniques. This article presents a proposed computer-aided diagnosis (CAD) system for extracting the most effective and significant features of Alzheimer's disease (AD) using these different discrete transform techniques and MFCC techniques. Linear support vector machine has been used as a classifier in this article. Experimental results conclude that the proposed CAD system using MFCC technique for AD recognition has a great improvement for the system performance with small number of significant extracted features, as compared with the CAD system based on DCT, DST, DWT, and the hybrid combination methods of the different transform techniques. © The Author(s) 2015.

Computer-aided diagnosis software for vulvovaginal candidiasis detection from Pap smear images.

PubMed

Momenzadeh, Mohammadreza; Vard, Alireza; Talebi, Ardeshir; Mehri Dehnavi, Alireza; Rabbani, Hossein

2018-01-01

Vulvovaginal candidiasis (VVC) is a common gynecologic infection and it occurs when there is overgrowth of the yeast called Candida. VVC diagnosis is usually done by observing a Pap smear sample under a microscope and searching for the conidium and mycelium components of Candida. This manual method is time consuming, subjective and tedious. Any diagnosis tools that detect VVC, semi- or full-automatically, can be very helpful to pathologists. This article presents a computer aided diagnosis (CAD) software to improve human diagnosis of VVC from Pap smear samples. The proposed software is designed based on phenotypic and morphology features of the Candida in Pap smear sample images. This software provide a user-friendly interface which consists of a set of image processing tools and analytical results that helps to detect Candida and determine severity of illness. The software was evaluated on 200 Pap smear sample images and obtained specificity of 91.04% and sensitivity of 92.48% to detect VVC. As a result, the use of the proposed software reduces diagnostic time and can be employed as a second objective opinion for pathologists. © 2017 Wiley Periodicals, Inc.

Computer aided lung cancer diagnosis with deep learning algorithms

NASA Astrophysics Data System (ADS)

Sun, Wenqing; Zheng, Bin; Qian, Wei

2016-03-01

Deep learning is considered as a popular and powerful method in pattern recognition and classification. However, there are not many deep structured applications used in medical imaging diagnosis area, because large dataset is not always available for medical images. In this study we tested the feasibility of using deep learning algorithms for lung cancer diagnosis with the cases from Lung Image Database Consortium (LIDC) database. The nodules on each computed tomography (CT) slice were segmented according to marks provided by the radiologists. After down sampling and rotating we acquired 174412 samples with 52 by 52 pixel each and the corresponding truth files. Three deep learning algorithms were designed and implemented, including Convolutional Neural Network (CNN), Deep Belief Networks (DBNs), Stacked Denoising Autoencoder (SDAE). To compare the performance of deep learning algorithms with traditional computer aided diagnosis (CADx) system, we designed a scheme with 28 image features and support vector machine. The accuracies of CNN, DBNs, and SDAE are 0.7976, 0.8119, and 0.7929, respectively; the accuracy of our designed traditional CADx is 0.7940, which is slightly lower than CNN and DBNs. We also noticed that the mislabeled nodules using DBNs are 4% larger than using traditional CADx, this might be resulting from down sampling process lost some size information of the nodules.

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.

A Hierarchical Feature and Sample Selection Framework and Its Application for Alzheimer’s Disease Diagnosis

NASA Astrophysics Data System (ADS)

An, Le; Adeli, Ehsan; Liu, Mingxia; Zhang, Jun; Lee, Seong-Whan; Shen, Dinggang

2017-03-01

Classification is one of the most important tasks in machine learning. Due to feature redundancy or outliers in samples, using all available data for training a classifier may be suboptimal. For example, the Alzheimer’s disease (AD) is correlated with certain brain regions or single nucleotide polymorphisms (SNPs), and identification of relevant features is critical for computer-aided diagnosis. Many existing methods first select features from structural magnetic resonance imaging (MRI) or SNPs and then use those features to build the classifier. However, with the presence of many redundant features, the most discriminative features are difficult to be identified in a single step. Thus, we formulate a hierarchical feature and sample selection framework to gradually select informative features and discard ambiguous samples in multiple steps for improved classifier learning. To positively guide the data manifold preservation process, we utilize both labeled and unlabeled data during training, making our method semi-supervised. For validation, we conduct experiments on AD diagnosis by selecting mutually informative features from both MRI and SNP, and using the most discriminative samples for training. The superior classification results demonstrate the effectiveness of our approach, as compared with the rivals.

Calculation of the lateral-dynamic stability of aircraft

NASA Technical Reports Server (NTRS)

Raikh, A

1952-01-01

Graphs and formulas are given with the aid of which all the aerodynamic coefficients required for computing the lateral dynamic stability can be determined. A number of numerical examples are given for obtaining the stability derivatives and solving the characteristic-stability equation. Approximate formulas are derived with the aid of which rapid preliminary computations may be made and the stability coefficients corrected for certain modifications of the airplane. A derivation of the lateral-dynamic-stability equations is included.

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.

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.

Quantitative diagnosis of tongue cancer from histological images in an animal model

NASA Astrophysics Data System (ADS)

Lu, Guolan; Qin, Xulei; Wang, Dongsheng; Muller, Susan; Zhang, Hongzheng; Chen, Amy; Chen, Zhuo G.; Fei, Baowei

2016-03-01

We developed a chemically-induced oral cancer animal model and a computer aided method for tongue cancer diagnosis. The animal model allows us to monitor the progress of the lesions over time. Tongue tissue dissected from mice was sent for histological processing. Representative areas of hematoxylin and eosin stained tissue from tongue sections were captured for classifying tumor and non-tumor tissue. The image set used in this paper consisted of 214 color images (114 tumor and 100 normal tissue samples). A total of 738 color, texture, morphometry and topology features were extracted from the histological images. The combination of image features from epithelium tissue and its constituent nuclei and cytoplasm has been demonstrated to improve the classification results. With ten iteration nested cross validation, the method achieved an average sensitivity of 96.5% and a specificity of 99% for tongue cancer detection. The next step of this research is to apply this approach to human tissue for computer aided diagnosis of tongue cancer.

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

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.

Biomedical engineering at Sandia National Laboratories

NASA Astrophysics Data System (ADS)

Zanner, Mary Ann

1994-12-01

The potential exists to reduce or control some aspects of the U.S. health care expenditure without compromising health care delivery by developing carefully selected technologies which impact favorably on the health care system. A focused effort to develop such technologies is underway at Sandia National Laboratories. As a DOE National Laboratory, Sandia possesses a wealth of engineering and scientific expertise that can be readily applied to this critical national need. Appropriate mechanisms currently exist to allow transfer of technology from the laboratory to the private sector. Sandia's Biomedical Engineering Initiative addresses the development of properly evaluated, cost-effective medical technologies through team collaborations with the medical community. Technology development is subjected to certain criteria including wide applicability, earlier diagnoses, increased efficiency, cost-effectiveness and dual-use. Examples of Sandia's medical technologies include a noninvasive blood glucose sensor, computer aided mammographic screening, noninvasive fetal oximetry and blood gas measurement, burn diagnostics and laser debridement, telerobotics and ultrasonic scanning for prosthetic devices. Sandia National Laboratories has the potential to aid in directing medical technology development efforts which emphasize health care needs, earlier diagnosis, cost containment and improvement of the quality of life.

Computer aided diagnosis and treatment planning for developmental dysplasia of the hip

NASA Astrophysics Data System (ADS)

Li, Bin; Lu, Hongbing; Cai, Wenli; Li, Xiang; Meng, Jie; Liang, Zhengrong

2005-04-01

The developmental dysplasia of the hip (DDH) is a congenital malformation affecting the proximal femurs and acetabulum that are subluxatable, dislocatable, and dislocated. Early diagnosis and treatment is important because failure to diagnose and improper treatment can result in significant morbidity. In this paper, we designed and implemented a computer aided system for the diagnosis and treatment planning of this disease. With the design, the patient received CT (computed tomography) or MRI (magnetic resonance imaging) scan first. A mixture-based PV partial-volume algorithm was applied to perform bone segmentation on CT image, followed by three-dimensional (3D) reconstruction and display of the segmented image, demonstrating the special relationship between the acetabulum and femurs for visual judgment. Several standard procedures, such as Salter procedure, Pemberton procedure and Femoral Shortening osteotomy, were simulated on the screen to rehearse a virtual treatment plan. Quantitative measurement of Acetabular Index (AI) and Femoral Neck Anteversion (FNA) were performed on the 3D image for evaluation of DDH and treatment plans. PC graphics-card GPU architecture was exploited to accelerate the 3D rendering and geometric manipulation. The prototype system was implemented on PC/Windows environment and is currently under clinical trial on patient datasets.

Computer-aided diagnosis of melanoma using border and wavelet-based texture analysis.

PubMed

Garnavi, Rahil; Aldeen, Mohammad; Bailey, James

2012-11-01

This paper presents a novel computer-aided diagnosis system for melanoma. The novelty lies in the optimised selection and integration of features derived from textural, borderbased and geometrical properties of the melanoma lesion. The texture features are derived from using wavelet-decomposition, the border features are derived from constructing a boundaryseries model of the lesion border and analysing it in spatial and frequency domains, and the geometry features are derived from shape indexes. The optimised selection of features is achieved by using the Gain-Ratio method, which is shown to be computationally efficient for melanoma diagnosis application. Classification is done through the use of four classifiers; namely, Support Vector Machine, Random Forest, Logistic Model Tree and Hidden Naive Bayes. The proposed diagnostic system is applied on a set of 289 dermoscopy images (114 malignant, 175 benign) partitioned into train, validation and test image sets. The system achieves and accuracy of 91.26% and AUC value of 0.937, when 23 features are used. Other important findings include (i) the clear advantage gained in complementing texture with border and geometry features, compared to using texture information only, and (ii) higher contribution of texture features than border-based features in the optimised feature set.

Human problem solving performance in a fault diagnosis task

NASA Technical Reports Server (NTRS)

Rouse, W. B.

1978-01-01

It is proposed that humans in automated systems will be asked to assume the role of troubleshooter or problem solver and that the problems which they will be asked to solve in such systems will not be amenable to rote solution. The design of visual displays for problem solving in such situations is considered, and the results of two experimental investigations of human problem solving performance in the diagnosis of faults in graphically displayed network problems are discussed. The effects of problem size, forced-pacing, computer aiding, and training are considered. Results indicate that human performance deviates from optimality as problem size increases. Forced-pacing appears to cause the human to adopt fairly brute force strategies, as compared to those adopted in self-paced situations. Computer aiding substantially lessens the number of mistaken diagnoses by performing the bookkeeping portions of the task.

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

Computer-assisted education and interdisciplinary breast cancer diagnosis

NASA Astrophysics Data System (ADS)

Whatmough, Pamela; Gale, Alastair G.; Wilson, A. R. M.

1996-04-01

The diagnosis of breast disease for screening or symptomatic women is largely arrived at by a multi-disciplinary team. We report work on the development and assessment of an inter- disciplinary computer based learning system to support the diagnosis of this disease. The diagnostic process is first modelled from different viewpoints and then appropriate knowledge structures pertinent to the domains of radiologist, pathologist and surgeon are depicted. Initially the underlying inter-relationships of the mammographic diagnostic approach were detailed which is largely considered here. Ultimately a system is envisaged which will link these specialties and act as a diagnostic aid as well as a multi-media educational system.

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.

Interfacing Computer Aided Parallelization and Performance Analysis

NASA Technical Reports Server (NTRS)

Jost, Gabriele; Jin, Haoqiang; Labarta, Jesus; Gimenez, Judit; Biegel, Bryan A. (Technical Monitor)

2003-01-01

When porting sequential applications to parallel computer architectures, the program developer will typically go through several cycles of source code optimization and performance analysis. We have started a project to develop an environment where the user can jointly navigate through program structure and performance data information in order to make efficient optimization decisions. In a prototype implementation we have interfaced the CAPO computer aided parallelization tool with the Paraver performance analysis tool. We describe both tools and their interface and give an example for how the interface helps within the program development cycle of a benchmark code.

Letter to the Editor: Use of Publicly Available Image Resources

DOE PAGES

Armato, Samuel G.; Drukker, Karen; Li, Feng; ...

2017-05-11

Here we write with regard to the Academic Radiology article entitled, “Computer-aided Diagnosis for Lung Cancer: Usefulness of Nodule Heterogeneity” by Drs. Nishio and Nagashima (1). The authors also report on a computerized method to classify as benign or malignant lung nodules present in computed tomography (CT) scans.

Role of Artificial Intelligence Techniques (Automatic Classifiers) in Molecular Imaging Modalities in Neurodegenerative Diseases.

PubMed

Cascianelli, Silvia; Scialpi, Michele; Amici, Serena; Forini, Nevio; Minestrini, Matteo; Fravolini, Mario Luca; Sinzinger, Helmut; Schillaci, Orazio; Palumbo, Barbara

2017-01-01

Artificial Intelligence (AI) is a very active Computer Science research field aiming to develop systems that mimic human intelligence and is helpful in many human activities, including Medicine. In this review we presented some examples of the exploiting of AI techniques, in particular automatic classifiers such as Artificial Neural Network (ANN), Support Vector Machine (SVM), Classification Tree (ClT) and ensemble methods like Random Forest (RF), able to analyze findings obtained by positron emission tomography (PET) or single-photon emission tomography (SPECT) scans of patients with Neurodegenerative Diseases, in particular Alzheimer's Disease. We also focused our attention on techniques applied in order to preprocess data and reduce their dimensionality via feature selection or projection in a more representative domain (Principal Component Analysis - PCA - or Partial Least Squares - PLS - are examples of such methods); this is a crucial step while dealing with medical data, since it is necessary to compress patient information and retain only the most useful in order to discriminate subjects into normal and pathological classes. Main literature papers on the application of these techniques to classify patients with neurodegenerative disease extracting data from molecular imaging modalities are reported, showing that the increasing development of computer aided diagnosis systems is very promising to contribute to the diagnostic process.

A survey of an introduction to fault diagnosis algorithms

NASA Technical Reports Server (NTRS)

Mathur, F. P.

1972-01-01

This report surveys the field of diagnosis and introduces some of the key algorithms and heuristics currently in use. Fault diagnosis is an important and a rapidly growing discipline. This is important in the design of self-repairable computers because the present diagnosis resolution of its fault-tolerant computer is limited to a functional unit or processor. Better resolution is necessary before failed units can become partially reuseable. The approach that holds the greatest promise is that of resident microdiagnostics; however, that presupposes a microprogrammable architecture for the computer being self-diagnosed. The presentation is tutorial and contains examples. An extensive bibliography of some 220 entries is included.

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.

Comprehensive Modeling and Visualization of Cardiac Anatomy and Physiology from CT Imaging and Computer Simulations

PubMed Central

Sun, Peng; Zhou, Haoyin; Ha, Seongmin; Hartaigh, Bríain ó; Truong, Quynh A.; Min, James K.

2016-01-01

In clinical cardiology, both anatomy and physiology are needed to diagnose cardiac pathologies. CT imaging and computer simulations provide valuable and complementary data for this purpose. However, it remains challenging to gain useful information from the large amount of high-dimensional diverse data. The current tools are not adequately integrated to visualize anatomic and physiologic data from a complete yet focused perspective. We introduce a new computer-aided diagnosis framework, which allows for comprehensive modeling and visualization of cardiac anatomy and physiology from CT imaging data and computer simulations, with a primary focus on ischemic heart disease. The following visual information is presented: (1) Anatomy from CT imaging: geometric modeling and visualization of cardiac anatomy, including four heart chambers, left and right ventricular outflow tracts, and coronary arteries; (2) Function from CT imaging: motion modeling, strain calculation, and visualization of four heart chambers; (3) Physiology from CT imaging: quantification and visualization of myocardial perfusion and contextual integration with coronary artery anatomy; (4) Physiology from computer simulation: computation and visualization of hemodynamics (e.g., coronary blood velocity, pressure, shear stress, and fluid forces on the vessel wall). Substantially, feedback from cardiologists have confirmed the practical utility of integrating these features for the purpose of computer-aided diagnosis of ischemic heart disease. PMID:26863663

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

Centered Kernel Alignment Enhancing Neural Network Pretraining for MRI-Based Dementia Diagnosis

PubMed Central

Cárdenas-Peña, David; Collazos-Huertas, Diego; Castellanos-Dominguez, German

2016-01-01

Dementia is a growing problem that affects elderly people worldwide. More accurate evaluation of dementia diagnosis can help during the medical examination. Several methods for computer-aided dementia diagnosis have been proposed using resonance imaging scans to discriminate between patients with Alzheimer's disease (AD) or mild cognitive impairment (MCI) and healthy controls (NC). Nonetheless, the computer-aided diagnosis is especially challenging because of the heterogeneous and intermediate nature of MCI. We address the automated dementia diagnosis by introducing a novel supervised pretraining approach that takes advantage of the artificial neural network (ANN) for complex classification tasks. The proposal initializes an ANN based on linear projections to achieve more discriminating spaces. Such projections are estimated by maximizing the centered kernel alignment criterion that assesses the affinity between the resonance imaging data kernel matrix and the label target matrix. As a result, the performed linear embedding allows accounting for features that contribute the most to the MCI class discrimination. We compare the supervised pretraining approach to two unsupervised initialization methods (autoencoders and Principal Component Analysis) and against the best four performing classification methods of the 2014 CADDementia challenge. As a result, our proposal outperforms all the baselines (7% of classification accuracy and area under the receiver-operating-characteristic curve) at the time it reduces the class biasing. PMID:27148392

Towards Building a High Performance Spatial Query System for Large Scale Medical Imaging Data.

PubMed

Aji, Ablimit; Wang, Fusheng; Saltz, Joel H

2012-11-06

Support of high performance queries on large volumes of scientific spatial data is becoming increasingly important in many applications. This growth is driven by not only geospatial problems in numerous fields, but also emerging scientific applications that are increasingly data- and compute-intensive. For example, digital pathology imaging has become an emerging field during the past decade, where examination of high resolution images of human tissue specimens enables more effective diagnosis, prediction and treatment of diseases. Systematic analysis of large-scale pathology images generates tremendous amounts of spatially derived quantifications of micro-anatomic objects, such as nuclei, blood vessels, and tissue regions. Analytical pathology imaging provides high potential to support image based computer aided diagnosis. One major requirement for this is effective querying of such enormous amount of data with fast response, which is faced with two major challenges: the "big data" challenge and the high computation complexity. In this paper, we present our work towards building a high performance spatial query system for querying massive spatial data on MapReduce. Our framework takes an on demand index building approach for processing spatial queries and a partition-merge approach for building parallel spatial query pipelines, which fits nicely with the computing model of MapReduce. We demonstrate our framework on supporting multi-way spatial joins for algorithm evaluation and nearest neighbor queries for microanatomic objects. To reduce query response time, we propose cost based query optimization to mitigate the effect of data skew. Our experiments show that the framework can efficiently support complex analytical spatial queries on MapReduce.

Towards Building a High Performance Spatial Query System for Large Scale Medical Imaging Data

PubMed Central

Aji, Ablimit; Wang, Fusheng; Saltz, Joel H.

2013-01-01

Support of high performance queries on large volumes of scientific spatial data is becoming increasingly important in many applications. This growth is driven by not only geospatial problems in numerous fields, but also emerging scientific applications that are increasingly data- and compute-intensive. For example, digital pathology imaging has become an emerging field during the past decade, where examination of high resolution images of human tissue specimens enables more effective diagnosis, prediction and treatment of diseases. Systematic analysis of large-scale pathology images generates tremendous amounts of spatially derived quantifications of micro-anatomic objects, such as nuclei, blood vessels, and tissue regions. Analytical pathology imaging provides high potential to support image based computer aided diagnosis. One major requirement for this is effective querying of such enormous amount of data with fast response, which is faced with two major challenges: the “big data” challenge and the high computation complexity. In this paper, we present our work towards building a high performance spatial query system for querying massive spatial data on MapReduce. Our framework takes an on demand index building approach for processing spatial queries and a partition-merge approach for building parallel spatial query pipelines, which fits nicely with the computing model of MapReduce. We demonstrate our framework on supporting multi-way spatial joins for algorithm evaluation and nearest neighbor queries for microanatomic objects. To reduce query response time, we propose cost based query optimization to mitigate the effect of data skew. Our experiments show that the framework can efficiently support complex analytical spatial queries on MapReduce. PMID:24501719

Structure and Computation in Immunoreagent Design: From Diagnostics to Vaccines.

PubMed

Gourlay, Louise; Peri, Claudio; Bolognesi, Martino; Colombo, Giorgio

2017-12-01

Novel immunological tools for efficient diagnosis and treatment of emerging infections are urgently required. Advances in the diagnostic and vaccine development fields are continuously progressing, with reverse vaccinology and structural vaccinology (SV) methods for antigen identification and structure-based antigen (re)design playing increasingly relevant roles. SV, in particular, is predicted to be the front-runner in the future development of diagnostics and vaccines targeting challenging diseases such as AIDS and cancer. We review state-of-the-art methodologies for structure-based epitope identification and antigen design, with specific applicative examples. We highlight the implications of such methods for the engineering of biomolecules with improved immunological properties, potential diagnostic and/or therapeutic uses, and discuss the perspectives of structure-based rational design for the production of advanced immunoreagents. Copyright © 2017 Elsevier Ltd. All rights reserved.

Multidetector CT of blunt traumatic venous injuries in the chest, abdomen, and pelvis.

PubMed

Holly, Brian P; Steenburg, Scott D

2011-01-01

Venous injuries as a result of blunt trauma are rare. Even though current protocols for multidetector computed tomography (CT) of patients with trauma are designed to evaluate primarily the solid organs and arteries, blunt venous injuries may nevertheless be identified, or at least suspected, on the basis of the multidetector CT findings. Venous injuries are associated with high morbidity and mortality rates. Diagnosis of a possible venous injury is crucial because the physical findings of a venous injury are nonspecific and may be absent. This article aims to make the radiologist aware of various venous injuries caused by blunt trauma and to provide helpful hints to aid in the identification of venous injuries. Multidetector CT technology, in combination with interactive manipulation of the raw dataset, can be useful in the creation of multiplanar reconstructed images and in the identification of a venous injury caused by blunt trauma. Familiarity with direct and indirect signs of venous injuries, as well as with examples of blunt traumatic venous injuries in the chest, abdomen, and pelvis, will help in the diagnosis of these injuries.

Thermo-mechanical design aspects of mercury bombardment ion thrusters.

NASA Technical Reports Server (NTRS)

Schnelker, D. E.; Kami, S.

1972-01-01

The mechanical design criteria are presented as background considerations for solving problems associated with the thermomechanical design of mercury ion bombardment thrusters. Various analytical procedures are used to aid in the development of thruster subassemblies and components in the fields of heat transfer, vibration, and stress analysis. Examples of these techniques which provide computer solutions to predict and control stress levels encountered during launch and operation of thruster systems are discussed. Computer models of specific examples are presented.

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

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

Bridging the integration gap between imaging and information systems: a uniform data concept for content-based image retrieval in computer-aided diagnosis.

PubMed

Welter, Petra; Riesmeier, Jörg; Fischer, Benedikt; Grouls, Christoph; Kuhl, Christiane; Deserno, Thomas M

2011-01-01

It is widely accepted that content-based image retrieval (CBIR) can be extremely useful for computer-aided diagnosis (CAD). However, CBIR has not been established in clinical practice yet. As a widely unattended gap of integration, a unified data concept for CBIR-based CAD results and reporting is lacking. Picture archiving and communication systems and the workflow of radiologists must be considered for successful data integration to be achieved. We suggest that CBIR systems applied to CAD should integrate their results in a picture archiving and communication systems environment such as Digital Imaging and Communications in Medicine (DICOM) structured reporting documents. A sample DICOM structured reporting template adaptable to CBIR and an appropriate integration scheme is presented. The proposed CBIR data concept may foster the promulgation of CBIR systems in clinical environments and, thereby, improve the diagnostic process.

Bridging the integration gap between imaging and information systems: a uniform data concept for content-based image retrieval in computer-aided diagnosis

PubMed Central

Riesmeier, Jörg; Fischer, Benedikt; Grouls, Christoph; Kuhl, Christiane; Deserno (né Lehmann), Thomas M

2011-01-01

It is widely accepted that content-based image retrieval (CBIR) can be extremely useful for computer-aided diagnosis (CAD). However, CBIR has not been established in clinical practice yet. As a widely unattended gap of integration, a unified data concept for CBIR-based CAD results and reporting is lacking. Picture archiving and communication systems and the workflow of radiologists must be considered for successful data integration to be achieved. We suggest that CBIR systems applied to CAD should integrate their results in a picture archiving and communication systems environment such as Digital Imaging and Communications in Medicine (DICOM) structured reporting documents. A sample DICOM structured reporting template adaptable to CBIR and an appropriate integration scheme is presented. The proposed CBIR data concept may foster the promulgation of CBIR systems in clinical environments and, thereby, improve the diagnostic process. PMID:21672913

Commentary: Objective aids for the assessment of ADHD - further clarification of what FDA approval for marketing means and why NEBA might help clinicians. A response to Arns et al. (2016).

PubMed

Stein, Mark A; Snyder, Steven M; Rugino, Thomas A; Hornig, Mady

2016-06-01

Neuropsychiatric EEG-Based ADHD Assessment Aid (NEBA) is an EEG-based device designed to aid in the diagnostic process for ADHD by identifying individuals less likely to have ADHD by virtue of a lower theta/beta ratio. In using NEBA as an example, the Arns et al. commentary misstates the purpose of NEBA, which is to widen the differential rather than to make the diagnosis. Arns et al. caution about missing an ADHD diagnosis, but fail to mention the impact of overdiagnosis. If we are to advance our knowledge of the etiology and pathophysiology of ADHD, as well as develop tailored treatments and ultimately improve outcomes for ADHD, then biomarkers and objective assessment aids such as NEBA are needed to improve and refine diagnostic accuracy beyond symptom description and clinical history. © 2016 The Authors. Journal of Child Psychology and Psychiatry published by John Wiley & Sons Ltd on behalf of Association for Child and Adolescent Mental Health.

A fast algorithm for computer aided collimation gamma camera (CACAO)

NASA Astrophysics Data System (ADS)

Jeanguillaume, C.; Begot, S.; Quartuccio, M.; Douiri, A.; Franck, D.; Pihet, P.; Ballongue, P.

2000-08-01

The computer aided collimation gamma camera is aimed at breaking down the resolution sensitivity trade-off of the conventional parallel hole collimator. It uses larger and longer holes, having an added linear movement at the acquisition sequence. A dedicated algorithm including shift and sum, deconvolution, parabolic filtering and rotation is described. Examples of reconstruction are given. This work shows that a simple and fast algorithm, based on a diagonal dominant approximation of the problem can be derived. Its gives a practical solution to the CACAO reconstruction problem.

Influence of Computer-Aided Detection on Performance of Screening Mammography

PubMed Central

Fenton, Joshua J.; Taplin, Stephen H.; Carney, Patricia A.; Abraham, Linn; Sickles, Edward A.; D'Orsi, Carl; Berns, Eric A.; Cutter, Gary; Hendrick, R. Edward; Barlow, William E.; Elmore, Joann G.

2011-01-01

Background Computer-aided detection identifies suspicious findings on mammograms to assist radiologists. Since the Food and Drug Administration approved the technology in 1998, it has been disseminated into practice, but its effect on the accuracy of interpretation is unclear. Methods We determined the association between the use of computer-aided detection at mammography facilities and the performance of screening mammography from 1998 through 2002 at 43 facilities in three states. We had complete data for 222,135 women (a total of 429,345 mammograms), including 2351 women who received a diagnosis of breast cancer within 1 year after screening. We calculated the specificity, sensitivity, and positive predictive value of screening mammography with and without computer-aided detection, as well as the rates of biopsy and breast-cancer detection and the overall accuracy, measured as the area under the receiver-operating-characteristic (ROC) curve. Results Seven facilities (16%) implemented computer-aided detection during the study period. Diagnostic specificity decreased from 90.2% before implementation to 87.2% after implementation (P<0.001), the positive predictive value decreased from 4.1% to 3.2% (P = 0.01), and the rate of biopsy increased by 19.7% (P<0.001). The increase in sensitivity from 80.4% before implementation of computer-aided detection to 84.0% after implementation was not significant (P = 0.32). The change in the cancer-detection rate (including invasive breast cancers and ductal carcinomas in situ) was not significant (4.15 cases per 1000 screening mammograms before implementation and 4.20 cases after implementation, P = 0.90). Analyses of data from all 43 facilities showed that the use of computer-aided detection was associated with significantly lower overall accuracy than was nonuse (area under the ROC curve, 0.871 vs. 0.919; P = 0.005). Conclusions The use of computer-aided detection is associated with reduced accuracy of interpretation of screening mammograms. The increased rate of biopsy with the use of computer-aided detection is not clearly associated with improved detection of invasive breast cancer. PMID:17409321

NAS: The first year

NASA Technical Reports Server (NTRS)

Bailey, F. R.; Kutler, Paul

1988-01-01

Discussed are the capabilities of NASA's Numerical Aerodynamic Simulation (NAS) Program and its application as an advanced supercomputing system for computational fluid dynamics (CFD) research. First, the paper describes the NAS computational system, called the NAS Processing System Network, and the advanced computational capabilities it offers as a consequence of carrying out the NAS pathfinder objective. Second, it presents examples of pioneering CFD research accomplished during NAS's first operational year. Examples are included which illustrate CFD applications for predicting fluid phenomena, complementing and supplementing experimentation, and aiding in design. Finally, pacing elements and future directions for CFD and NAS are discussed.

Ultrasound introscopic image quantitative characteristics for medical diagnosis

NASA Astrophysics Data System (ADS)

Novoselets, Mikhail K.; Sarkisov, Sergey S.; Gridko, Alexander N.; Tcheban, Anatoliy K.

1993-09-01

The results on computer aided extraction of quantitative characteristics (QC) of ultrasound introscopic images for medical diagnosis are presented. Thyroid gland (TG) images of Chernobil Accident sufferers are considered. It is shown that TG diseases can be associated with some values of selected QCs of random echo distribution in the image. The possibility of these QCs usage for TG diseases recognition in accordance with calculated values is analyzed. The role of speckle noise elimination in the solution of the problem on TG diagnosis is considered too.

Dr. Lindberg's Legacy : Charting A New Course | NIH MedlinePlus the Magazine

MedlinePlus

... technology, artificial intelligence, computer-aided medical diagnosis, and electronic health records. As the first President of the ... about it—when Don began, NLM had no electronic journals in its collection, few people owned personal ...

AIDS: The Role of Imaging Modalities and Infection Control Policies

PubMed Central

Moore-Stovall, Joyce

1988-01-01

The availability of imaging modalities, such as the chest radiograph, gallium scan, double-contrast barium enema, computed tomography, and nuclear magnetic resonance, are very helpful in the diagnosis, treatment, and follow-up evaluation of patients with acquired immunodeficiency syndrome (AIDS). Because this syndrome causes irreversible destruction of the immune system, patients are susceptible to a multitude of opportunistic infections and malignancies. Health care professionals and the general public would be less fearful and apprehensive of AIDS victims if properly informed about the communicability of this syndrome. PMID:3047412

Computer-aided diagnosis and artificial intelligence in clinical imaging.

PubMed

Shiraishi, Junji; Li, Qiang; Appelbaum, Daniel; Doi, Kunio

2011-11-01

Computer-aided diagnosis (CAD) is rapidly entering the radiology mainstream. It has already become a part of the routine clinical work for the detection of breast cancer with mammograms. The computer output is used as a "second opinion" in assisting radiologists' image interpretations. The computer algorithm generally consists of several steps that may include image processing, image feature analysis, and data classification via the use of tools such as artificial neural networks (ANN). In this article, we will explore these and other current processes that have come to be referred to as "artificial intelligence." One element of CAD, temporal subtraction, has been applied for enhancing interval changes and for suppressing unchanged structures (eg, normal structures) between 2 successive radiologic images. To reduce misregistration artifacts on the temporal subtraction images, a nonlinear image warping technique for matching the previous image to the current one has been developed. Development of the temporal subtraction method originated with chest radiographs, with the method subsequently being applied to chest computed tomography (CT) and nuclear medicine bone scans. The usefulness of the temporal subtraction method for bone scans was demonstrated by an observer study in which reading times and diagnostic accuracy improved significantly. An additional prospective clinical study verified that the temporal subtraction image could be used as a "second opinion" by radiologists with negligible detrimental effects. ANN was first used in 1990 for computerized differential diagnosis of interstitial lung diseases in CAD. Since then, ANN has been widely used in CAD schemes for the detection and diagnosis of various diseases in different imaging modalities, including the differential diagnosis of lung nodules and interstitial lung diseases in chest radiography, CT, and position emission tomography/CT. It is likely that CAD will be integrated into picture archiving and communication systems and will become a standard of care for diagnostic examinations in daily clinical work. Copyright © 2011 Elsevier Inc. All rights reserved.

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.

Vascular tissue engineering by computer-aided laser micromachining.

PubMed

Doraiswamy, Anand; Narayan, Roger J

2010-04-28

Many conventional technologies for fabricating tissue engineering scaffolds are not suitable for fabricating scaffolds with patient-specific attributes. For example, many conventional technologies for fabricating tissue engineering scaffolds do not provide control over overall scaffold geometry or over cell position within the scaffold. In this study, the use of computer-aided laser micromachining to create scaffolds for vascular tissue networks was investigated. Computer-aided laser micromachining was used to construct patterned surfaces in agarose or in silicon, which were used for differential adherence and growth of cells into vascular tissue networks. Concentric three-ring structures were fabricated on agarose hydrogel substrates, in which the inner ring contained human aortic endothelial cells, the middle ring contained HA587 human elastin and the outer ring contained human aortic vascular smooth muscle cells. Basement membrane matrix containing vascular endothelial growth factor and heparin was to promote proliferation of human aortic endothelial cells within the vascular tissue networks. Computer-aided laser micromachining provides a unique approach to fabricate small-diameter blood vessels for bypass surgery as well as other artificial tissues with complex geometries.

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.

Operational Assessment of Color Vision

DTIC Science & Technology

2016-06-20

evaluated in this study. 15. SUBJECT TERMS Color vision, aviation, cone contrast test, Colour Assessment & Diagnosis , color Dx, OBVA 16. SECURITY...symbologies are frequently used to aid or direct critical activities such as aircraft landing approaches or railroad right-of-way designations...computer-generated display systems have facilitated the development of computer-based, automated tests of color vision [14,15]. The United Kingdom’s

FIESTA: An operational decision aid for space network fault isolation

NASA Technical Reports Server (NTRS)

Lowe, Dawn; Quillin, Bob; Matteson, Nadine; Wilkinson, Bill; Miksell, Steve

1987-01-01

The Fault Tolerance Expert System for Tracking and Data Relay Satellite System (TDRSS) Applications (FIESTA) is a fault detection and fault diagnosis expert system being developed as a decision aid to support operations in the Network Control Center (NCC) for NASA's Space Network. The operational objectives which influenced FIESTA development are presented and an overview of the architecture used to achieve these goals are provided. The approach to the knowledge engineering effort and the methodology employed are also presented and illustrated with examples drawn from the FIESTA domain.

Computers as Instructional Aids.

ERIC Educational Resources Information Center

Wright, Anne

The use of microcomputers as word processors for writing papers is commonplace in English departments, but there are many less well-known uses that English teachers can make of the computer. For example, word processing programs can be used to teach sentence combining. Moving text on the screen is very easy, so it is possible to rearrange words or…

Using Software Tools to Automate the Assessment of Student Programs.

ERIC Educational Resources Information Center

Jackson, David

1991-01-01

Argues that advent of computer-aided instruction (CAI) systems for teaching introductory computer programing makes it imperative that software be developed to automate assessment and grading of student programs. Examples of typical student programing problems are given, and application of the Unix tools Lex and Yacc to the automatic assessment of…

Example Based Pedagogical Strategies in a Computer Science Intelligent Tutoring System

ERIC Educational Resources Information Center

Green, Nicholas

2017-01-01

Worked-out examples are a common teaching strategy that aids learners in understanding concepts by use of step-by-step instruction. Literature has shown that they can be extremely beneficial, with a large body of material showing they can provide benefits over regular problem solving alone. This research looks into the viability of using this…

Computer-Aided Diagnosis for Breast Ultrasound Using Computerized BI-RADS Features and Machine Learning Methods.

PubMed

Shan, Juan; Alam, S Kaisar; Garra, Brian; Zhang, Yingtao; Ahmed, Tahira

2016-04-01

This work identifies effective computable features from the Breast Imaging Reporting and Data System (BI-RADS), to develop a computer-aided diagnosis (CAD) system for breast ultrasound. Computerized features corresponding to ultrasound BI-RADs categories were designed and tested using a database of 283 pathology-proven benign and malignant lesions. Features were selected based on classification performance using a "bottom-up" approach for different machine learning methods, including decision tree, artificial neural network, random forest and support vector machine. Using 10-fold cross-validation on the database of 283 cases, the highest area under the receiver operating characteristic (ROC) curve (AUC) was 0.84 from a support vector machine with 77.7% overall accuracy; the highest overall accuracy, 78.5%, was from a random forest with the AUC 0.83. Lesion margin and orientation were optimum features common to all of the different machine learning methods. These features can be used in CAD systems to help distinguish benign from worrisome lesions. Copyright © 2016 World Federation for Ultrasound in Medicine & Biology. All rights reserved.

[An integrated segmentation method for 3D ultrasound carotid artery].

PubMed

Yang, Xin; Wu, Huihui; Liu, Yang; Xu, Hongwei; Liang, Huageng; Cai, Wenjuan; Fang, Mengjie; Wang, Yujie

2013-07-01

An integrated segmentation method for 3D ultrasound carotid artery was proposed. 3D ultrasound image was sliced into transverse, coronal and sagittal 2D images on the carotid bifurcation point. Then, the three images were processed respectively, and the carotid artery contours and thickness were obtained finally. This paper tries to overcome the disadvantages of current computer aided diagnosis method, such as high computational complexity, easily introduced subjective errors et al. The proposed method could get the carotid artery overall information rapidly, accurately and completely. It could be transplanted into clinical usage for atherosclerosis diagnosis and prevention.

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.

Computer-aided diagnostic detection system of venous beading in retinal images

NASA Astrophysics Data System (ADS)

Yang, Ching-Wen; Ma, DyeJyun; Chao, ShuennChing; Wang, ChuinMu; Wen, Chia-Hsien; Lo, ChienShun; Chung, Pau-Choo; Chang, Chein-I.

2000-05-01

The detection of venous beading in retinal images provides an early sign of diabetic retinopathy and plays an important role as a preprocessing step in diagnosing ocular diseases. We present a computer-aided diagnostic system to automatically detect venous beading of blood vessels. It comprises of two modules, referred to as the blood vessel extraction module and the venus beading detection module. The former uses a bell-shaped Gaussian kernel with 12 azimuths to extract blood vessels while the latter applies a neural network-based shape cognitron to detect venous beading among the extracted blood vessels for diagnosis. Both modules are fully computer-automated. To evaluate the proposed system, 61 retinal images (32 beaded and 29 normal images) are used for performance evaluation.

Medical image analysis with artificial neural networks.

PubMed

Jiang, J; Trundle, P; Ren, J

2010-12-01

Given that neural networks have been widely reported in the research community of medical imaging, we provide a focused literature survey on recent neural network developments in computer-aided diagnosis, medical image segmentation and edge detection towards visual content analysis, and medical image registration for its pre-processing and post-processing, with the aims of increasing awareness of how neural networks can be applied to these areas and to provide a foundation for further research and practical development. Representative techniques and algorithms are explained in detail to provide inspiring examples illustrating: (i) how a known neural network with fixed structure and training procedure could be applied to resolve a medical imaging problem; (ii) how medical images could be analysed, processed, and characterised by neural networks; and (iii) how neural networks could be expanded further to resolve problems relevant to medical imaging. In the concluding section, a highlight of comparisons among many neural network applications is included to provide a global view on computational intelligence with neural networks in medical imaging. Copyright © 2010 Elsevier Ltd. All rights reserved.

Application of infrared thermography in computer aided diagnosis

NASA Astrophysics Data System (ADS)

Faust, Oliver; Rajendra Acharya, U.; Ng, E. Y. K.; Hong, Tan Jen; Yu, Wenwei

2014-09-01

The invention of thermography, in the 1950s, posed a formidable problem to the research community: What is the relationship between disease and heat radiation captured with Infrared (IR) cameras? The research community responded with a continuous effort to find this crucial relationship. This effort was aided by advances in processing techniques, improved sensitivity and spatial resolution of thermal sensors. However, despite this progress fundamental issues with this imaging modality still remain. The main problem is that the link between disease and heat radiation is complex and in many cases even non-linear. Furthermore, the change in heat radiation as well as the change in radiation pattern, which indicate disease, is minute. On a technical level, this poses high requirements on image capturing and processing. On a more abstract level, these problems lead to inter-observer variability and on an even more abstract level they lead to a lack of trust in this imaging modality. In this review, we adopt the position that these problems can only be solved through a strict application of scientific principles and objective performance assessment. Computing machinery is inherently objective; this helps us to apply scientific principles in a transparent way and to assess the performance results. As a consequence, we aim to promote thermography based Computer-Aided Diagnosis (CAD) systems. Another benefit of CAD systems comes from the fact that the diagnostic accuracy is linked to the capability of the computing machinery and, in general, computers become ever more potent. We predict that a pervasive application of computers and networking technology in medicine will help us to overcome the shortcomings of any single imaging modality and this will pave the way for integrated health care systems which maximize the quality of patient care.

Asymmetry in mesial root number and morphology in mandibular second molars: a case report

PubMed Central

Shetty, Shashit; Shekhar, Rhitu

2014-01-01

Ambiguity in the root morphology of the mandibular second molars is quite common. The most common root canal configuration is 2 roots and 3 canals, nonetheless other possibilities may still exist. The presence of accessory roots is an interesting example of anatomic root variation. While the presence of radix entomolaris or radix paramolaris is regarded as a typical clinical finding of a three-rooted mandibular second permanent molar, the occurrence of an additional mesial root is rather uncommon and represents a possibility of deviation from the regular norms. This case report describes successful endodontic management of a three-rooted mandibular second molar presenting with an unusual accessory mesial root, which was identified with the aid of multiangled radiographs and cone-beam computed tomography imaging. This article also discusses the prevalence, etiology, morphological variations, clinical approach to diagnosis, and significance of supernumerary roots in contemporary clinical dentistry. PMID:24516829

ICADx: interpretable computer aided diagnosis of breast masses

NASA Astrophysics Data System (ADS)

Kim, Seong Tae; Lee, Hakmin; Kim, Hak Gu; Ro, Yong Man

2018-02-01

In this study, a novel computer aided diagnosis (CADx) framework is devised to investigate interpretability for classifying breast masses. Recently, a deep learning technology has been successfully applied to medical image analysis including CADx. Existing deep learning based CADx approaches, however, have a limitation in explaining the diagnostic decision. In real clinical practice, clinical decisions could be made with reasonable explanation. So current deep learning approaches in CADx are limited in real world deployment. In this paper, we investigate interpretability in CADx with the proposed interpretable CADx (ICADx) framework. The proposed framework is devised with a generative adversarial network, which consists of interpretable diagnosis network and synthetic lesion generative network to learn the relationship between malignancy and a standardized description (BI-RADS). The lesion generative network and the interpretable diagnosis network compete in an adversarial learning so that the two networks are improved. The effectiveness of the proposed method was validated on public mammogram database. Experimental results showed that the proposed ICADx framework could provide the interpretability of mass as well as mass classification. It was mainly attributed to the fact that the proposed method was effectively trained to find the relationship between malignancy and interpretations via the adversarial learning. These results imply that the proposed ICADx framework could be a promising approach to develop the CADx system.

Computer-aided design of antenna structures and components

NASA Technical Reports Server (NTRS)

Levy, R.

1976-01-01

This paper discusses computer-aided design procedures for antenna reflector structures and related components. The primary design aid is a computer program that establishes cross sectional sizes of the structural members by an optimality criterion. Alternative types of deflection-dependent objectives can be selected for designs subject to constraints on structure weight. The computer program has a special-purpose formulation to design structures of the type frequently used for antenna construction. These structures, in common with many in other areas of application, are represented by analytical models that employ only the three translational degrees of freedom at each node. The special-purpose construction of the program, however, permits coding and data management simplifications that provide advantages in problem size and execution speed. Size and speed are essentially governed by the requirements of structural analysis and are relatively unaffected by the added requirements of design. Computation times to execute several design/analysis cycles are comparable to the times required by general-purpose programs for a single analysis cycle. Examples in the paper illustrate effective design improvement for structures with several thousand degrees of freedom and within reasonable computing times.

A review of critical in-flight events research methodology

NASA Technical Reports Server (NTRS)

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

1985-01-01

Pilot's cognitive responses to critical in-flight events (CIFE's) were investigated, using pilots, who had on the average about 2540 flight hours each, in four experiments: (1) full-mission simulation in a general aviation trainer, (2) paper and pencil CIFE tests, (3) interactive computer-aided scenario testing, and (4) verbal protocols in fault diagnosis tasks. The results of both computer and paper and pencil tests showed only 50 percent efficiency in correct diagnosis of critical events. The efficiency in arriving at a diagnosis was also low: over 20 inquiries were made for 21 percent of the scenarios diagnosed. The information-seeking pattern was random, with frequent retracing over old inquiries. The measures for developing improved cognitive skills for CIFE's are discussed.

Does positron emission tomography/computed tomography aid the diagnosis of prosthetic valve infective endocarditis?

PubMed

Balmforth, Damian; Chacko, Jacob; Uppal, Rakesh

2016-10-01

A best evidence topic was constructed according to a structured protocol. The question addressed was whether (18)F-fluorodeoxyglucose positron emission tomography/computed tomography (PET/CT) aids the diagnosis of prosthetic valve endocarditis (PVE)? A total of 107 publications were found using the reported search, of which 6 represented the best evidence to answer the clinical question. The authors, journal, date and country of publication, patient group studied, study type, relevant outcomes and results of these papers are tabulated. The reported outcome of all studies was a final diagnosis of confirmed endocarditis on follow-up. All the six studies were non-randomized, single-centre, observational studies and thus represented level 3 evidence. The diagnostic capability of PET/CT for PVE was compared with that of the modified Duke Criteria and echocardiography, and reported in terms of sensitivity, specificity and positive and negative predictive values. All studies demonstrated an increased sensitivity for the diagnosis of PVE when PET/CT was combined with the modified Duke Criteria on admission. A higher SUVmax on PET was found to be significantly associated with a confirmed diagnosis of endocarditis and an additional diagnostic benefit of PET/CT angiography over conventional PET/non-enhanced CT is reported due to improved anatomical resolution. However, PET/CT was found to be unreliable in the early postoperative period due to its inability to distinguish between infection and residual postoperative inflammatory changes. PET/CT was also found to be poor at diagnosing cases of native valve endocarditis. We conclude that PET/CT aids in the diagnosis of PVE when combined with the modified Duke Criteria on admission by increasing the diagnostic sensitivity. The diagnostic ability of PET/CT can be potentiated by the use of PET/CTA; however, its use may be unreliable in the early postoperative period or in native valve endocarditis. © The Author 2016. Published by Oxford University Press on behalf of the European Association for Cardio-Thoracic Surgery. All rights reserved.

"Tennis elbow". A challenging call for computation and medicine

NASA Astrophysics Data System (ADS)

Sfetsioris, D.; Bontioti, E. N.

2014-10-01

An attempt to give an insight on the features composing this musculotendinous disorder. We address the issues of definition, pathophysiology and the mechanism underlying the onset and the occurrence of the disease, diagnosis and diagnostic tools as well as the methods of treatment. We focus mostly on conservative treatment protocols and we recognize the need for a more thorough investigation with the aid of computation.

Computer-Aided Nodule Assessment and Risk Yield Risk Management of Adenocarcinoma: The Future of Imaging?

PubMed

Foley, Finbar; Rajagopalan, Srinivasan; Raghunath, Sushravya M; Boland, Jennifer M; Karwoski, Ronald A; Maldonado, Fabien; Bartholmai, Brian J; Peikert, Tobias

2016-01-01

Increased clinical use of chest high-resolution computed tomography results in increased identification of lung adenocarcinomas and persistent subsolid opacities. However, these lesions range from very indolent to extremely aggressive tumors. Clinically relevant diagnostic tools to noninvasively risk stratify and guide individualized management of these lesions are lacking. Research efforts investigating semiquantitative measures to decrease interrater and intrarater variability are emerging, and in some cases steps have been taken to automate this process. However, many such methods currently are still suboptimal, require validation and are not yet clinically applicable. The computer-aided nodule assessment and risk yield software application represents a validated tool for the automated, quantitative, and noninvasive tool for risk stratification of adenocarcinoma lung nodules. Computer-aided nodule assessment and risk yield correlates well with consensus histology and postsurgical patient outcomes, and therefore may help to guide individualized patient management, for example, in identification of nodules amenable to radiological surveillance, or in need of adjunctive therapy. Copyright © 2016 Elsevier Inc. All rights reserved.

[The Meaning of "Understanding the Brain": Peeking into the Brain of a Computational Neuroscientist].

PubMed

Tanaka, Hirokazu

2016-11-01

What does "understanding the brain" mean? Here, I review how computational neuroscience, a theoretical approach to the brain, can aid our understanding of the brain. First, I illustrate the study of reinforcement learning and dopamine neurons and argue its success in the light of Marr's three levels of computation. Second, I discuss how Marr's program has led to a computational understanding of the brain, and present computational models of the motor cortex and of a spiking neural network as illustrative examples.

Computer-aided diagnosis of alcoholism-related EEG signals.

PubMed

Acharya, U Rajendra; S, Vidya; Bhat, Shreya; Adeli, Hojjat; Adeli, Amir

2014-12-01

Alcoholism is a severe disorder that affects the functionality of neurons in the central nervous system (CNS) and alters the behavior of the affected person. Electroencephalogram (EEG) signals can be used as a diagnostic tool in the evaluation of subjects with alcoholism. The neurophysiological interpretation of EEG signals in persons with alcoholism (PWA) is based on observation and interpretation of the frequency and power in their EEGs compared to EEG signals from persons without alcoholism. This paper presents a review of the known features of EEGs obtained from PWA and proposes that the impact of alcoholism on the brain can be determined by computer-aided analysis of EEGs through extracting the minute variations in the EEG signals that can differentiate the EEGs of PWA from those of nonaffected persons. The authors advance the idea of automated computer-aided diagnosis (CAD) of alcoholism by employing the EEG signals. This is achieved through judicious combination of signal processing techniques such as wavelet, nonlinear dynamics, and chaos theory and pattern recognition and classification techniques. A CAD system is cost-effective and efficient and can be used as a decision support system by physicians in the diagnosis and treatment of alcoholism especially those who do not specialize in alcoholism or neurophysiology. It can also be of great value to rehabilitation centers to assess PWA over time and to monitor the impact of treatment aimed at minimizing or reversing the effects of the disease on the brain. A CAD system can be used to determine the extent of alcoholism-related changes in EEG signals (low, medium, high) and the effectiveness of therapeutic plans. Copyright © 2014 Elsevier Inc. All rights reserved.

An evaluation of consensus techniques for diagnostic interpretation

NASA Astrophysics Data System (ADS)

Sauter, Jake N.; LaBarre, Victoria M.; Furst, Jacob D.; Raicu, Daniela S.

2018-02-01

Learning diagnostic labels from image content has been the standard in computer-aided diagnosis. Most computer-aided diagnosis systems use low-level image features extracted directly from image content to train and test machine learning classifiers for diagnostic label prediction. When the ground truth for the diagnostic labels is not available, reference truth is generated from the experts diagnostic interpretations of the image/region of interest. More specifically, when the label is uncertain, e.g. when multiple experts label an image and their interpretations are different, techniques to handle the label variability are necessary. In this paper, we compare three consensus techniques that are typically used to encode the variability in the experts labeling of the medical data: mean, median and mode, and their effects on simple classifiers that can handle deterministic labels (decision trees) and probabilistic vectors of labels (belief decision trees). Given that the NIH/NCI Lung Image Database Consortium (LIDC) data provides interpretations for lung nodules by up to four radiologists, we leverage the LIDC data to evaluate and compare these consensus approaches when creating computer-aided diagnosis systems for lung nodules. First, low-level image features of nodules are extracted and paired with their radiologists semantic ratings (1= most likely benign, , 5 = most likely malignant); second, machine learning multi-class classifiers that handle deterministic labels (decision trees) and probabilistic vectors of labels (belief decision trees) are built to predict the lung nodules semantic ratings. We show that the mean-based consensus generates the most robust classi- fier overall when compared to the median- and mode-based consensus. Lastly, the results of this study show that, when building CAD systems with uncertain diagnostic interpretation, it is important to evaluate different strategies for encoding and predicting the diagnostic label.

Post-traumatic Stress Disorder Symptoms Among People Living with HIV/AIDS in Rural China.

PubMed

Luo, Sitong; Lin, Chunqing; Ji, Guoping; Li, Li

2017-11-01

Among people living with HIV/AIDS (PLHA), the occurrence of post-traumatic stress disorder (PTSD) symptoms associated with HIV diagnosis is a common problem. This study examined HIV diagnosis-related PTSD symptoms and its associated factors among PLHA in rural China. We used baseline data from a randomized controlled trial conducted in Anhui Province, China. Surveys of 522 PLHA were conducted via computer-assisted personal interview method. PTSD symptoms were measured based on re-experiencing, avoidance and arousal of the day of HIV diagnosis. Association between PTSD symptoms and demographic characteristics, physical and social functioning were assessed by multiple regression analysis and structural equation modeling. Social functioning exhibited a direct association with HIV diagnosis-related PTSD symptoms, and also mediated the association between PTSD symptoms and age, family income, and physical functioning. The study findings underscore the importance of developing interventions that alleviate PTSD symptoms and improve social functioning among PLHA in rural China.

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.

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.

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.

Broadening the Scope of Dental Education.

ERIC Educational Resources Information Center

Loe, Harald

1992-01-01

Scientific and technological advances affecting dental education in the near future are examined, including the growing role of saliva in diagnosis, direct imaging methods, biomaterials research, computer-aided design and manufacturing, molecular biology, and new restorative dentistry. It is argued that dentistry should be a fully recognized…

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.

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.

An integrated classifier for computer-aided diagnosis of colorectal polyps based on random forest and location index strategies

NASA Astrophysics Data System (ADS)

Hu, Yifan; Han, Hao; Zhu, Wei; Li, Lihong; Pickhardt, Perry J.; Liang, Zhengrong

2016-03-01

Feature classification plays an important role in differentiation or computer-aided diagnosis (CADx) of suspicious lesions. As a widely used ensemble learning algorithm for classification, random forest (RF) has a distinguished performance for CADx. Our recent study has shown that the location index (LI), which is derived from the well-known kNN (k nearest neighbor) and wkNN (weighted k nearest neighbor) classifier [1], has also a distinguished role in the classification for CADx. Therefore, in this paper, based on the property that the LI will achieve a very high accuracy, we design an algorithm to integrate the LI into RF for improved or higher value of AUC (area under the curve of receiver operating characteristics -- ROC). Experiments were performed by the use of a database of 153 lesions (polyps), including 116 neoplastic lesions and 37 hyperplastic lesions, with comparison to the existing classifiers of RF and wkNN, respectively. A noticeable gain by the proposed integrated classifier was quantified by the AUC measure.

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.

Integrating hinge axis approximation and the virtual facial simulation of prosthetic outcomes for treatment with CAD-CAM immediate dentures: A clinical report of a patient with microstomia.

PubMed

Kuric, Katelyn M; Harris, Bryan T; Morton, Dean; Azevedo, Bruno; Lin, Wei-Shao

2017-09-29

This clinical report describes a digital workflow using extraoral digital photographs and volumetric datasets from cone beam computed tomography (CBCT) imaging to create a 3-dimensional (3D), virtual patient with photorealistic appearance. In a patient with microstomia, hinge axis approximation, diagnostic casts simulating postextraction alveolar ridge profile, and facial simulation of prosthetic treatment outcome were completed in a 3D, virtual environment. The approach facilitated the diagnosis, communication, and patient acceptance of the treatment of maxillary and mandibular computer-aided design and computer-aided manufacturing (CAD-CAM) of immediate dentures at increased occlusal vertical dimension. Copyright © 2017 Editorial Council for the Journal of Prosthetic Dentistry. Published by Elsevier Inc. All rights reserved.

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.

Image Processing and Computer Aided Diagnosis in Computed Tomography of the Breast

DTIC Science & Technology

2007-03-01

TERMS breast imaging, breast CT, scatter compensation, denoising, CAD , Cone-beam CT 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF...clinical projection images. The CAD tool based on signal known exactly (SKE) scenario is under development. Task 6: Test and compare the...performances of the CAD developed in Task 5 applied to processed projection data from Task 1 with the CAD performance on the projection data without Bayesian

Computer-aided diagnosis of lung cancer: definition and detection of ground-glass opacity type of nodules by high-resolution computed tomography.

PubMed

Okada, Tohru; Iwano, Shingo; Ishigaki, Takeo; Kitasaka, Takayuki; Hirano, Yasushi; Mori, Kensaku; Suenaga, Yasuhito; Naganawa, Shinji

2009-02-01

The ground-glass opacity (GGO) of lung cancer is identified only subjectively on computed tomography (CT) images as no quantitative characteristic has been defined for GGOs. We sought to define GGOs quantitatively and to differentiate between GGOs and solid-type lung cancers semiautomatically with a computer-aided diagnosis (CAD). High-resolution CT images of 100 pulmonary nodules (all peripheral lung cancers) were collected from our clinical records. Two radiologists traced the contours of nodules and distinguished GGOs from solid areas. The CT attenuation value of each area was measured. Differentiation between cancer types was assessed by a receiver-operating characteristic (ROC) analysis. The mean CT attenuation of the GGO areas was -618.4 +/- 212.2 HU, whereas that of solid areas was -68.1 +/- 230.3 HU. CAD differentiated between solidand GGO-type lung cancers with a sensitivity of 86.0% and specificity of 96.5% when the threshold value was -370 HU. Four nodules of mixed GGOs were incorrectly classified as the solid type. CAD detected 96.3% of GGO areas when the threshold between GGO and solid areas was 194 HU. Objective definition of GGO area by CT attenuation is feasible. This method is useful for semiautomatic differentiation between GGOs and solid types of lung cancer.

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.

A computer-aided diagnostic system for kidney disease

PubMed Central

Jahantigh, Farzad Firouzi; Malmir, Behnam; Avilaq, Behzad Aslani

2017-01-01

Background Disease diagnosis is complicated since patients may demonstrate similar symptoms but physician may diagnose different diseases. There are a few number of investigations aimed to create a fuzzy expert system, as a computer aided system for disease diagnosis. Methods In this research, a cross-sectional descriptive study conducted in a kidney clinic in Tehran, Iran in 2012. Medical diagnosis fuzzy rules applied, and a set of symptoms related to the set of considered diseases defined. The input case to be diagnosed defined by assigning a fuzzy value to each symptom and then three physicians asked about each suspected diseases. Then comments of those three physicians summarized for each disease. The fuzzy inference applied to obtain a decision fuzzy set for each disease, and crisp decision values attained to determine the certainty of existence for each disease. Results Results indicated that, in the diagnosis of seven cases of kidney disease by examining 21 indicators using fuzzy expert system, kidney stone disease with 63% certainty was the most probable, renal tubular was at the lowest level with 15%, and other kidney diseases were at the other levels. The most remarkable finding of this study was that results of kidney disease diagnosis (e.g., kidney stone) via fuzzy expert system were fully compatible with those of kidney physicians. Conclusion The proposed fuzzy expert system is a valid, reliable, and flexible instrument to diagnose several typical input cases. The developed system decreases the effort of initial physical checking and manual feeding of input symptoms. PMID:28392995

A computer-aided diagnostic system for kidney disease.

PubMed

Jahantigh, Farzad Firouzi; Malmir, Behnam; Avilaq, Behzad Aslani

2017-03-01

Disease diagnosis is complicated since patients may demonstrate similar symptoms but physician may diagnose different diseases. There are a few number of investigations aimed to create a fuzzy expert system, as a computer aided system for disease diagnosis. In this research, a cross-sectional descriptive study conducted in a kidney clinic in Tehran, Iran in 2012. Medical diagnosis fuzzy rules applied, and a set of symptoms related to the set of considered diseases defined. The input case to be diagnosed defined by assigning a fuzzy value to each symptom and then three physicians asked about each suspected diseases. Then comments of those three physicians summarized for each disease. The fuzzy inference applied to obtain a decision fuzzy set for each disease, and crisp decision values attained to determine the certainty of existence for each disease. Results indicated that, in the diagnosis of seven cases of kidney disease by examining 21 indicators using fuzzy expert system, kidney stone disease with 63% certainty was the most probable, renal tubular was at the lowest level with 15%, and other kidney diseases were at the other levels. The most remarkable finding of this study was that results of kidney disease diagnosis (e.g., kidney stone) via fuzzy expert system were fully compatible with those of kidney physicians. The proposed fuzzy expert system is a valid, reliable, and flexible instrument to diagnose several typical input cases. The developed system decreases the effort of initial physical checking and manual feeding of input symptoms.

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

Performance evaluation using SYSTID time domain simulation. [computer-aid design and analysis for communication systems

NASA Technical Reports Server (NTRS)

Tranter, W. H.; Ziemer, R. E.; Fashano, M. J.

1975-01-01

This paper reviews the SYSTID technique for performance evaluation of communication systems using time-domain computer simulation. An example program illustrates the language. The inclusion of both Gaussian and impulse noise models make accurate simulation possible in a wide variety of environments. A very flexible postprocessor makes possible accurate and efficient performance evaluation.

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

Computer aided diagnosis system for Alzheimer disease using brain diffusion tensor imaging features selected by Pearson's correlation.

PubMed

Graña, M; Termenon, M; Savio, A; Gonzalez-Pinto, A; Echeveste, J; Pérez, J M; Besga, A

2011-09-20

The aim of this paper is to obtain discriminant features from two scalar measures of Diffusion Tensor Imaging (DTI) data, Fractional Anisotropy (FA) and Mean Diffusivity (MD), and to train and test classifiers able to discriminate Alzheimer's Disease (AD) patients from controls on the basis of features extracted from the FA or MD volumes. In this study, support vector machine (SVM) classifier was trained and tested on FA and MD data. Feature selection is done computing the Pearson's correlation between FA or MD values at voxel site across subjects and the indicative variable specifying the subject class. Voxel sites with high absolute correlation are selected for feature extraction. Results are obtained over an on-going study in Hospital de Santiago Apostol collecting anatomical T1-weighted MRI volumes and DTI data from healthy control subjects and AD patients. FA features and a linear SVM classifier achieve perfect accuracy, sensitivity and specificity in several cross-validation studies, supporting the usefulness of DTI-derived features as an image-marker for AD and to the feasibility of building Computer Aided Diagnosis systems for AD based on them. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Optical coherence tomography and computer-aided diagnosis of a murine model of chronic kidney disease

NASA Astrophysics Data System (ADS)

Wang, Bohan; Wang, Hsing-Wen; Guo, Hengchang; Anderson, Erik; Tang, Qinggong; Wu, Tongtong; Falola, Reuben; Smith, Tikina; Andrews, Peter M.; Chen, Yu

2017-12-01

Chronic kidney disease (CKD) is characterized by a progressive loss of renal function over time. Histopathological analysis of the condition of glomeruli and the proximal convolutional tubules over time can provide valuable insights into the progression of CKD. Optical coherence tomography (OCT) is a technology that can analyze the microscopic structures of a kidney in a nondestructive manner. Recently, we have shown that OCT can provide real-time imaging of kidney microstructures in vivo without administering exogenous contrast agents. A murine model of CKD induced by intravenous Adriamycin (ADR) injection is evaluated by OCT. OCT images of the rat kidneys have been captured every week up to eight weeks. Tubular diameter and hypertrophic tubule population of the kidneys at multiple time points after ADR injection have been evaluated through a fully automated computer-vision system. Results revealed that mean tubular diameter and hypertrophic tubule population increase with time in post-ADR injection period. The results suggest that OCT images of the kidney contain abundant information about kidney histopathology. Fully automated computer-aided diagnosis based on OCT has the potential for clinical evaluation of CKD conditions.

Selection of examples in case-based computer-aided decision systems

PubMed Central

Mazurowski, Maciej A.; Zurada, Jacek M.; Tourassi, Georgia D.

2013-01-01

Case-based computer-aided decision (CB-CAD) systems rely on a database of previously stored, known examples when classifying new, incoming queries. Such systems can be particularly useful since they do not need retraining every time a new example is deposited in the case base. The adaptive nature of case-based systems is well suited to the current trend of continuously expanding digital databases in the medical domain. To maintain efficiency, however, such systems need sophisticated strategies to effectively manage the available evidence database. In this paper, we discuss the general problem of building an evidence database by selecting the most useful examples to store while satisfying existing storage requirements. We evaluate three intelligent techniques for this purpose: genetic algorithm-based selection, greedy selection and random mutation hill climbing. These techniques are compared to a random selection strategy used as the baseline. The study is performed with a previously presented CB-CAD system applied for false positive reduction in screening mammograms. The experimental evaluation shows that when the development goal is to maximize the system’s diagnostic performance, the intelligent techniques are able to reduce the size of the evidence database to 37% of the original database by eliminating superfluous and/or detrimental examples while at the same time significantly improving the CAD system’s performance. Furthermore, if the case-base size is a main concern, the total number of examples stored in the system can be reduced to only 2–4% of the original database without a decrease in the diagnostic performance. Comparison of the techniques shows that random mutation hill climbing provides the best balance between the diagnostic performance and computational efficiency when building the evidence database of the CB-CAD system. PMID:18854606

CT-assisted agile manufacturing

NASA Astrophysics Data System (ADS)

Stanley, James H.; Yancey, Robert N.

1996-11-01

The next century will witness at least two great revolutions in the way goods are produced. First, workers will use the medium of virtual reality in all aspects of marketing, research, development, prototyping, manufacturing, sales and service. Second, market forces will drive manufacturing towards small-lot production and just-in-time delivery. Already, we can discern the merging of these megatrends into what some are calling agile manufacturing. Under this new paradigm, parts and processes will be designed and engineered within the mind of a computer, tooled and manufactured by the offspring of today's rapid prototyping equipment, and evaluated for performance and reliability by advanced nondestructive evaluation (NDE) techniques and sophisticated computational models. Computed tomography (CT) is the premier example of an NDE method suitable for future agile manufacturing activities. It is the only modality that provides convenient access to the full suite of engineering data that users will need to avail themselves of computer- aided design, computer-aided manufacturing, and computer- aided engineering capabilities, as well as newly emerging reverse engineering, rapid prototyping and solid freeform fabrication technologies. As such, CT is assured a central, utilitarian role in future industrial operations. An overview of this exciting future for industrial CT is presented.

Evaluation of a New Ensemble Learning Framework for Mass Classification in Mammograms.

PubMed

Rahmani Seryasat, Omid; Haddadnia, Javad

2018-06-01

Mammography is the most common screening method for diagnosis of breast cancer. In this study, a computer-aided system for diagnosis of benignity and malignity of the masses was implemented in mammogram images. In the computer aided diagnosis system, we first reduce the noise in the mammograms using an effective noise removal technique. After the noise removal, the mass in the region of interest must be segmented and this segmentation is done using a deformable model. After the mass segmentation, a number of features are extracted from it. These features include: features of the mass shape and border, tissue properties, and the fractal dimension. After extracting a large number of features, a proper subset must be chosen from among them. In this study, we make use of a new method on the basis of a genetic algorithm for selection of a proper set of features. After determining the proper features, a classifier is trained. To classify the samples, a new architecture for combination of the classifiers is proposed. In this architecture, easy and difficult samples are identified and trained using different classifiers. Finally, the proposed mass diagnosis system was also tested on mini-Mammographic Image Analysis Society and digital database for screening mammography databases. The obtained results indicate that the proposed system can compete with the state-of-the-art methods in terms of accuracy. Copyright © 2017 Elsevier Inc. All rights reserved.

Design of Computer-aided Instruction for Radiology Interpretation: The Role of Cognitive Task Analysis

PubMed Central

Pusic, Martin V.; LeBlanc, Vicki; Patel, Vimla L.

2001-01-01

Traditional task analysis for instructional design has emphasized the importance of precisely defining behavioral educational objectives and working back to select objective-appropriate instructional strategies. However, this approach may miss effective strategies. Cognitive task analysis, on the other hand, breaks a process down into its component knowledge representations. Selection of instructional strategies based on all such representations in a domain is likely to lead to optimal instructional design. In this demonstration, using the interpretation of cervical spine x-rays as an educational example, we show how a detailed cognitive task analysis can guide the development of computer-aided instruction.

Application programs written by using customizing tools of a computer-aided design system

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

Li, X.; Huang, R.; Juricic, D.

1995-12-31

Customizing tools of Computer-Aided Design Systems have been developed to such a degree as to become equivalent to powerful higher-level programming languages that are especially suitable for graphics applications. Two examples of application programs written by using AutoCAD`s customizing tools are given in some detail to illustrate their power. One tool uses AutoLISP list-processing language to develop an application program that produces four views of a given solid model. The other uses AutoCAD Developmental System, based on program modules written in C, to produce an application program that renders a freehand sketch from a given CAD drawing.

SPREADSHEET BASED SCALING CALCULATIONS AND MEMBRANE PERFORMANCE

EPA Science Inventory

Many membrane element manufacturers provide a computer program to aid buyers in the use of their elements. However, to date there are few examples of fully integrated public domain software available for calculating reverse osmosis and nanofiltration system performance. The Total...

Fault diagnosis model for power transformers based on information fusion

NASA Astrophysics Data System (ADS)

Dong, Ming; Yan, Zhang; Yang, Li; Judd, Martin D.

2005-07-01

Methods used to assess the insulation status of power transformers before they deteriorate to a critical state include dissolved gas analysis (DGA), partial discharge (PD) detection and transfer function techniques, etc. All of these approaches require experience in order to correctly interpret the observations. Artificial intelligence (AI) is increasingly used to improve interpretation of the individual datasets. However, a satisfactory diagnosis may not be obtained if only one technique is used. For example, the exact location of PD cannot be predicted if only DGA is performed. However, using diverse methods may result in different diagnosis solutions, a problem that is addressed in this paper through the introduction of a fuzzy information infusion model. An inference scheme is proposed that yields consistent conclusions and manages the inherent uncertainty in the various methods. With the aid of information fusion, a framework is established that allows different diagnostic tools to be combined in a systematic way. The application of information fusion technique for insulation diagnostics of transformers is proved promising by means of examples.

Software Infrastructure for Computer-aided Drug Discovery and Development, a Practical Example with Guidelines.

PubMed

Moretti, Loris; Sartori, Luca

2016-09-01

In the field of Computer-Aided Drug Discovery and Development (CADDD) the proper software infrastructure is essential for everyday investigations. The creation of such an environment should be carefully planned and implemented with certain features in order to be productive and efficient. Here we describe a solution to integrate standard computational services into a functional unit that empowers modelling applications for drug discovery. This system allows users with various level of expertise to run in silico experiments automatically and without the burden of file formatting for different software, managing the actual computation, keeping track of the activities and graphical rendering of the structural outcomes. To showcase the potential of this approach, performances of five different docking programs on an Hiv-1 protease test set are presented. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Breast Ultrasound: Computer-Aided Diagnosis Approach to Improving Specificity and Decreasing Observer Variability

DTIC Science & Technology

1998-01-01

the conduct of research involving hazardous organisms, the investigator(s) adhered to the CDC-NIH Guide for Biosafetv in Microbiological and...Misinterpretation and misuse of the kappa statistic. American Journal of Epidemiology, 1987. 126: p. 161-169. 23. Soeken. K.L. and P.A. Prescott

Health Insurance Portability and Accountability Act-Compliant Ocular Telehealth Network for the Remote Diagnosis and Management of Diabetic Retinopathy

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

Li, Yaquin; Karnowski, Thomas Paul; Tobin Jr, Kenneth William

2011-01-01

In this article, we present the design and implementation of a regional ocular telehealth network for remote assessment and management of diabetic retinopathy (DR), including the design requirements, network topology, protocol design, system work flow, graphics user interfaces, and performance evaluation. The Telemedical Retinal Image Analysis and Diagnosis Network is a computer-aided, image analysis telehealth paradigm for the diagnosis of DR and other retinal diseases using fundus images acquired from primary care end users delivering care to underserved patient populations in the mid-South and southeastern United States.

A health insurance portability and accountability act-compliant ocular telehealth network for the remote diagnosis and management of diabetic retinopathy.

PubMed

Li, Yaqin; Karnowski, Thomas P; Tobin, Kenneth W; Giancardo, Luca; Morris, Scott; Sparrow, Sylvia E; Garg, Seema; Fox, Karen; Chaum, Edward

2011-10-01

In this article, we present the design and implementation of a regional ocular telehealth network for remote assessment and management of diabetic retinopathy (DR), including the design requirements, network topology, protocol design, system work flow, graphics user interfaces, and performance evaluation. The Telemedical Retinal Image Analysis and Diagnosis Network is a computer-aided, image analysis telehealth paradigm for the diagnosis of DR and other retinal diseases using fundus images acquired from primary care end users delivering care to underserved patient populations in the mid-South and southeastern United States.

Can computed crystal energy landscapes help understand pharmaceutical solids?

PubMed Central

Price, Sarah L.; Braun, Doris E.; Reutzel-Edens, Susan M.

2017-01-01

Computational crystal structure prediction (CSP) methods can now be applied to the smaller pharmaceutical molecules currently in drug development. We review the recent uses of computed crystal energy landscapes for pharmaceuticals, concentrating on examples where they have been used in collaboration with industrial-style experimental solid form screening. There is a strong complementarity in aiding experiment to find and characterise practically important solid forms and understanding the nature of the solid form landscape. PMID:27067116

Computer-Aided Recognition of Facial Attributes for Fetal Alcohol Spectrum Disorders.

PubMed

Valentine, Matthew; Bihm, Dustin C J; Wolf, Lior; Hoyme, H Eugene; May, Philip A; Buckley, David; Kalberg, Wendy; Abdul-Rahman, Omar A

2017-12-01

To compare the detection of facial attributes by computer-based facial recognition software of 2-D images against standard, manual examination in fetal alcohol spectrum disorders (FASD). Participants were gathered from the Fetal Alcohol Syndrome Epidemiology Research database. Standard frontal and oblique photographs of children were obtained during a manual, in-person dysmorphology assessment. Images were submitted for facial analysis conducted by the facial dysmorphology novel analysis technology (an automated system), which assesses ratios of measurements between various facial landmarks to determine the presence of dysmorphic features. Manual blinded dysmorphology assessments were compared with those obtained via the computer-aided system. Areas under the curve values for individual receiver-operating characteristic curves revealed the computer-aided system (0.88 ± 0.02) to be comparable to the manual method (0.86 ± 0.03) in detecting patients with FASD. Interestingly, cases of alcohol-related neurodevelopmental disorder (ARND) were identified more efficiently by the computer-aided system (0.84 ± 0.07) in comparison to the manual method (0.74 ± 0.04). A facial gestalt analysis of patients with ARND also identified more generalized facial findings compared to the cardinal facial features seen in more severe forms of FASD. We found there was an increased diagnostic accuracy for ARND via our computer-aided method. As this category has been historically difficult to diagnose, we believe our experiment demonstrates that facial dysmorphology novel analysis technology can potentially improve ARND diagnosis by introducing a standardized metric for recognizing FASD-associated facial anomalies. Earlier recognition of these patients will lead to earlier intervention with improved patient outcomes. Copyright © 2017 by the American Academy of Pediatrics.

Index of Selected Publications Through December 1983,

DTIC Science & Technology

1984-03-01

substantiating methodology , and is designed mainly for * readers with a professional interest in the subject but do * not have a primary responsibility in that...Navy in postwar American security policy -- computer subroutines - CRC 20 H 1052 experimental design techniques, computer North Atlantic-Norwegian...statistical tion and Congestion, With an Example from Southern experimental design technique aids the analysis California, 27 pp., Jan 1971, AD 719 906 of

Intelligent Computer-Aided Instruction and Musical Performance Skills. CITE Report No. 18.

ERIC Educational Resources Information Center

Baker, Michael

This paper is a transcription from memory of a short talk that used overhead projector slides, with musical examples played on an Apple Macintosh computer and a Yamaha CX5 synthesizer. The slides appear in the text as reduced "icons" at the point where they would have been used in the talk. The paper concerns ways in which artificial intelligence…

Computer Aided Teaching of Digital Signal Processing.

ERIC Educational Resources Information Center

Castro, Ian P.

1990-01-01

Describes a microcomputer-based software package developed at the University of Surrey for teaching digital signal processing to undergraduate science and engineering students. Menu-driven software capabilities are explained, including demonstration of qualitative concepts and experimentation with quantitative data, and examples are given of…

Informatics approaches in the Biological Characterization of Adverse Outcome Pathways

EPA Science Inventory

Adverse Outcome Pathways (AOPs) are a conceptual framework to characterize toxicity pathways by a series of mechanistic steps from a molecular initiating event to population outcomes. This framework helps to direct risk assessment research, for example by aiding in computational ...

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.

Computational Psychiatry

PubMed Central

Wang, Xiao-Jing; Krystal, John H.

2014-01-01

Psychiatric disorders such as autism and schizophrenia arise from abnormalities in brain systems that underlie cognitive, emotional and social functions. The brain is enormously complex and its abundant feedback loops on multiple scales preclude intuitive explication of circuit functions. In close interplay with experiments, theory and computational modeling are essential for understanding how, precisely, neural circuits generate flexible behaviors and their impairments give rise to psychiatric symptoms. This Perspective highlights recent progress in applying computational neuroscience to the study of mental disorders. We outline basic approaches, including identification of core deficits that cut across disease categories, biologically-realistic modeling bridging cellular and synaptic mechanisms with behavior, model-aided diagnosis. The need for new research strategies in psychiatry is urgent. Computational psychiatry potentially provides powerful tools for elucidating pathophysiology that may inform both diagnosis and treatment. To achieve this promise will require investment in cross-disciplinary training and research in this nascent field. PMID:25442941

A new method to acquire 3-D images of a dental cast

NASA Astrophysics Data System (ADS)

Li, Zhongke; Yi, Yaxing; Zhu, Zhen; Li, Hua; Qin, Yongyuan

2006-01-01

This paper introduced our newly developed method to acquire three-dimensional images of a dental cast. A rotatable table, a laser-knife, a mirror, a CCD camera and a personal computer made up of a three-dimensional data acquiring system. A dental cast is placed on the table; the mirror is installed beside the table; a linear laser is projected to the dental cast; the CCD camera is put up above the dental cast, it can take picture of the dental cast and the shadow in the mirror; while the table rotating, the camera records the shape of the laser streak projected on the dental cast, and transmit the data to the computer. After the table rotated one circuit, the computer processes the data, calculates the three-dimensional coordinates of the dental cast's surface. In data processing procedure, artificial neural networks are enrolled to calibrate the lens distortion, map coordinates form screen coordinate system to world coordinate system. According to the three-dimensional coordinates, the computer reconstructs the stereo image of the dental cast. It is essential for computer-aided diagnosis and treatment planning in orthodontics. In comparison with other systems in service, for example, laser beam three-dimensional scanning system, the characteristic of this three-dimensional data acquiring system: a. celerity, it casts only 1 minute to scan a dental cast; b. compact, the machinery is simple and compact; c. no blind zone, a mirror is introduced ably to reduce blind zone.

Computing elastic anisotropy to discover gum-metal-like structural alloys

NASA Astrophysics Data System (ADS)

Winter, I. S.; de Jong, M.; Asta, M.; Chrzan, D. C.

2017-08-01

The computer aided discovery of structural alloys is a burgeoning but still challenging area of research. A primary challenge in the field is to identify computable screening parameters that embody key structural alloy properties. Here, an elastic anisotropy parameter that captures a material's susceptibility to solute solution strengthening is identified. The parameter has many applications in the discovery and optimization of structural materials. As a first example, the parameter is used to identify alloys that might display the super elasticity, super strength, and high ductility of the class of TiNb alloys known as gum metals. In addition, it is noted that the parameter can be used to screen candidate alloys for shape memory response, and potentially aid in the optimization of the mechanical properties of high-entropy alloys.

Computer-Aided Diagnosis with Deep Learning Architecture: Applications to Breast Lesions in US Images and Pulmonary Nodules in CT Scans

NASA Astrophysics Data System (ADS)

Cheng, Jie-Zhi; Ni, Dong; Chou, Yi-Hong; Qin, Jing; Tiu, Chui-Mei; Chang, Yeun-Chung; Huang, Chiun-Sheng; Shen, Dinggang; Chen, Chung-Ming

2016-04-01

This paper performs a comprehensive study on the deep-learning-based computer-aided diagnosis (CADx) for the differential diagnosis of benign and malignant nodules/lesions by avoiding the potential errors caused by inaccurate image processing results (e.g., boundary segmentation), as well as the classification bias resulting from a less robust feature set, as involved in most conventional CADx algorithms. Specifically, the stacked denoising auto-encoder (SDAE) is exploited on the two CADx applications for the differentiation of breast ultrasound lesions and lung CT nodules. The SDAE architecture is well equipped with the automatic feature exploration mechanism and noise tolerance advantage, and hence may be suitable to deal with the intrinsically noisy property of medical image data from various imaging modalities. To show the outperformance of SDAE-based CADx over the conventional scheme, two latest conventional CADx algorithms are implemented for comparison. 10 times of 10-fold cross-validations are conducted to illustrate the efficacy of the SDAE-based CADx algorithm. The experimental results show the significant performance boost by the SDAE-based CADx algorithm over the two conventional methods, suggesting that deep learning techniques can potentially change the design paradigm of the CADx systems without the need of explicit design and selection of problem-oriented features.

Computer-Aided Diagnosis with Deep Learning Architecture: Applications to Breast Lesions in US Images and Pulmonary Nodules in CT Scans.

PubMed

Cheng, Jie-Zhi; Ni, Dong; Chou, Yi-Hong; Qin, Jing; Tiu, Chui-Mei; Chang, Yeun-Chung; Huang, Chiun-Sheng; Shen, Dinggang; Chen, Chung-Ming

2016-04-15

This paper performs a comprehensive study on the deep-learning-based computer-aided diagnosis (CADx) for the differential diagnosis of benign and malignant nodules/lesions by avoiding the potential errors caused by inaccurate image processing results (e.g., boundary segmentation), as well as the classification bias resulting from a less robust feature set, as involved in most conventional CADx algorithms. Specifically, the stacked denoising auto-encoder (SDAE) is exploited on the two CADx applications for the differentiation of breast ultrasound lesions and lung CT nodules. The SDAE architecture is well equipped with the automatic feature exploration mechanism and noise tolerance advantage, and hence may be suitable to deal with the intrinsically noisy property of medical image data from various imaging modalities. To show the outperformance of SDAE-based CADx over the conventional scheme, two latest conventional CADx algorithms are implemented for comparison. 10 times of 10-fold cross-validations are conducted to illustrate the efficacy of the SDAE-based CADx algorithm. The experimental results show the significant performance boost by the SDAE-based CADx algorithm over the two conventional methods, suggesting that deep learning techniques can potentially change the design paradigm of the CADx systems without the need of explicit design and selection of problem-oriented features.

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.

Deep Learning Role in Early Diagnosis of Prostate Cancer

PubMed Central

Reda, Islam; Khalil, Ashraf; Elmogy, Mohammed; Abou El-Fetouh, Ahmed; Shalaby, Ahmed; Abou El-Ghar, Mohamed; Elmaghraby, Adel; Ghazal, Mohammed; El-Baz, Ayman

2018-01-01

The objective of this work is to develop a computer-aided diagnostic system for early diagnosis of prostate cancer. The presented system integrates both clinical biomarkers (prostate-specific antigen) and extracted features from diffusion-weighted magnetic resonance imaging collected at multiple b values. The presented system performs 3 major processing steps. First, prostate delineation using a hybrid approach that combines a level-set model with nonnegative matrix factorization. Second, estimation and normalization of diffusion parameters, which are the apparent diffusion coefficients of the delineated prostate volumes at different b values followed by refinement of those apparent diffusion coefficients using a generalized Gaussian Markov random field model. Then, construction of the cumulative distribution functions of the processed apparent diffusion coefficients at multiple b values. In parallel, a K-nearest neighbor classifier is employed to transform the prostate-specific antigen results into diagnostic probabilities. Finally, those prostate-specific antigen–based probabilities are integrated with the initial diagnostic probabilities obtained using stacked nonnegativity constraint sparse autoencoders that employ apparent diffusion coefficient–cumulative distribution functions for better diagnostic accuracy. Experiments conducted on 18 diffusion-weighted magnetic resonance imaging data sets achieved 94.4% diagnosis accuracy (sensitivity = 88.9% and specificity = 100%), which indicate the promising results of the presented computer-aided diagnostic system. PMID:29804518

Call for a Computer-Aided Cancer Detection and Classification Research Initiative in Oman.

PubMed

Mirzal, Andri; Chaudhry, Shafique Ahmad

2016-01-01

Cancer is a major health problem in Oman. It is reported that cancer incidence in Oman is the second highest after Saudi Arabia among Gulf Cooperation Council countries. Based on GLOBOCAN estimates, Oman is predicted to face an almost two-fold increase in cancer incidence in the period 2008-2020. However, cancer research in Oman is still in its infancy. This is due to the fact that medical institutions and infrastructure that play central roles in data collection and analysis are relatively new developments in Oman. We believe the country requires an organized plan and efforts to promote local cancer research. In this paper, we discuss current research progress in cancer diagnosis using machine learning techniques to optimize computer aided cancer detection and classification (CAD). We specifically discuss CAD using two major medical data, i.e., medical imaging and microarray gene expression profiling, because medical imaging like mammography, MRI, and PET have been widely used in Oman for assisting radiologists in early cancer diagnosis and microarray data have been proven to be a reliable source for differential diagnosis. We also discuss future cancer research directions and benefits to Oman economy for entering the cancer research and treatment business as it is a multi-billion dollar industry worldwide.

Computer-Aided Diagnosis with Deep Learning Architecture: Applications to Breast Lesions in US Images and Pulmonary Nodules in CT Scans

PubMed Central

Cheng, Jie-Zhi; Ni, Dong; Chou, Yi-Hong; Qin, Jing; Tiu, Chui-Mei; Chang, Yeun-Chung; Huang, Chiun-Sheng; Shen, Dinggang; Chen, Chung-Ming

2016-01-01

This paper performs a comprehensive study on the deep-learning-based computer-aided diagnosis (CADx) for the differential diagnosis of benign and malignant nodules/lesions by avoiding the potential errors caused by inaccurate image processing results (e.g., boundary segmentation), as well as the classification bias resulting from a less robust feature set, as involved in most conventional CADx algorithms. Specifically, the stacked denoising auto-encoder (SDAE) is exploited on the two CADx applications for the differentiation of breast ultrasound lesions and lung CT nodules. The SDAE architecture is well equipped with the automatic feature exploration mechanism and noise tolerance advantage, and hence may be suitable to deal with the intrinsically noisy property of medical image data from various imaging modalities. To show the outperformance of SDAE-based CADx over the conventional scheme, two latest conventional CADx algorithms are implemented for comparison. 10 times of 10-fold cross-validations are conducted to illustrate the efficacy of the SDAE-based CADx algorithm. The experimental results show the significant performance boost by the SDAE-based CADx algorithm over the two conventional methods, suggesting that deep learning techniques can potentially change the design paradigm of the CADx systems without the need of explicit design and selection of problem-oriented features. PMID:27079888

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 classification of breast masses using contrast-enhanced digital mammograms

NASA Astrophysics Data System (ADS)

Danala, Gopichandh; Aghaei, Faranak; Heidari, Morteza; Wu, Teresa; Patel, Bhavika; Zheng, Bin

2018-02-01

By taking advantages of both mammography and breast MRI, contrast-enhanced digital mammography (CEDM) has emerged as a new promising imaging modality to improve efficacy of breast cancer screening and diagnosis. The primary objective of study is to develop and evaluate a new computer-aided detection and diagnosis (CAD) scheme of CEDM images to classify between malignant and benign breast masses. A CEDM dataset consisting of 111 patients (33 benign and 78 malignant) was retrospectively assembled. Each case includes two types of images namely, low-energy (LE) and dual-energy subtracted (DES) images. First, CAD scheme applied a hybrid segmentation method to automatically segment masses depicting on LE and DES images separately. Optimal segmentation results from DES images were also mapped to LE images and vice versa. Next, a set of 109 quantitative image features related to mass shape and density heterogeneity was initially computed. Last, four multilayer perceptron-based machine learning classifiers integrated with correlationbased feature subset evaluator and leave-one-case-out cross-validation method was built to classify mass regions depicting on LE and DES images, respectively. Initially, when CAD scheme was applied to original segmentation of DES and LE images, the areas under ROC curves were 0.7585+/-0.0526 and 0.7534+/-0.0470, respectively. After optimal segmentation mapping from DES to LE images, AUC value of CAD scheme significantly increased to 0.8477+/-0.0376 (p<0.01). Since DES images eliminate overlapping effect of dense breast tissue on lesions, segmentation accuracy was significantly improved as compared to regular mammograms, the study demonstrated that computer-aided classification of breast masses using CEDM images yielded higher performance.

Computer aided exercise electrocardiographic testing and coronary arteriography in patients with angina pectoris and with myocardial infarction.

PubMed Central

Angelhed, J E; Bjurö, T I; Ejdebäck, J; Selin, K; Schlossman, D; Griffith, L S; Bergstrand, R; Vedin, A; Wilhelmsson, C

1984-01-01

A set of electrocardiographic criteria for the diagnosis of coronary artery disease was evaluated in two different groups of patients examined by computer aided 12 lead exercise electrocardiographic stress testing and coronary arteriography. One group consisted of patients with severe angina pectoris and the other of patients who had suffered a myocardial infarction three years before the study. Angiographically determined categories of patients could be identified with satisfactory precision by the electrocardiographic criteria under test in the patients with angina pectoris but not in those with infarction. A new method of classifying patients on the basis of data from coronary arteriography improved the correlation with ST segment analysis compared with conventional classification. PMID:6743432

Computer-aided diagnosis of colorectal polyp histology by using a real-time image recognition system and narrow-band imaging magnifying colonoscopy.

PubMed

Kominami, Yoko; Yoshida, Shigeto; Tanaka, Shinji; Sanomura, Yoji; Hirakawa, Tsubasa; Raytchev, Bisser; Tamaki, Toru; Koide, Tetsusi; Kaneda, Kazufumi; Chayama, Kazuaki

2016-03-01

It is necessary to establish cost-effective examinations and treatments for diminutive colorectal tumors that consider the treatment risk and surveillance interval after treatment. The Preservation and Incorporation of Valuable Endoscopic Innovations (PIVI) committee of the American Society for Gastrointestinal Endoscopy published a statement recommending the establishment of endoscopic techniques that practice the resect and discard strategy. The aims of this study were to evaluate whether our newly developed real-time image recognition system can predict histologic diagnoses of colorectal lesions depicted on narrow-band imaging and to satisfy some problems with the PIVI recommendations. We enrolled 41 patients who had undergone endoscopic resection of 118 colorectal lesions (45 nonneoplastic lesions and 73 neoplastic lesions). We compared the results of real-time image recognition system analysis with that of narrow-band imaging diagnosis and evaluated the correlation between image analysis and the pathological results. Concordance between the endoscopic diagnosis and diagnosis by a real-time image recognition system with a support vector machine output value was 97.5% (115/118). Accuracy between the histologic findings of diminutive colorectal lesions (polyps) and diagnosis by a real-time image recognition system with a support vector machine output value was 93.2% (sensitivity, 93.0%; specificity, 93.3%; positive predictive value (PPV), 93.0%; and negative predictive value, 93.3%). Although further investigation is necessary to establish our computer-aided diagnosis system, this real-time image recognition system may satisfy the PIVI recommendations and be useful for predicting the histology of colorectal tumors. Copyright © 2016 American Society for Gastrointestinal Endoscopy. Published by Elsevier Inc. All rights reserved.

A Computer-Aided Diagnosis System Using Artificial Intelligence for the Diagnosis and Characterization of Thyroid Nodules on Ultrasound: Initial Clinical Assessment.

PubMed

Choi, Young Jun; Baek, Jung Hwan; Park, Hye Sun; Shim, Woo Hyun; Kim, Tae Yong; Shong, Young Kee; Lee, Jeong Hyun

2017-04-01

An initial clinical assessment is described of a new, commercially available, computer-aided diagnosis (CAD) system using artificial intelligence (AI) for thyroid ultrasound, and its performance is evaluated in the diagnosis of malignant thyroid nodules and categorization of nodule characteristics. Patients with thyroid nodules with decisive diagnosis, whether benign or malignant, were consecutively enrolled from November 2015 to February 2016. An experienced radiologist reviewed the ultrasound image characteristics of the thyroid nodules, while another radiologist assessed the same thyroid nodules using the CAD system, providing ultrasound characteristics and a diagnosis of whether nodules were benign or malignant. The diagnostic performance and agreement of US characteristics between the experienced radiologist and the CAD system were compared. In total, 102 thyroid nodules from 89 patients were included; 59 (57.8%) were benign and 43 (42.2%) were malignant. The CAD system showed a similar sensitivity as the experienced radiologist (90.7% vs. 88.4%, p > 0.99), but a lower specificity and a lower area under the receiver operating characteristic (AUROC) curve (specificity: 74.6% vs. 94.9%, p = 0.002; AUROC: 0.83 vs. 0.92, p = 0.021). Classifications of the ultrasound characteristics (composition, orientation, echogenicity, and spongiform) between radiologist and CAD system were in substantial agreement (κ = 0.659, 0.740, 0.733, and 0.658, respectively), while the margin showed a fair agreement (κ = 0.239). The sensitivity of the CAD system using AI for malignant thyroid nodules was as good as that of the experienced radiologist, while specificity and accuracy were lower than those of the experienced radiologist. The CAD system showed an acceptable agreement with the experienced radiologist for characterization of thyroid nodules.

Effectiveness of computer-aided diagnosis of colorectal lesions using novel software for magnifying narrow-band imaging: a pilot study.

PubMed

Tamai, Naoto; Saito, Yutaka; Sakamoto, Taku; Nakajima, Takeshi; Matsuda, Takahisa; Sumiyama, Kazuki; Tajiri, Hisao; Koyama, Ryosuke; Kido, Shoji

2017-08-01

 Magnifying narrow-band imaging (M-NBI) enables detailed observation of microvascular architecture and can be used in endoscopic diagnosis of colorectal lesion. However, in clinical practice, differential diagnosis and estimation of invasion depth of colorectal lesions based on M-NBI findings require experience. Therefore, developing computer-aided diagnosis (CAD) for M-NBI would be beneficial for clinical practice. The aim of this study was to evaluate the effectiveness of software for CAD of colorectal lesions. In collaboration with Yamaguchi University, we developed novel software that enables CAD of colorectal lesions using M-NBI images. This software for CAD further specifically divides original Sano's colorectal M-NBI classification into 3 groups (group A, capillary pattern [CP] type I; group B, CP type II + CP type IIIA; group C, CP type IIIB), which describe hyperplastic polyps (HPs), adenoma/adenocarcinoma (intramucosal [IM] to submucosal [SM]-superficial) lesions, and SM-deep lesions, respectively. We retrospectively reviewed 121 lesions evaluated using M-NBI. The 121 reviewed lesions included 21 HP, 80 adenoma/adenocarcinoma (IM to SM-superficial), and 20 SM-deep lesions. The concordance rate between the CAD and the diagnosis of the experienced endoscopists was 90.9 %. The sensitivity, specificity, positive and negative predictive values, and accuracy of the CAD for neoplastic lesions were 83.9 %, 82.6 %, 53.1 %, 95.6 %, and 82.8 %, respectively. The values for SM-deep lesions were 83.9 %, 82.6 %, 53.1 %, 95.6 %, and 82.8 %, respectively.  Relatively high diagnostic values were obtained using CAD. This software for CAD could possibly lead to a wider use of M-NBI in the endoscopic diagnosis of colorectal lesions.

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

PubMed Central

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

2016-01-01

One in six men will develop prostate cancer in his life time. 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 multi-parametric 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 MR spectroscopy imaging. Due to 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. In order 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. PMID:27133005

Giga-voxel computational morphogenesis for structural design

NASA Astrophysics Data System (ADS)

Aage, Niels; Andreassen, Erik; Lazarov, Boyan S.; Sigmund, Ole

2017-10-01

In the design of industrial products ranging from hearing aids to automobiles and aeroplanes, material is distributed so as to maximize the performance and minimize the cost. Historically, human intuition and insight have driven the evolution of mechanical design, recently assisted by computer-aided design approaches. The computer-aided approach known as topology optimization enables unrestricted design freedom and shows great promise with regard to weight savings, but its applicability has so far been limited to the design of single components or simple structures, owing to the resolution limits of current optimization methods. Here we report a computational morphogenesis tool, implemented on a supercomputer, that produces designs with giga-voxel resolution—more than two orders of magnitude higher than previously reported. Such resolution provides insights into the optimal distribution of material within a structure that were hitherto unachievable owing to the challenges of scaling up existing modelling and optimization frameworks. As an example, we apply the tool to the design of the internal structure of a full-scale aeroplane wing. The optimized full-wing design has unprecedented structural detail at length scales ranging from tens of metres to millimetres and, intriguingly, shows remarkable similarity to naturally occurring bone structures in, for example, bird beaks. We estimate that our optimized design corresponds to a reduction in mass of 2-5 per cent compared to currently used aeroplane wing designs, which translates into a reduction in fuel consumption of about 40-200 tonnes per year per aeroplane. Our morphogenesis process is generally applicable, not only to mechanical design, but also to flow systems, antennas, nano-optics and micro-systems.

Giga-voxel computational morphogenesis for structural design.

PubMed

Aage, Niels; Andreassen, Erik; Lazarov, Boyan S; Sigmund, Ole

2017-10-04

In the design of industrial products ranging from hearing aids to automobiles and aeroplanes, material is distributed so as to maximize the performance and minimize the cost. Historically, human intuition and insight have driven the evolution of mechanical design, recently assisted by computer-aided design approaches. The computer-aided approach known as topology optimization enables unrestricted design freedom and shows great promise with regard to weight savings, but its applicability has so far been limited to the design of single components or simple structures, owing to the resolution limits of current optimization methods. Here we report a computational morphogenesis tool, implemented on a supercomputer, that produces designs with giga-voxel resolution-more than two orders of magnitude higher than previously reported. Such resolution provides insights into the optimal distribution of material within a structure that were hitherto unachievable owing to the challenges of scaling up existing modelling and optimization frameworks. As an example, we apply the tool to the design of the internal structure of a full-scale aeroplane wing. The optimized full-wing design has unprecedented structural detail at length scales ranging from tens of metres to millimetres and, intriguingly, shows remarkable similarity to naturally occurring bone structures in, for example, bird beaks. We estimate that our optimized design corresponds to a reduction in mass of 2-5 per cent compared to currently used aeroplane wing designs, which translates into a reduction in fuel consumption of about 40-200 tonnes per year per aeroplane. Our morphogenesis process is generally applicable, not only to mechanical design, but also to flow systems, antennas, nano-optics and micro-systems.

Applying Learning Diagnosis Diagram in Computer Aided Instructions: Research, Practice and Evaluation

ERIC Educational Resources Information Center

Wu, YuLung

2010-01-01

In Taiwan, when students learn in experiment-related courses, they are often grouped into several teams. The familiar method of grouping learning is "Cooperative Learning". A well-organized grouping strategy improves cooperative learning and increases the number of activities. This study proposes a novel pedagogical method by adopting…

Incorporating Computer-Aided Language Sample Analysis into Clinical Practice

ERIC Educational Resources Information Center

Price, Lisa Hammett; Hendricks, Sean; Cook, Colleen

2010-01-01

Purpose: During the evaluation of language abilities, the needs of the child are best served when multiple types and sources of data are included in the evaluation process. Current educational policies and practice guidelines further dictate the use of authentic assessment data to inform diagnosis and treatment planning. Language sampling and…

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 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

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.

Bilateral symmetry aspects in computer-aided Alzheimer's disease diagnosis by single-photon emission-computed tomography imaging.

PubMed

Illán, Ignacio Alvarez; Górriz, Juan Manuel; Ramírez, Javier; Lang, Elmar W; Salas-Gonzalez, Diego; Puntonet, Carlos G

2012-11-01

This paper explores the importance of the latent symmetry of the brain in computer-aided systems for diagnosing Alzheimer's disease (AD). Symmetry and asymmetry are studied from two points of view: (i) the development of an effective classifier within the scope of machine learning techniques, and (ii) the assessment of its relevance to the AD diagnosis in the early stages of the disease. The proposed methodology is based on eigenimage decomposition of single-photon emission-computed tomography images, using an eigenspace extension to accommodate odd and even eigenvectors separately. This feature extraction technique allows for support-vector-machine classification and image analysis. Identification of AD patterns is improved when the latent symmetry of the brain is considered, with an estimated 92.78% accuracy (92.86% sensitivity, 92.68% specificity) using a linear kernel and a leave-one-out cross validation strategy. Also, asymmetries may be used to define a test for AD that is very specific (90.24% specificity) but not especially sensitive. Two main conclusions are derived from the analysis of the eigenimage spectrum. Firstly, the recognition of AD patterns is improved when considering only the symmetric part of the spectrum. Secondly, asymmetries in the hypo-metabolic patterns, when present, are more pronounced in subjects with AD. Copyright © 2012 Elsevier B.V. All rights reserved.

Analysis of components of variance in multiple-reader studies of computer-aided diagnosis with different tasks

NASA Astrophysics Data System (ADS)

Beiden, Sergey V.; Wagner, Robert F.; Campbell, Gregory; Metz, Charles E.; Chan, Heang-Ping; Nishikawa, Robert M.; Schnall, Mitchell D.; Jiang, Yulei

2001-06-01

In recent years, the multiple-reader, multiple-case (MRMC) study paradigm has become widespread for receiver operating characteristic (ROC) assessment of systems for diagnostic imaging and computer-aided diagnosis. We review how MRMC data can be analyzed in terms of the multiple components of the variance (case, reader, interactions) observed in those studies. Such information is useful for the design of pivotal studies from results of a pilot study and also for studying the effects of reader training. Recently, several of the present authors have demonstrated methods to generalize the analysis of multiple variance components to the case where unaided readers of diagnostic images are compared with readers who receive the benefit of a computer assist (CAD). For this case it is necessary to model the possibility that several of the components of variance might be reduced when readers incorporate the computer assist, compared to the unaided reading condition. We review results of this kind of analysis on three previously published MRMC studies, two of which were applications of CAD to diagnostic mammography and one was an application of CAD to screening mammography. The results for the three cases are seen to differ, depending on the reader population sampled and the task of interest. Thus, it is not possible to generalize a particular analysis of variance components beyond the tasks and populations actually investigated.

Comparison of image features calculated in different dimensions for computer-aided diagnosis of lung nodules

NASA Astrophysics Data System (ADS)

Xu, Ye; Lee, Michael C.; Boroczky, Lilla; Cann, Aaron D.; Borczuk, Alain C.; Kawut, Steven M.; Powell, Charles A.

2009-02-01

Features calculated from different dimensions of images capture quantitative information of the lung nodules through one or multiple image slices. Previously published computer-aided diagnosis (CADx) systems have used either twodimensional (2D) or three-dimensional (3D) features, though there has been little systematic analysis of the relevance of the different dimensions and of the impact of combining different dimensions. The aim of this study is to determine the importance of combining features calculated in different dimensions. We have performed CADx experiments on 125 pulmonary nodules imaged using multi-detector row CT (MDCT). The CADx system computed 192 2D, 2.5D, and 3D image features of the lesions. Leave-one-out experiments were performed using five different combinations of features from different dimensions: 2D, 3D, 2.5D, 2D+3D, and 2D+3D+2.5D. The experiments were performed ten times for each group. Accuracy, sensitivity and specificity were used to evaluate the performance. Wilcoxon signed-rank tests were applied to compare the classification results from these five different combinations of features. Our results showed that 3D image features generate the best result compared with other combinations of features. This suggests one approach to potentially reducing the dimensionality of the CADx data space and the computational complexity of the system while maintaining diagnostic accuracy.

Fault diagnosis

NASA Technical Reports Server (NTRS)

Abbott, Kathy

1990-01-01

The objective of the research in this area of fault management is to develop and implement a decision aiding concept for diagnosing faults, especially faults which are difficult for pilots to identify, and to develop methods for presenting the diagnosis information to the flight crew in a timely and comprehensible manner. The requirements for the diagnosis concept were identified by interviewing pilots, analyzing actual incident and accident cases, and examining psychology literature on how humans perform diagnosis. The diagnosis decision aiding concept developed based on those requirements takes abnormal sensor readings as input, as identified by a fault monitor. Based on these abnormal sensor readings, the diagnosis concept identifies the cause or source of the fault and all components affected by the fault. This concept was implemented for diagnosis of aircraft propulsion and hydraulic subsystems in a computer program called Draphys (Diagnostic Reasoning About Physical Systems). Draphys is unique in two important ways. First, it uses models of both functional and physical relationships in the subsystems. Using both models enables the diagnostic reasoning to identify the fault propagation as the faulted system continues to operate, and to diagnose physical damage. Draphys also reasons about behavior of the faulted system over time, to eliminate possibilities as more information becomes available, and to update the system status as more components are affected by the fault. The crew interface research is examining display issues associated with presenting diagnosis information to the flight crew. One study examined issues for presenting system status information. One lesson learned from that study was that pilots found fault situations to be more complex if they involved multiple subsystems. Another was pilots could identify the faulted systems more quickly if the system status was presented in pictorial or text format. Another study is currently under way to examine pilot mental models of the aircraft subsystems and their use in diagnosis tasks. Future research plans include piloted simulation evaluation of the diagnosis decision aiding concepts and crew interface issues. Information is given in viewgraph form.

Detecting Disease in Radiographs with Intuitive Confidence

PubMed Central

2015-01-01

This paper argues in favor of a specific type of confidence for use in computer-aided diagnosis and disease classification, namely, sine/cosine values of angles represented by points on the unit circle. The paper shows how this confidence is motivated by Chinese medicine and how sine/cosine values are directly related with the two forces Yin and Yang. The angle for which sine and cosine are equal (45°) represents the state of equilibrium between Yin and Yang, which is a state of nonduality that indicates neither normality nor abnormality in terms of disease classification. The paper claims that the proposed confidence is intuitive and can be readily understood by physicians. The paper underpins this thesis with theoretical results in neural signal processing, stating that a sine/cosine relationship between the actual input signal and the perceived (learned) input is key to neural learning processes. As a practical example, the paper shows how to use the proposed confidence values to highlight manifestations of tuberculosis in frontal chest X-rays. PMID:26495433

Assessment methodologies and statistical issues for computer-aided diagnosis of lung nodules in computed tomography: contemporary research topics relevant to the lung image database consortium.

PubMed

Dodd, Lori E; Wagner, Robert F; Armato, Samuel G; McNitt-Gray, Michael F; Beiden, Sergey; Chan, Heang-Ping; Gur, David; McLennan, Geoffrey; Metz, Charles E; Petrick, Nicholas; Sahiner, Berkman; Sayre, Jim

2004-04-01

Cancer of the lung and bronchus is the leading fatal malignancy in the United States. Five-year survival is low, but treatment of early stage disease considerably improves chances of survival. Advances in multidetector-row computed tomography technology provide detection of smaller lung nodules and offer a potentially effective screening tool. The large number of images per exam, however, requires considerable radiologist time for interpretation and is an impediment to clinical throughput. Thus, computer-aided diagnosis (CAD) methods are needed to assist radiologists with their decision making. To promote the development of CAD methods, the National Cancer Institute formed the Lung Image Database Consortium (LIDC). The LIDC is charged with developing the consensus and standards necessary to create an image database of multidetector-row computed tomography lung images as a resource for CAD researchers. To develop such a prospective database, its potential uses must be anticipated. The ultimate applications will influence the information that must be included along with the images, the relevant measures of algorithm performance, and the number of required images. In this article we outline assessment methodologies and statistical issues as they relate to several potential uses of the LIDC database. We review methods for performance assessment and discuss issues of defining "truth" as well as the complications that arise when truth information is not available. We also discuss issues about sizing and populating a database.

Linear Optimization and Image Reconstruction

DTIC Science & Technology

1994-06-01

final example is again a novel one. We formulate the problem of computer assisted tomographic ( CAT ) image reconstruction as a linear optimization...possibility that a patient, Fred, suffers from a brain tumor. Further, the physician opts to make use of the CAT (Computer Aided Tomography) scan device...and examine the inside of Fred’s head without exploratory surgery. The CAT scan machine works by projecting a finite number of X-rays of known

Manned space station environmental control and life support system computer-aided technology assessment program

NASA Technical Reports Server (NTRS)

Hall, J. B., Jr.; Pickett, S. J.; Sage, K. H.

1984-01-01

A computer program for assessing manned space station environmental control and life support systems technology is described. The methodology, mission model parameters, evaluation criteria, and data base for 17 candidate technologies for providing metabolic oxygen and water to the crew are discussed. Examples are presented which demonstrate the capability of the program to evaluate candidate technology options for evolving space station requirements.

Geometric and computer-aided spline hob modeling

NASA Astrophysics Data System (ADS)

Brailov, I. G.; Myasoedova, T. M.; Panchuk, K. L.; Krysova, I. V.; Rogoza, YU A.

2018-03-01

The paper considers acquiring the spline hob geometric model. The objective of the research is the development of a mathematical model of spline hob for spline shaft machining. The structure of the spline hob is described taking into consideration the motion in parameters of the machine tool system of cutting edge positioning and orientation. Computer-aided study is performed with the use of CAD and on the basis of 3D modeling methods. Vector representation of cutting edge geometry is accepted as the principal method of spline hob mathematical model development. The paper defines the correlations described by parametric vector functions representing helical cutting edges designed for spline shaft machining with consideration for helical movement in two dimensions. An application for acquiring the 3D model of spline hob is developed on the basis of AutoLISP for AutoCAD environment. The application presents the opportunity for the use of the acquired model for milling process imitation. An example of evaluation, analytical representation and computer modeling of the proposed geometrical model is reviewed. In the mentioned example, a calculation of key spline hob parameters assuring the capability of hobbing a spline shaft of standard design is performed. The polygonal and solid spline hob 3D models are acquired by the use of imitational computer modeling.

CAD of control systems: Application of nonlinear programming to a linear quadratic formulation

NASA Technical Reports Server (NTRS)

Fleming, P.

1983-01-01

The familiar suboptimal regulator design approach is recast as a constrained optimization problem and incorporated in a Computer Aided Design (CAD) package where both design objective and constraints are quadratic cost functions. This formulation permits the separate consideration of, for example, model following errors, sensitivity measures and control energy as objectives to be minimized or limits to be observed. Efficient techniques for computing the interrelated cost functions and their gradients are utilized in conjunction with a nonlinear programming algorithm. The effectiveness of the approach and the degree of insight into the problem which it affords is illustrated in a helicopter regulation design example.

Automatic diagnosis of imbalanced ophthalmic images using a cost-sensitive deep convolutional neural network.

PubMed

Jiang, Jiewei; Liu, Xiyang; Zhang, Kai; Long, Erping; Wang, Liming; Li, Wangting; Liu, Lin; Wang, Shuai; Zhu, Mingmin; Cui, Jiangtao; Liu, Zhenzhen; Lin, Zhuoling; Li, Xiaoyan; Chen, Jingjing; Cao, Qianzhong; Li, Jing; Wu, Xiaohang; Wang, Dongni; Wang, Jinghui; Lin, Haotian

2017-11-21

Ocular images play an essential role in ophthalmological diagnoses. Having an imbalanced dataset is an inevitable issue in automated ocular diseases diagnosis; the scarcity of positive samples always tends to result in the misdiagnosis of severe patients during the classification task. Exploring an effective computer-aided diagnostic method to deal with imbalanced ophthalmological dataset is crucial. In this paper, we develop an effective cost-sensitive deep residual convolutional neural network (CS-ResCNN) classifier to diagnose ophthalmic diseases using retro-illumination images. First, the regions of interest (crystalline lens) are automatically identified via twice-applied Canny detection and Hough transformation. Then, the localized zones are fed into the CS-ResCNN to extract high-level features for subsequent use in automatic diagnosis. Second, the impacts of cost factors on the CS-ResCNN are further analyzed using a grid-search procedure to verify that our proposed system is robust and efficient. Qualitative analyses and quantitative experimental results demonstrate that our proposed method outperforms other conventional approaches and offers exceptional mean accuracy (92.24%), specificity (93.19%), sensitivity (89.66%) and AUC (97.11%) results. Moreover, the sensitivity of the CS-ResCNN is enhanced by over 13.6% compared to the native CNN method. Our study provides a practical strategy for addressing imbalanced ophthalmological datasets and has the potential to be applied to other medical images. The developed and deployed CS-ResCNN could serve as computer-aided diagnosis software for ophthalmologists in clinical application.

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.

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 modeling of lung cancer diagnosis-to-treatment process

PubMed Central

Ju, Feng; Lee, Hyo Kyung; Osarogiagbon, Raymond U.; Yu, Xinhua; Faris, Nick

2015-01-01

We introduce an example of a rigorous, quantitative method for quality improvement in lung cancer care-delivery. Computer process modeling methods are introduced for lung cancer diagnosis, staging and treatment selection process. Two types of process modeling techniques, discrete event simulation (DES) and analytical models, are briefly reviewed. Recent developments in DES are outlined and the necessary data and procedures to develop a DES model for lung cancer diagnosis, leading up to surgical treatment process are summarized. The analytical models include both Markov chain model and closed formulas. The Markov chain models with its application in healthcare are introduced and the approach to derive a lung cancer diagnosis process model is presented. Similarly, the procedure to derive closed formulas evaluating the diagnosis process performance is outlined. Finally, the pros and cons of these methods are discussed. PMID:26380181

Computer-Aided Evaluation of Forage Management: Forage Manager.

ERIC Educational Resources Information Center

Panciera, M. T.; And Others

1993-01-01

Presents the Forage Manager spreadsheet, developed as a forage management teaching tool to integrate agronomic, livestock, and cost data to demonstrate the impact of forage management on livestock production costs. Teaching applications, examples involving agronomic data and conventional agronomic evaluation, and limitations of the program are…

Computer-Aided Writing.

DTIC Science & Technology

1988-04-01

e.g., definitions, references, pictures) on the selected item in a separate window. For example, in a hyper- text document on astronomy , the reader...might arrive at the highlighted word " Copernicus ", select the word with the keyboard or mouse, and then be offered a number of related topics from

A Method for Extracting Suspected Parotid Lesions in CT Images using Feature-based Segmentation and Active Contours based on Stationary Wavelet Transform

NASA Astrophysics Data System (ADS)

Wu, T. Y.; Lin, S. F.

2013-10-01

Automatic suspected lesion extraction is an important application in computer-aided diagnosis (CAD). In this paper, we propose a method to automatically extract the suspected parotid regions for clinical evaluation in head and neck CT images. The suspected lesion tissues in low contrast tissue regions can be localized with feature-based segmentation (FBS) based on local texture features, and can be delineated with accuracy by modified active contour models (ACM). At first, stationary wavelet transform (SWT) is introduced. The derived wavelet coefficients are applied to derive the local features for FBS, and to generate enhanced energy maps for ACM computation. Geometric shape features (GSFs) are proposed to analyze each soft tissue region segmented by FBS; the regions with higher similarity GSFs with the lesions are extracted and the information is also applied as the initial conditions for fine delineation computation. Consequently, the suspected lesions can be automatically localized and accurately delineated for aiding clinical diagnosis. The performance of the proposed method is evaluated by comparing with the results outlined by clinical experts. The experiments on 20 pathological CT data sets show that the true-positive (TP) rate on recognizing parotid lesions is about 94%, and the dimension accuracy of delineation results can also approach over 93%.

A Health Insurance Portability and Accountability Act–Compliant Ocular Telehealth Network for the Remote Diagnosis and Management of Diabetic Retinopathy

PubMed Central

Li, Yaqin; Karnowski, Thomas P.; Tobin, Kenneth W.; Giancardo, Luca; Morris, Scott; Sparrow, Sylvia E.; Garg, Seema; Fox, Karen

2011-01-01

Abstract In this article, we present the design and implementation of a regional ocular telehealth network for remote assessment and management of diabetic retinopathy (DR), including the design requirements, network topology, protocol design, system work flow, graphics user interfaces, and performance evaluation. The Telemedical Retinal Image Analysis and Diagnosis Network is a computer-aided, image analysis telehealth paradigm for the diagnosis of DR and other retinal diseases using fundus images acquired from primary care end users delivering care to underserved patient populations in the mid-South and southeastern United States. PMID:21819244

Computer aided detection system for lung cancer using computer tomography scans

NASA Astrophysics Data System (ADS)

Mahesh, Shanthi; Rakesh, Spoorthi; Patil, Vidya C.

2018-04-01

Lung Cancer is a disease can be defined as uncontrolled cell growth in tissues of the lung. If we detect the Lung Cancer in its early stage, then that could be the key of its cure. In this work the non-invasive methods are studied for assisting in nodule detection. It supplies a Computer Aided Diagnosis System (CAD) for early detection of lung cancer nodules from the Computer Tomography (CT) images. CAD system is the one which helps to improve the diagnostic performance of radiologists in their image interpretations. The main aim of this technique is to develop a CAD system for finding the lung cancer using the lung CT images and classify the nodule as Benign or Malignant. For classifying cancer cells, SVM classifier is used. Here, image processing techniques have been used to de-noise, to enhance, for segmentation and edge detection of an image is used to extract the area, perimeter and shape of nodule. The core factors of this research are Image quality and accuracy.

Determinants of Progression to AIDS and Death Following HIV Diagnosis: A Retrospective Cohort Study in Wuhan, China

PubMed Central

Jiang, Hongbo; Xie, Nianhua; Cao, Beibei; Tan, Li; Fan, Yunzhou; Zhang, Fan; Yao, Zhongzhao; Liu, Li; Nie, Shaofa

2013-01-01

Objective To identify determinants associated with disease progression and death following human immunodeficiency virus (HIV) diagnosis. Methods Disease progression data from the diagnosis of HIV infection or acquiring immunodeficiency syndrome (AIDS) to February 29, 2012 were retrospectively collected from the national surveillance system databases and the national treatment database in Wuhan, China. Kaplan-Meier method, Logistic regression and Cox proportional hazards model were applied to identify the related factors of progression to AIDS or death following HIV diagnosis. Results By the end of February 2012, 181 of 691 HIV infectors developed to AIDS, and 129 of 470 AIDS patients died among whom 289 cases received concurrent HIV/AIDS diagnosis. Compared with men infected through homosexual behavior, injection drug users possessed sharply decreased hazard ratio (HR) for progression to AIDS following HIV diagnosis [HR = 0.31, 95% confidence interval (CI), 0.18–0.54, P = 4.01×10−5]. HIV infectors at least 60 years presented 1.15-fold (HR = 2.15, 95% CI, 1.15–4.03, P = 0.017) increased risk to develop AIDS when compared with those aged 17–29 years. Similarly, AIDS patients with diagnosis ages between 50 and 59 years were at a 1.60-fold higher risk of death (HR = 2.60, 95% CI, 1.18–5.72, P = 0.017) compared to those aged 19–29 years. AIDS patients with more CD4+ T-cells within 6 months at diagnosis (cell/µL) presented lower risk of death (HR = 0.29 for 50- vs <50, 95% CI, 0.15–0.59, P = 0.001). The highly active antiretroviral therapy (HAART) delayed progression to AIDS from HIV diagnosis (HR = 0.15, 95% CI, 0.07–0.34, P = 6.46×10−6) and reduced the risk of death after AIDS diagnosis (HR = 0.02, 95% CI, 0.01–0.04, P = 7.25×10−25). Conclusions Progression to AIDS and death following HIV diagnosis differed in age at diagnosis, transmission categories, CD4+ T-cell counts and HAART. Effective interventions should target those at higher risk for morbidity or mortality, ensuring early diagnosis and timely treatment to slow down the disease progression. PMID:24376638

Determinants of progression to AIDS and death following HIV diagnosis: a retrospective cohort study in Wuhan, China.

PubMed

Jiang, Hongbo; Xie, Nianhua; Cao, Beibei; Tan, Li; Fan, Yunzhou; Zhang, Fan; Yao, Zhongzhao; Liu, Li; Nie, Shaofa

2013-01-01

To identify determinants associated with disease progression and death following human immunodeficiency virus (HIV) diagnosis. Disease progression data from the diagnosis of HIV infection or acquiring immunodeficiency syndrome (AIDS) to February 29, 2012 were retrospectively collected from the national surveillance system databases and the national treatment database in Wuhan, China. Kaplan-Meier method, Logistic regression and Cox proportional hazards model were applied to identify the related factors of progression to AIDS or death following HIV diagnosis. By the end of February 2012, 181 of 691 HIV infectors developed to AIDS, and 129 of 470 AIDS patients died among whom 289 cases received concurrent HIV/AIDS diagnosis. Compared with men infected through homosexual behavior, injection drug users possessed sharply decreased hazard ratio (HR) for progression to AIDS following HIV diagnosis [HR = 0.31, 95% confidence interval (CI), 0.18-0.54, P = 4.01×10(-5)]. HIV infectors at least 60 years presented 1.15-fold (HR = 2.15, 95% CI, 1.15-4.03, P = 0.017) increased risk to develop AIDS when compared with those aged 17-29 years. Similarly, AIDS patients with diagnosis ages between 50 and 59 years were at a 1.60-fold higher risk of death (HR = 2.60, 95% CI, 1.18-5.72, P = 0.017) compared to those aged 19-29 years. AIDS patients with more CD4(+) T-cells within 6 months at diagnosis (cell/µL) presented lower risk of death (HR = 0.29 for 50- vs <50, 95% CI, 0.15-0.59, P = 0.001). The highly active antiretroviral therapy (HAART) delayed progression to AIDS from HIV diagnosis (HR = 0.15, 95% CI, 0.07-0.34, P = 6.46×10(-6)) and reduced the risk of death after AIDS diagnosis (HR = 0.02, 95% CI, 0.01-0.04, P = 7.25×10(-25)). Progression to AIDS and death following HIV diagnosis differed in age at diagnosis, transmission categories, CD4(+) T-cell counts and HAART. Effective interventions should target those at higher risk for morbidity or mortality, ensuring early diagnosis and timely treatment to slow down the disease progression.

Bipolar disorder in adolescence.

PubMed

DeFilippis, Melissa; Wagner, Karen Dineen

2013-08-01

Bipolar disorder is a serious psychiatric condition that may have onset in childhood. It is important for physicians to recognize the symptoms of bipolar disorder in children and adolescents in order to accurately diagnose this illness early in its course. Evidence regarding the efficacy of various treatments is necessary to guide the management of bipolar disorder in youth. For example, several medications commonly used for adults with bipolar disorder have not shown efficacy for children and adolescents with bipolar disorder. This article reviews the prevalence, diagnosis, course, and treatment of bipolar disorder in children and adolescents and provides physicians with information that will aid in diagnosis and treatment.

Image-based diagnostic aid for interstitial lung disease with secondary data integration

NASA Astrophysics Data System (ADS)

Depeursinge, Adrien; Müller, Henning; Hidki, Asmâa; Poletti, Pierre-Alexandre; Platon, Alexandra; Geissbuhler, Antoine

2007-03-01

Interstitial lung diseases (ILDs) are a relatively heterogeneous group of around 150 illnesses with often very unspecific symptoms. The most complete imaging method for the characterisation of ILDs is the high-resolution computed tomography (HRCT) of the chest but a correct interpretation of these images is difficult even for specialists as many diseases are rare and thus little experience exists. Moreover, interpreting HRCT images requires knowledge of the context defined by clinical data of the studied case. A computerised diagnostic aid tool based on HRCT images with associated medical data to retrieve similar cases of ILDs from a dedicated database can bring quick and precious information for example for emergency radiologists. The experience from a pilot project highlighted the need for detailed database containing high-quality annotations in addition to clinical data. The state of the art is studied to identify requirements for image-based diagnostic aid for interstitial lung disease with secondary data integration. The data acquisition steps are detailed. The selection of the most relevant clinical parameters is done in collaboration with lung specialists from current literature, along with knowledge bases of computer-based diagnostic decision support systems. In order to perform high-quality annotations of the interstitial lung tissue in the HRCT images an annotation software and its own file format is implemented for DICOM images. A multimedia database is implemented to store ILD cases with clinical data and annotated image series. Cases from the University & University Hospitals of Geneva (HUG) are retrospectively and prospectively collected to populate the database. Currently, 59 cases with certified diagnosis and their clinical parameters are stored in the database as well as 254 image series of which 26 have their regions of interest annotated. The available data was used to test primary visual features for the classification of lung tissue patterns. These features show good discriminative properties for the separation of five classes of visual observations.

Computed tomography-assisted laparoscopic removal of intraabdominally migrated levonorgestrel-releasing intrauterine systems.

PubMed

Mahmoud, Mohamad S; Merhi, Zaher O

2010-04-01

To report three cases of migrated levonorgestrel intrauterine device (LNG-IUS) into the pelvic/abdominal cavity removed laparoscopically with the aid of preoperative computed tomography (CT) scan imaging. Three patients presenting with a missing LNG-IUS on examination and pelvic ultrasound are presented. A preoperative CT scan was performed, what helped in a successful removal of the LNG-IUS. The patients were discharged home the same day of the procedure. Our cases reinforce, besides the diagnosis of a migrated LNG-IUS by ultrasound, the fact that preoperative CT scan imaging assists in the diagnosis of the precise location of a migrated LNG-IUS into the pelvic/abdominal cavity and helps the physician in the prediction of the difficulty of the laparoscopic removal.

[Role of multislice computed tomography in the diagnosis of acute rupture of the thoracic aorta and hepatic artery in a patient with severe concomitant injury].

PubMed

Muslimov, R Sh; Sharifullin, F A; Chernaia, N R; Novruzbekov, M S; Kokov, L S

2015-01-01

Acute traumatic aortic rupture is associated with extremely high mortality rates and requires emergency diagnosis and treatment. This clinical example shows the role of multislice spiral computed tomography in the emergency diagnosis of rupture of two large arterial vessels in severe concomitant injury. It presents the benefits of this rapid and noninvasive imaging technique, an algorithm of the study and the semiotics of injuries in patients with suspected traumatic aortic rupture. The paper also shows the importance of this method in defining treatment policy and then in the assessment of the results of the performed correction.

Image Processing and Computer Aided Diagnosis in Computed Tomography of the Breast

DTIC Science & Technology

2007-10-01

Brian Harrawood, Ronald Pedroni, Alexander Crowell, Robert Macri, Mathew Kiser, Richard Walter ,Werner 111 Tornow , Neutron Stimulated Emission...1( kkkk k nn kkk n k n k w PBbywbb σσσ += +−⋅+=+ , (2) MLE estimate is known to increase high frequency image noise. To overcome this, some...contrast to noise ratio results for the three images shown in Figure 5. With grid w /o grid w /o grid; scatter reduction RSF 11% 45% 10% CNR 7.04 6.99

Automated Quantification of Pneumothorax in CT

PubMed Central

Do, Synho; Salvaggio, Kristen; Gupta, Supriya; Kalra, Mannudeep; Ali, Nabeel U.; Pien, Homer

2012-01-01

An automated, computer-aided diagnosis (CAD) algorithm for the quantification of pneumothoraces from Multidetector Computed Tomography (MDCT) images has been developed. Algorithm performance was evaluated through comparison to manual segmentation by expert radiologists. A combination of two-dimensional and three-dimensional processing techniques was incorporated to reduce required processing time by two-thirds (as compared to similar techniques). Volumetric measurements on relative pneumothorax size were obtained and the overall performance of the automated method shows an average error of just below 1%. PMID:23082091

Correlative Feature Analysis for Multimodality Breast CAD

DTIC Science & Technology

2009-09-01

Imaging 20, 1275–1284 2001. 22V. Caselles, R . Kimmel, and G. Sapiro, “Geodesic active contours,” Int. J. Comput. Vis. 22, 61–79 1997. 23R. Malladi , J...A. R . Jamieson, C. A. Sennett, and S. A. Jensen, “Evaluation of computer-aided diagnosis on a large clinical full-field digital mammographic dataset...Academic Radiology, 15, 1437-1445 (2008). Conference Proceeding Papers [1] Y. Yuan, M. L. Giger, K. Suzuki, H. Li, and A. R . Jamieson, “A

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

Van Wie, N.H.

An overview of the UCC-ND system for computer-aided cost estimating is provided. The program is generally utilized in the preparation of construction cost estimates for projects costing $25,000,000 or more. The advantages of the system to the manager and the estimator are discussed, and examples of the product are provided. 19 figures, 1 table.

Headsprout Early Reading for Students at Risk for Reading Failure

ERIC Educational Resources Information Center

Kreskey, Donna D.

2012-01-01

This study examined the efficacy of using Headsprout Early Reading (Headsprout, 2007) to supplement a balanced literacy curriculum for kindergarten and first grade students in a suburban public school system. Headsprout, which is an example of computer aided instruction (CAI), provided internet-based, supplemental reading instruction that…

Estimation of risk of cancers before occurrence of acquired immunodeficiency syndrome in persons infected with human immunodeficiency virus.

PubMed

Li, Yueming; Law, Matthew; McDonald, Ann; Correll, Patty; Kaldor, John M; Grulich, Andrew E

2002-01-15

There is methodological debate as to whether cohorts defined by acquired immunodeficiency syndrome (AIDS) diagnosis can be used to estimate risks of cancer in persons with human immunodeficiency virus (HIV) before AIDS. The authors compared risks of non-AIDS-defining cancers before AIDS in persons with HIV using a cohort based on AIDS diagnosis and a second cohort based on HIV diagnosis. National population-based registries of AIDS and HIV diagnoses to August 1999 were matched separately with the National Cancer Registry in Australia. Four analyses were performed. In analysis 1, follow-up was from 5 years before AIDS registration in 8,118 persons with AIDS. Analysis 2 was similar but adjusted expected numbers of cancers for decreased survival. Analysis 3 was based on 7,061 persons registered with HIV, with follow-up from the reported date of diagnosis. Analysis 4 was based on 2,112 AIDS cases previously reported with HIV, with follow-up from 5 years before AIDS diagnosis. In all analyses, follow-up ended at cancer diagnosis, death, 6 months before AIDS, or the end of available cancer data, whichever occurred first. For 10 types of cancer there were at least three cases in any one of the analyses. For these cancers there was no systematic pattern such that one analysis produced consistently higher or lower estimates than the others. These analyses suggest that cancer risk in persons with HIV before AIDS diagnosis may be estimated reliably based on cancer experience 5 years before AIDS.

Characteristics of lip-mouth region in smiling position from 80 persons with acceptable faces and individual normal occlusions.

PubMed

Zhang, Jiangheng; Chen, Yangxi; Zhou, Xiukun

2002-09-01

The characteristics of lip-mouth region including the soft and hard tissues in smiling position with frontal fixed position photographic computer-aided analysis were studied. The subjects were 80 persons (40 male and 40 females, age range: 17 to approximately 25 years) with acceptable faces and individual normal occlusions. The subjects were asked to take maximum smiling position to accept photographic measurement with computer-aided analysis. The maximum smile line could be divided into 3 categories: low smile line (16.25%), average smile line (68.75%), and high smile line (15%). The method adopting maximum smiling position to study the lip-month region is reproducible and comparable. This study would be helpful to provide a quantitative reference for clinical investigation, diagnosis, treatment and efficacy appraisal.

Program Helps Generate And Manage Graphics

NASA Technical Reports Server (NTRS)

Truong, L. V.

1994-01-01

Living Color Frame Maker (LCFM) computer program generates computer-graphics frames. Graphical frames saved as text files, in readable and disclosed format, easily retrieved and manipulated by user programs for wide range of real-time visual information applications. LCFM implemented in frame-based expert system for visual aids in management of systems. Monitoring, diagnosis, and/or control, diagrams of circuits or systems brought to "life" by use of designated video colors and intensities to symbolize status of hardware components (via real-time feedback from sensors). Status of systems can be displayed. Written in C++ using Borland C++ 2.0 compiler for IBM PC-series computers and compatible computers running MS-DOS.

[The new concept of osteoporosis. Early diagnosis, prevention and therapy are possible today].

PubMed

Hesch, R D; Harms, H; Rittinghaus, E F; Brabant, G

1990-04-15

A paradigma of osteoporosis pathology is discussed, at the center of which is the hormone-related disturbance of the osteoblast/osteoclast functional unit. A liberal replacement of estrogen-gestagen in post-menopausal women is advocated. Early diagnosis with the aid of quantitative computed tomography makes it possible to establish the indication for timely hormonal treatment in the future, which can result in a measureable increase in bone mass. Late therapy, that is, treatment initiated after the occurrence of fractures, has proven largely ineffective.

Neuromyelitis optica: Application of computer diagnostics to historical case reports.

PubMed

Garcia Reitboeck, Pablo; Garrard, Peter; Peters, Timothy

2017-01-01

The retrospective diagnosis of illnesses by medical historians can often be difficult and prone to bias, although knowledge of the medical disorders of historical figures is key to the understanding of their behavior and reactions. The recent application of computer diagnostics to historical figures allows an objective differential diagnosis to be accomplished. Taking an example from clinical neurology, we analyzed the earliest reported cases of Devic's disease (neuromyelitis optica) that commonly affects the optic nerve and spinal cord and was previously often confused with multiple sclerosis. We conclude that in most identified cases the software concurred with the contemporary physicians' interpretation, but some claimed cases either had insufficient data to provide a diagnosis or other possible diagnoses were suggested that had not been considered. Computational methods may, therefore, help historians to diagnose the ailments of historical figures with greater objectivity.

Aircraft geometry verification with enhanced computer generated displays

NASA Technical Reports Server (NTRS)

Cozzolongo, J. V.

1982-01-01

A method for visual verification of aerodynamic geometries using computer generated, color shaded images is described. The mathematical models representing aircraft geometries are created for use in theoretical aerodynamic analyses and in computer aided manufacturing. The aerodynamic shapes are defined using parametric bi-cubic splined patches. This mathematical representation is then used as input to an algorithm that generates a color shaded image of the geometry. A discussion of the techniques used in the mathematical representation of the geometry and in the rendering of the color shaded display is presented. The results include examples of color shaded displays, which are contrasted with wire frame type displays. The examples also show the use of mapped surface pressures in terms of color shaded images of V/STOL fighter/attack aircraft and advanced turboprop aircraft.

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.

Computed Tomography

NASA Astrophysics Data System (ADS)

Castellano, Isabel; Geleijns, Jacob

After its clinical introduction in 1973, computed tomography developed from an x-ray modality for axial imaging in neuroradiology into a versatile three dimensional imaging modality for a wide range of applications in for example oncology, vascular radiology, cardiology, traumatology and even in interventional radiology. Computed tomography is applied for diagnosis, follow-up studies and screening of healthy subpopulations with specific risk factors. This chapter provides a general introduction in computed tomography, covering a short history of computed tomography, technology, image quality, dosimetry, room shielding, quality control and quality criteria.

Computer-Based Technologies in Dentistry: Types and Applications

PubMed Central

Albuha Al-Mussawi, Raja’a M.; Farid, Farzaneh

2016-01-01

During dental education, dental students learn how to examine patients, make diagnosis, plan treatment and perform dental procedures perfectly and efficiently. However, progresses in computer-based technologies including virtual reality (VR) simulators, augmented reality (AR) and computer aided design/computer aided manufacturing (CAD/CAM) systems have resulted in new modalities for instruction and practice of dentistry. Virtual reality dental simulators enable repeated, objective and assessable practice in various controlled situations. Superimposition of three-dimensional (3D) virtual images on actual images in AR allows surgeons to simultaneously visualize the surgical site and superimpose informative 3D images of invisible regions on the surgical site to serve as a guide. The use of CAD/CAM systems for designing and manufacturing of dental appliances and prostheses has been well established. This article reviews computer-based technologies, their application in dentistry and their potentials and limitations in promoting dental education, training and practice. Practitioners will be able to choose from a broader spectrum of options in their field of practice by becoming familiar with new modalities of training and practice. PMID:28392819

Computer-Based Technologies in Dentistry: Types and Applications.

PubMed

Albuha Al-Mussawi, Raja'a M; Farid, Farzaneh

2016-06-01

During dental education, dental students learn how to examine patients, make diagnosis, plan treatment and perform dental procedures perfectly and efficiently. However, progresses in computer-based technologies including virtual reality (VR) simulators, augmented reality (AR) and computer aided design/computer aided manufacturing (CAD/CAM) systems have resulted in new modalities for instruction and practice of dentistry. Virtual reality dental simulators enable repeated, objective and assessable practice in various controlled situations. Superimposition of three-dimensional (3D) virtual images on actual images in AR allows surgeons to simultaneously visualize the surgical site and superimpose informative 3D images of invisible regions on the surgical site to serve as a guide. The use of CAD/CAM systems for designing and manufacturing of dental appliances and prostheses has been well established. This article reviews computer-based technologies, their application in dentistry and their potentials and limitations in promoting dental education, training and practice. Practitioners will be able to choose from a broader spectrum of options in their field of practice by becoming familiar with new modalities of training and practice.

A novel method to acquire 3D data from serial 2D images of a dental cast

NASA Astrophysics Data System (ADS)

Yi, Yaxing; Li, Zhongke; Chen, Qi; Shao, Jun; Li, Xinshe; Liu, Zhiqin

2007-05-01

This paper introduced a newly developed method to acquire three-dimensional data from serial two-dimensional images of a dental cast. The system consists of a computer and a set of data acquiring device. The data acquiring device is used to take serial pictures of the a dental cast; an artificial neural network works to translate two-dimensional pictures to three-dimensional data; then three-dimensional image can reconstruct by the computer. The three-dimensional data acquiring of dental casts is the foundation of computer-aided diagnosis and treatment planning in orthodontics.

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

Computer-Aided Discovery Tools for Volcano Deformation Studies with InSAR and GPS

NASA Astrophysics Data System (ADS)

Pankratius, V.; Pilewskie, J.; Rude, C. M.; Li, J. D.; Gowanlock, M.; Bechor, N.; Herring, T.; Wauthier, C.

2016-12-01

We present a Computer-Aided Discovery approach that facilitates the cloud-scalable fusion of different data sources, such as GPS time series and Interferometric Synthetic Aperture Radar (InSAR), for the purpose of identifying the expansion centers and deformation styles of volcanoes. The tools currently developed at MIT allow the definition of alternatives for data processing pipelines that use various analysis algorithms. The Computer-Aided Discovery system automatically generates algorithmic and parameter variants to help researchers explore multidimensional data processing search spaces efficiently. We present first application examples of this technique using GPS data on volcanoes on the Aleutian Islands and work in progress on combined GPS and InSAR data in Hawaii. In the model search context, we also illustrate work in progress combining time series Principal Component Analysis with InSAR augmentation to constrain the space of possible model explanations on current empirical data sets and achieve a better identification of deformation patterns. This work is supported by NASA AIST-NNX15AG84G and NSF ACI-1442997 (PI: V. Pankratius).

Computer-Aided Software Engineering - An approach to real-time software development

NASA Technical Reports Server (NTRS)

Walker, Carrie K.; Turkovich, John J.

1989-01-01

A new software engineering discipline is Computer-Aided Software Engineering (CASE), a technology aimed at automating the software development process. This paper explores the development of CASE technology, particularly in the area of real-time/scientific/engineering software, and a history of CASE is given. The proposed software development environment for the Advanced Launch System (ALS CASE) is described as an example of an advanced software development system for real-time/scientific/engineering (RT/SE) software. The Automated Programming Subsystem of ALS CASE automatically generates executable code and corresponding documentation from a suitably formatted specification of the software requirements. Software requirements are interactively specified in the form of engineering block diagrams. Several demonstrations of the Automated Programming Subsystem are discussed.

Embedded Process Modeling, Analogy-Based Option Generation and Analytical Graphic Interaction for Enhanced User-Computer Interaction: An Interactive Storyboard of Next Generation User-Computer Interface Technology. Phase 1

DTIC Science & Technology

1988-03-01

structure of the interface is a mapping from the physical world [for example, the use of icons, which S have inherent meaning to users but represent...design alternatives. Mechanisms for linking the user to the computer include physical devices (keyboards), actions taken with the devices (keystrokes...VALUATION AIDES TEMLATEI IITCOM1I LATOR IACTICAL KNOWLEDGE ACGIUISITION MICNnII t 1 Fig. 9. INTACVAL. * OtJiCTs ARE PHYSICAL ENTITIES OR CONCEPTUAL EN

Automated diagnosis of autism: in search of a mathematical marker.

PubMed

Bhat, Shreya; Acharya, U Rajendra; Adeli, Hojjat; Bairy, G Muralidhar; Adeli, Amir

2014-01-01

Autism is a type of neurodevelopmental disorder affecting the memory, behavior, emotion, learning ability, and communication of an individual. An early detection of the abnormality, due to irregular processing in the brain, can be achieved using electroencephalograms (EEG). The variations in the EEG signals cannot be deciphered by mere visual inspection. Computer-aided diagnostic tools can be used to recognize the subtle and invisible information present in the irregular EEG pattern and diagnose autism. This paper presents a state-of-the-art review of automated EEG-based diagnosis of autism. Various time domain, frequency domain, time-frequency domain, and nonlinear dynamics for the analysis of autistic EEG signals are described briefly. A focus of the review is the use of nonlinear dynamics and chaos theory to discover the mathematical biomarkers for the diagnosis of the autism analogous to biological markers. A combination of the time-frequency and nonlinear dynamic analysis is the most effective approach to characterize the nonstationary and chaotic physiological signals for the automated EEG-based diagnosis of autism spectrum disorder (ASD). The features extracted using these nonlinear methods can be used as mathematical markers to detect the early stage of autism and aid the clinicians in their diagnosis. This will expedite the administration of appropriate therapies to treat the disorder.

Computer aided segmentation of kidneys using locally shape constrained deformable models on CT images

NASA Astrophysics Data System (ADS)

Erdt, Marius; Sakas, Georgios

2010-03-01

This work presents a novel approach for model based segmentation of the kidney in images acquired by Computed Tomography (CT). The developed computer aided segmentation system is expected to support computer aided diagnosis and operation planning. We have developed a deformable model based approach based on local shape constraints that prevents the model from deforming into neighboring structures while allowing the global shape to adapt freely to the data. Those local constraints are derived from the anatomical structure of the kidney and the presence and appearance of neighboring organs. The adaptation process is guided by a rule-based deformation logic in order to improve the robustness of the segmentation in areas of diffuse organ boundaries. Our work flow consists of two steps: 1.) a user guided positioning and 2.) an automatic model adaptation using affine and free form deformation in order to robustly extract the kidney. In cases which show pronounced pathologies, the system also offers real time mesh editing tools for a quick refinement of the segmentation result. Evaluation results based on 30 clinical cases using CT data sets show an average dice correlation coefficient of 93% compared to the ground truth. The results are therefore in most cases comparable to manual delineation. Computation times of the automatic adaptation step are lower than 6 seconds which makes the proposed system suitable for an application in clinical practice.

SYSTID - A flexible tool for the analysis of communication systems.

NASA Technical Reports Server (NTRS)

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

1972-01-01

Description of the System Time Domain Simulation (SYSTID) computer-aided analysis program which is specifically structured for communication systems analysis. The SYSTID program is user oriented so that very little knowledge of computer techniques and very little programming ability are required for proper application. The program is designed so that the user can go from a system block diagram to an accurate simulation by simply programming a single English language statement for each block in the system. The mathematical and functional models available in the SYSTID library are presented. An example problem is given which illustrates the ease of modeling communication systems. Examples of the outputs available are presented, and proposed improvements are summarized.

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

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.

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.

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.

Hepatitis Diagnosis Using Facial Color Image

NASA Astrophysics Data System (ADS)

Liu, Mingjia; Guo, Zhenhua

Facial color diagnosis is an important diagnostic method in traditional Chinese medicine (TCM). However, due to its qualitative, subjective and experi-ence-based nature, traditional facial color diagnosis has a very limited application in clinical medicine. To circumvent the subjective and qualitative problems of facial color diagnosis of Traditional Chinese Medicine, in this paper, we present a novel computer aided facial color diagnosis method (CAFCDM). The method has three parts: face Image Database, Image Preprocessing Module and Diagnosis Engine. Face Image Database is carried out on a group of 116 patients affected by 2 kinds of liver diseases and 29 healthy volunteers. The quantitative color feature is extracted from facial images by using popular digital image processing techni-ques. Then, KNN classifier is employed to model the relationship between the quantitative color feature and diseases. The results show that the method can properly identify three groups: healthy, severe hepatitis with jaundice and severe hepatitis without jaundice with accuracy higher than 73%.

Improved biliary detection and diagnosis through intelligent machine analysis.

PubMed

Logeswaran, Rajasvaran

2012-09-01

This paper reports on work undertaken to improve automated detection of bile ducts in magnetic resonance cholangiopancreatography (MRCP) images, with the objective of conducting preliminary classification of the images for diagnosis. The proposed I-BDeDIMA (Improved Biliary Detection and Diagnosis through Intelligent Machine Analysis) scheme is a multi-stage framework consisting of successive phases of image normalization, denoising, structure identification, object labeling, feature selection and disease classification. A combination of multiresolution wavelet, dynamic intensity thresholding, segment-based region growing, region elimination, statistical analysis and neural networks, is used in this framework to achieve good structure detection and preliminary diagnosis. Tests conducted on over 200 clinical images with known diagnosis have shown promising results of over 90% accuracy. The scheme outperforms related work in the literature, making it a viable framework for computer-aided diagnosis of biliary diseases. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

The use of infrared thermal imaging in the diagnosis of deep vein thrombosis

NASA Astrophysics Data System (ADS)

Kacmaz, Seydi; Ercelebi, Ergun; Zengin, Suat; Cindoruk, Sener

2017-11-01

The diagnosis of Deep Vein Thrombosis is of vital importance, especially in emergency situations where there is a lack of time and the patient's condition is critical. Late diagnosis causes cost increase, long waiting time, and improper treatment. Today, with the rapidly developing technology, the cost of thermal cameras is gradually decreasing day by day. Studies have shown that many diseases are associated with heat. As a result, infrared images are thought to be a tool for diagnosing various diseases. In this study, it has been shown that infrared thermal imaging can be used as a pre-screening test in the diagnosis of Deep Vein Thrombosis with the developed computer aided software. In addition, a sample combination is shown for applications that utilize emergency services to perform diagnosis and treatment of Deep Vein Thrombosis as soon as possible.

[123I]N-ω-fluoropropyl-2β-carbomethoxy-3β-(4-iodophenyl)nortropane single-photon emission computed tomography brain imaging in the diagnosis of dementia with Lewy bodies.

PubMed

Walker, Zuzana; Cummings, Jeffrey L

2012-01-01

Early, accurate diagnosis of dementia with Lewy bodies (DLB), in particular its differentiation from Alzheimer's disease, is important for optimal management, providing patients/carers with information about the likely symptomatology and illness course, allowing initiation of effective pharmacotherapy, and avoiding the consequences of neuroleptic sensitivity. Clinical diagnosis of DLB has high specificity but low sensitivity. Clinical trials of [(123)I]N-ω-fluoropropyl-2β-carbomethoxy-3β-(4-iodophenyl)nortropane single-photon emission computed tomography ([(123)I]FP-CIT SPECT) indicate high positive and negative percent agreement with reference to clinical diagnosis, and high sensitivity and specificity in patients with neuropathologically confirmed diagnoses of DLB. An abnormal [(123)I]FP-CIT SPECT image in patients fulfilling criteria for possible DLB advances the certainty of a diagnosis to probable DLB. [(123)I]FP-CIT SPECT, by identifying the striatal dopaminergic deficit, can be a valuable diagnostic aid and can provide support to a clinical diagnosis of DLB in patients with dementia. The technique is likely to be of particular utility in patients with dementia with an uncertain diagnosis. Copyright © 2012 The Alzheimer's Association. Published by Elsevier Inc. All rights reserved.

Visualization of suspicious lesions in breast MRI based on intelligent neural systems

NASA Astrophysics Data System (ADS)

Twellmann, Thorsten; Lange, Oliver; Nattkemper, Tim Wilhelm; Meyer-Bäse, Anke

2006-05-01

Intelligent medical systems based on supervised and unsupervised artificial neural networks are applied to the automatic visualization and classification of suspicious lesions in breast MRI. These systems represent an important component of future sophisticated computer-aided diagnosis systems and enable the extraction of spatial and temporal features of dynamic MRI data stemming from patients with confirmed lesion diagnosis. By taking into account the heterogenity of the cancerous tissue, these techniques reveal the malignant, benign and normal kinetic signals and and provide a regional subclassification of pathological breast tissue. Intelligent medical systems are expected to have substantial implications in healthcare politics by contributing to the diagnosis of indeterminate breast lesions by non-invasive imaging.

Ideas in Practice (3): A Simulated Laboratory Experience in Digital Design.

ERIC Educational Resources Information Center

Cleaver, Thomas G.

1988-01-01

Gives an example of the use of a simplified logic simulator in a logic design course. Discusses some problems in logic design classes, commercially available software, and software problems. Describes computer-aided engineering (CAE) software. Lists 14 experiments in the simulated laboratory and presents students' evaluation of the course. (YP)

Solving rational matrix equations in the state space with applications to computer-aided control-system design

NASA Technical Reports Server (NTRS)

Packard, A. K.; Sastry, S. S.

1986-01-01

A method of solving a class of linear matrix equations over various rings is proposed, using results from linear geometric control theory. An algorithm, successfully implemented, is presented, along with non-trivial numerical examples. Applications of the method to the algebraic control system design methodology are discussed.

Impact of CALS on Electronic Publishing Systems and Users.

ERIC Educational Resources Information Center

Beazley, William G.

1990-01-01

The U.S. Department of Defense has begun using its buying power to enforce standards on the vendors and contractors of automatic data processing hardware and software. An example of this, the Computer-Aided Acquisition and Logistic Support (CALS) program, is described, and how it will affect electronic publishing systems is discussed. (five…

A Guide to Computer Adaptive Testing Systems

ERIC Educational Resources Information Center

Davey, Tim

2011-01-01

Some brand names are used generically to describe an entire class of products that perform the same function. "Kleenex," "Xerox," "Thermos," and "Band-Aid" are good examples. The term "computerized adaptive testing" (CAT) is similar in that it is often applied uniformly across a diverse family of testing methods. Although the various members of…

Study of Aided Diagnosis of Hepatic Carcinoma Based on Artificial Neural Network Combined with Tumor Marker Group

NASA Astrophysics Data System (ADS)

Tan, Shanjuan; Feng, Feifei; Wu, Yongjun; Wu, Yiming

To develop a computer-aided diagnostic scheme by using an artificial neural network (ANN) combined with tumor markers for diagnosis of hepatic carcinoma (HCC) as a clinical assistant method. 140 serum samples (50 malignant, 40 benign and 50 normal) were analyzed for α-fetoprotein (AFP), carbohydrate antigen 125 (CA125), carcinoembryonic antigen (CEA), sialic acid (SA) and calcium (Ca). The five tumor marker values were then used as ANN inputs data. The result of ANN was compared with that of discriminant analysis by receiver operating characteristic (ROC) curve (AUC) analysis. The diagnostic accuracy of ANN and discriminant analysis among all samples of the test group was 95.5% and 79.3%, respectively. Analysis of multiple tumor markers based on ANN may be a better choice than the traditional statistical methods for differentiating HCC from benign or normal.

Automated localization and segmentation techniques for B-mode ultrasound images: A review.

PubMed

Meiburger, Kristen M; Acharya, U Rajendra; Molinari, Filippo

2018-01-01

B-mode ultrasound imaging is used extensively in medicine. Hence, there is a need to have efficient segmentation tools to aid in computer-aided diagnosis, image-guided interventions, and therapy. This paper presents a comprehensive review on automated localization and segmentation techniques for B-mode ultrasound images. The paper first describes the general characteristics of B-mode ultrasound images. Then insight on the localization and segmentation of tissues is provided, both in the case in which the organ/tissue localization provides the final segmentation and in the case in which a two-step segmentation process is needed, due to the desired boundaries being too fine to locate from within the entire ultrasound frame. Subsequenly, examples of some main techniques found in literature are shown, including but not limited to shape priors, superpixel and classification, local pixel statistics, active contours, edge-tracking, dynamic programming, and data mining. Ten selected applications (abdomen/kidney, breast, cardiology, thyroid, liver, vascular, musculoskeletal, obstetrics, gynecology, prostate) are then investigated in depth, and the performances of a few specific applications are compared. In conclusion, future perspectives for B-mode based segmentation, such as the integration of RF information, the employment of higher frequency probes when possible, the focus on completely automatic algorithms, and the increase in available data are discussed. Copyright © 2017 Elsevier Ltd. All rights reserved.

Significant Increase in Factual Knowledge with Web-Assisted Problem-Based Learning as Part of an Undergraduate Cardio-Respiratory Curriculum

ERIC Educational Resources Information Center

Raupach, T.; Munscher, C.; Pukrop, T.; Anders, S.; Harendza, S.

2010-01-01

In recent years, increasing attention has been paid to web-based learning although the advantages of computer-aided instruction over traditional teaching formats still need to be confirmed. This study examined whether participation in an online module on the differential diagnosis of dyspnoea impacts on student performance in a multiple choice…

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.

Computer aided diagnosis of diabetic foot using infrared thermography: A review.

PubMed

Adam, Muhammad; Ng, Eddie Y K; Tan, Jen Hong; Heng, Marabelle L; Tong, Jasper W K; Acharya, U Rajendra

2017-12-01

Diabetes mellitus (DM) is a chronic metabolic disorder that requires regular medical care to prevent severe complications. The elevated blood glucose level affects the eyes, blood vessels, nerves, heart, and kidneys after the onset. The affected blood vessels (usually due to atherosclerosis) may lead to insufficient blood circulation particularly in the lower extremities and nerve damage (neuropathy), which can result in serious foot complications. Hence, an early detection and treatment can prevent foot complications such as ulcerations and amputations. Clinicians often assess the diabetic foot for sensory deficits with clinical tools, and the resulting foot severity is often manually evaluated. The infrared thermography is a fast, nonintrusive and non-contact method which allows the visualization of foot plantar temperature distribution. Several studies have proposed infrared thermography-based computer aided diagnosis (CAD) methods for diabetic foot. Among them, the asymmetric temperature analysis method is more superior, as it is easy to implement, and yielded satisfactory results in most of the studies. In this paper, the diabetic foot, its pathophysiology, conventional assessments methods, infrared thermography and the different infrared thermography-based CAD analysis methods are reviewed. Copyright © 2017 Elsevier Ltd. All rights reserved.

Twelve years' experience of computer-aided diagnosis in a district general hospital.

PubMed Central

McAdam, W. A.; Brock, B. M.; Armitage, T.; Davenport, P.; Chan, M.; de Dombal, F. T.

1990-01-01

This paper describes experience in a modern district general hospital with a small desktop system for computer-aided diagnosis of acute abdominal pain, over a 12-year period involving 5512 cases. When compared with a baseline year (1973) in which unaided performance was monitored, during an initial study period (1974-76) the diagnostic accuracy of junior staff rose by between 10 and 15%. This higher performance level was then maintained for a decade (1976-86) despite changes in staff. The perforation rate among appendicitis cases fell from 27% to 12.5%, accompanied by a smaller fall in negative laparotomy rates. The saving in surgical bednights devoted to acute abdominal pain was approximately 15%, and the notional cost of resources saved during the first 6 years of operation was 120,000 pounds. Other hospitals have shown--in the short term--benefits similar to those obtained at Airedale District General Hospital. The long-term benefits of the system at Airedale reinforce the conclusions of the earlier short-term trials that a comparable system should probably be offered to all DGHs in the UK, not as an exercise in 'artificial intelligence' but as an effective continuing stimulus to good clinical practice. PMID:2185682

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.

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.

Computer-aided diagnosis of mammographic masses using geometric verification-based image retrieval

NASA Astrophysics Data System (ADS)

Li, Qingliang; Shi, Weili; Yang, Huamin; Zhang, Huimao; Li, Guoxin; Chen, Tao; Mori, Kensaku; Jiang, Zhengang

2017-03-01

Computer-Aided Diagnosis of masses in mammograms is an important indicator of breast cancer. The use of retrieval systems in breast examination is increasing gradually. In this respect, the method of exploiting the vocabulary tree framework and the inverted file in the mammographic masse retrieval have been proved high accuracy and excellent scalability. However it just considered the features in each image as a visual word and had ignored the spatial configurations of features. It greatly affect the retrieval performance. To overcome this drawback, we introduce the geometric verification method to retrieval in mammographic masses. First of all, we obtain corresponding match features based on the vocabulary tree framework and the inverted file. After that, we grasps the main point of local similarity characteristic of deformations in the local regions by constructing the circle regions of corresponding pairs. Meanwhile we segment the circle to express the geometric relationship of local matches in the area and generate the spatial encoding strictly. Finally we judge whether the matched features are correct or not, based on verifying the all spatial encoding are whether satisfied the geometric consistency. Experiments show the promising results of our approach.

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.

Initial development of a computer-aided diagnosis tool for solitary pulmonary nodules

NASA Astrophysics Data System (ADS)

Catarious, David M., Jr.; Baydush, Alan H.; Floyd, Carey E., Jr.

2001-07-01

This paper describes the development of a computer-aided diagnosis (CAD) tool for solitary pulmonary nodules. This CAD tool is built upon physically meaningful features that were selected because of their relevance to shape and texture. These features included a modified version of the Hotelling statistic (HS), a channelized HS, three measures of fractal properties, two measures of spicularity, and three manually measured shape features. These features were measured from a difficult database consisting of 237 regions of interest (ROIs) extracted from digitized chest radiographs. The center of each 256x256 pixel ROI contained a suspicious lesion which was sent to follow-up by a radiologist and whose nature was later clinically determined. Linear discriminant analysis (LDA) was used to search the feature space via sequential forward search using percentage correct as the performance metric. An optimized feature subset, selected for the highest accuracy, was then fed into a three layer artificial neural network (ANN). The ANN's performance was assessed by receiver operating characteristic (ROC) analysis. A leave-one-out testing/training methodology was employed for the ROC analysis. The performance of this system is competitive with that of three radiologists on the same database.

Computational Methods in Drug Discovery

PubMed Central

Sliwoski, Gregory; Kothiwale, Sandeepkumar; Meiler, Jens

2014-01-01

Computer-aided drug discovery/design methods have played a major role in the development of therapeutically important small molecules for over three decades. These methods are broadly classified as either structure-based or ligand-based methods. Structure-based methods are in principle analogous to high-throughput screening in that both target and ligand structure information is imperative. Structure-based approaches include ligand docking, pharmacophore, and ligand design methods. The article discusses theory behind the most important methods and recent successful applications. Ligand-based methods use only ligand information for predicting activity depending on its similarity/dissimilarity to previously known active ligands. We review widely used ligand-based methods such as ligand-based pharmacophores, molecular descriptors, and quantitative structure-activity relationships. In addition, important tools such as target/ligand data bases, homology modeling, ligand fingerprint methods, etc., necessary for successful implementation of various computer-aided drug discovery/design methods in a drug discovery campaign are discussed. Finally, computational methods for toxicity prediction and optimization for favorable physiologic properties are discussed with successful examples from literature. PMID:24381236

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.

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.

Computer-aided classification of lung nodules on computed tomography images via deep learning technique

PubMed Central

Hua, Kai-Lung; Hsu, Che-Hao; Hidayati, Shintami Chusnul; Cheng, Wen-Huang; Chen, Yu-Jen

2015-01-01

Lung cancer has a poor prognosis when not diagnosed early and unresectable lesions are present. The management of small lung nodules noted on computed tomography scan is controversial due to uncertain tumor characteristics. A conventional computer-aided diagnosis (CAD) scheme requires several image processing and pattern recognition steps to accomplish a quantitative tumor differentiation result. In such an ad hoc image analysis pipeline, every step depends heavily on the performance of the previous step. Accordingly, tuning of classification performance in a conventional CAD scheme is very complicated and arduous. Deep learning techniques, on the other hand, have the intrinsic advantage of an automatic exploitation feature and tuning of performance in a seamless fashion. In this study, we attempted to simplify the image analysis pipeline of conventional CAD with deep learning techniques. Specifically, we introduced models of a deep belief network and a convolutional neural network in the context of nodule classification in computed tomography images. Two baseline methods with feature computing steps were implemented for comparison. The experimental results suggest that deep learning methods could achieve better discriminative results and hold promise in the CAD application domain. PMID:26346558

Computer-aided classification of lung nodules on computed tomography images via deep learning technique.

PubMed

Hua, Kai-Lung; Hsu, Che-Hao; Hidayati, Shintami Chusnul; Cheng, Wen-Huang; Chen, Yu-Jen

2015-01-01

Lung cancer has a poor prognosis when not diagnosed early and unresectable lesions are present. The management of small lung nodules noted on computed tomography scan is controversial due to uncertain tumor characteristics. A conventional computer-aided diagnosis (CAD) scheme requires several image processing and pattern recognition steps to accomplish a quantitative tumor differentiation result. In such an ad hoc image analysis pipeline, every step depends heavily on the performance of the previous step. Accordingly, tuning of classification performance in a conventional CAD scheme is very complicated and arduous. Deep learning techniques, on the other hand, have the intrinsic advantage of an automatic exploitation feature and tuning of performance in a seamless fashion. In this study, we attempted to simplify the image analysis pipeline of conventional CAD with deep learning techniques. Specifically, we introduced models of a deep belief network and a convolutional neural network in the context of nodule classification in computed tomography images. Two baseline methods with feature computing steps were implemented for comparison. The experimental results suggest that deep learning methods could achieve better discriminative results and hold promise in the CAD application domain.

Computed tomography or necropsy diagnosis of multiple bullae and the treatment of pneumothorax in rhesus macaques (Macaca mulatta).

PubMed

Kim, Jong-Min; Han, Sungyoung; Shin, Jun-Seop; Min, Byoung-Hoon; Jeong, Won Young; Lee, Ga Eul; Kim, Min Sun; Kim, Ju Eun; Chung, Hyunwoo; Park, Chung-Gyu

2017-10-01

Pulmonary bullae and pneumothorax have various etiologies in veterinary medicine. We diagnosed multiple pulmonary bullae combined with or without pneumothorax by computed tomography (CT) or necropsy in seven rhesus macaques (Macaca mulatta) imported from China. Two of seven rhesus macaques accompanied by pneumothorax were cured by fixation of ruptured lung through left or right 3rd intercostal thoracotomy. Pneumonyssus simicola, one of the etiologies of pulmonary bullae, was not detected from tracheobronchiolar lavage. To the best of our knowledge, this is the first case report on the CT-aided diagnosis of pulmonary bullae and the successful treatment of combined pneumothorax by thoracotomy in non-human primates (NHPs). © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Clinical Applications of Transcranial Magnetic Stimulation in Pediatric Neurology.

PubMed

Narayana, Shalini; Papanicolaou, Andrew C; McGregor, Amy; Boop, Frederick A; Wheless, James W

2015-08-01

Noninvasive brain stimulation is now an accepted technique that is used as a diagnostic aid and in the treatment of neuropsychiatric disorders in adults, and is being increasingly used in children. In this review, we will discuss the basic principles and safety of one noninvasive brain stimulation method, transcranial magnetic stimulation. Improvements in the spatial accuracy of transcranial magnetic stimulation are described in the context of image-guided transcranial magnetic stimulation. The article describes and provides examples of the current clinical applications of transcranial magnetic stimulation in children as an aid in the diagnosis and treatment of neuropsychiatric disorders and discusses future potential applications. Transcranial magnetic stimulation is a noninvasive tool that is safe for use in children and adolescents for functional mapping and treatment, and for many children it aids in the preoperative evaluation and the risk-benefit decision making. © The Author(s) 2014.

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.

Medical diagnosis and treatment using high-resolution manometry with computer-aided system

NASA Astrophysics Data System (ADS)

Pedowski, Tomasz; Wasiewicz, Piotr; Maciejewski, Ryszard; Wallner, Grzegorz

2010-09-01

Nowadays computers analyze medical data almost in every diagnosis and treatment steps. We develop new technology which gives us better and more precise diagnosis. We chose esophageal high resolution manometry with impedance (HRMI) which has been considered as a "gold standard" test for esophageal motility. HRMI is the next generation of manometry explanation which is more sensitive and accurate to EFT. Examination allows physicians to ger information about esophageal peristalsis, amplitude and duration of the esophageal contraction and liquid/viscous bolus transit time from mouth through stomach. In 2008 we examined 80 patients using "old" EFT manometry and 80 patients in 2009 using high resolution manometry (HRMI). Everybody got manometry, endoscopy and x-ray examination. We asked about symptoms which we correlate and connect with data from EFT and HRMI. We tried to find a good algorithm for this purpose in order to do a simple and helpful tool for physician to make righta diagnosis and treatment decision. Connection between data and symptoms seems to be right and clear, but finding a good algorithm for given data is the main problem.

Artefacts found in computed radiography.

PubMed

Cesar, L J; Schueler, B A; Zink, F E; Daly, T R; Taubel, J P; Jorgenson, L L

2001-02-01

Artefacts on radiographic images are distracting and may compromise accurate diagnosis. Although most artefacts that occur in conventional radiography have become familiar, computed radiography (CR) systems produce artefacts that differ from those found in conventional radiography. We have encountered a variety of artefacts in CR images that were produced from four different models plate reader. These artefacts have been identified and traced to the imaging plate, plate reader, image processing software or laser printer or to operator error. Understanding the potential sources of CR artefacts will aid in identifying and resolving problems quickly and help prevent future occurrences.

Digital model as an alternative to plaster model in assessment of space analysis

PubMed Central

Kumar, A. Anand; Phillip, Abraham; Kumar, Sathesh; Rawat, Anuradha; Priya, Sakthi; Kumaran, V.

2015-01-01

Introduction: Digital three-dimensional models are widely used for orthodontic diagnosis. The purpose of this study was to appraise the accuracy of digital models obtained from computer-aided design/computer-aided manufacturing (CAD/CAM) and cone-beam computed tomography (CBCT) for tooth-width measurements and the Bolton analysis. Materials and Methods: Digital models (CAD/CAM, CBCT) and plaster model were made for each of 50 subjects. Tooth-width measurements on the digital models (CAD/CAM, CBCT) were compared with those on the corresponding plaster models. The anterior and overall Bolton ratios were calculated for each participant and for each method. The paired t-test was applied to determine the validity. Results: Tooth-width measurements, anterior, and overall Bolton ratio of digital models of CAD/CAM and CBCT did not differ significantly from those on the plaster models. Conclusion: Hence, both CBCT and CAD/CAM are trustable and promising technique that can replace plaster models due to its overwhelming advantages. PMID:26538899

Orthodontics: computer-aided diagnosis and treatment planning

NASA Astrophysics Data System (ADS)

Yi, Yaxing; Li, Zhongke; Wei, Suyuan; Deng, Fanglin; Yao, Sen

2000-10-01

The purpose of this article is to introduce the outline of our newly developed computer-aided 3D dental cast analyzing system with laser scanning, and its preliminary clinical applications. The system is composed of a scanning device and a personal computer as a scanning controller and post processor. The scanning device is composed of a laser beam emitter, two sets of linear CCD cameras and a table which is rotatable by two-degree-of-freedom. The rotating is controlled precisely by a personal computer. The dental cast is projected and scanned with a laser beam. Triangulation is applied to determine the location of each point. Generation of 3D graphics of the dental cast takes approximately 40 minutes. About 170,000 sets of X,Y,Z coordinates are store for one dental cast. Besides the conventional linear and angular measurements of the dental cast, we are also able to demonstrate the size of the top surface area of each molar. The advantage of this system is that it facilitates the otherwise complicated and time- consuming mock surgery necessary for treatment planning in orthognathic surgery.

Tracheomalacia and recurrent exacerbations of chronic obstructive pulmonary disease: a case report and review of the literature

PubMed Central

Kerolus, Ghaly; Ikladios, Ossama

2016-01-01

Chronic obstructive pulmonary disease (COPD) is one of the leading causes of disability and death worldwide. COPD exacerbation is usually treated with antibiotics, systemic corticosteroids, and inhaled bronchodilators. We present a case of recurrent COPD exacerbation that was treated repeatedly with standard therapy. Dynamic expiratory computed tomography of the chest was done, which revealed concomitant tracheomalacia. COPD and tracheomalacia may coexist during recurrent exacerbations of COPD, and delayed diagnosis can be associated with severe comorbidities. Ordering the appropriate imaging may aid in the correct diagnosis and facilitate appropriate management. PMID:27987292

Imaging of vascular lesions of the head and neck.

PubMed

Griauzde, Julius; Srinivasan, Ashok

2015-01-01

The diagnosis of vascular lesions of the head and neck should be directed by classifying the lesions as tumors or malformations and by determining their flow characteristics. Location of the lesion is key when differentiating between vascular neoplasms. Ultrasonography is an appropriate screening tool; MRI is often used to confirm the diagnosis. Computed tomography can be used for further characterization of the lesion, particularly when there is bony involvement. In many cases, vascular lesions grow to be extensive. In these cases, percutaneous sclerotherapy or embolization therapy can be employed to aid in surgical resection. Copyright © 2015 Elsevier Inc. 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.

The National Shipbuilding Research Program. 1989 Ship Production Symposium. Paper No. 13: NIDDESC: Meeting the Data Exchange Challenge Through a Cooperative Effort

DTIC Science & Technology

1989-09-01

RESPONSIBLE PERSON a. REPORT unclassified b. ABSTRACT unclassified c . THIS PAGE unclassified Standard Form 298 (Rev. 8-98) Prescribed by ANSI Std Z39-18... Computer Aided Design (CAD) and Manufacturing (CAM) techniques in the marine industry has increased significantly in recent years, With more...somewhat from ship to ship. All of the activities and companies involved have improved this process by utilizing computer tools. For example, many

"Cloud" functions and templates of engineering calculations for nuclear power plants

NASA Astrophysics Data System (ADS)

Ochkov, V. F.; Orlov, K. A.; Ko, Chzho Ko

2014-10-01

The article deals with an important problem of setting up computer-aided design calculations of various circuit configurations and power equipment carried out using the templates and standard computer programs available in the Internet. Information about the developed Internet-based technology for carrying out such calculations using the templates accessible in the Mathcad Prime software package is given. The technology is considered taking as an example the solution of two problems relating to the field of nuclear power engineering.

[Construction and analysis of questionnaires on AIDS cough in traditional Chinese medicine diagnosis and treatment procedures].

PubMed

Zhang, Ying; Xue, Liu-Hua; Chen, Yu-Xia; Huang, Shi-Jing; Pan, Ju-Hua; Wang, Jie

2013-08-01

To norm the behavior of AIDS cough in traditional Chinese medicine diagnosis and treatment and improve the clinical level of cough treatment for HIV/AIDS, and build AIDS cough diagnosis and treatment procedures in traditional Chinese medicine. Combined with clinical practice,to formulate questionnaire on AIDS cough in traditional Chinese medicine diagnosis and treatment by both English and Chinese literature research to expertise consultation and verify the results of the questionnaires on the statistics using the Delphi method. Questionnaire contents consist of overview, pathogeny, diagnosis standard, dialectical medication (phlegm heat resistance pulmonary lung and kidney Yin deficiency lung spleen-deficiency), treating spleen-deficiency (lung), moxibustion treatment and aftercare care and diet and mental, average (2.93-3.00), full mark rate (93.10%-100%) ranks average (9.91-10.67) and (287.50-309.50) of which are the most high value, and the variation coefficient is 0.00, the Kendall coefficient (Kendalls W) is 0.049 which is statistical significance, the questionnaire reliability value of alpha was 0.788. Preliminary standarded concept, etiology and pathogenesis, diagnosis and syndrome differentiation treatment of AIDS cough, basically recognised by the experts in this field, and laid the foundation of traditional Chinese medicine diagnosis and treatment on develop the AIDS cough specifications.

Management and Analysis of Biological and Clinical Data: How Computer Science May Support Biomedical and Clinical Research

NASA Astrophysics Data System (ADS)

Veltri, Pierangelo

The use of computer based solutions for data management in biology and clinical science has contributed to improve life-quality and also to gather research results in shorter time. Indeed, new algorithms and high performance computation have been using in proteomics and genomics studies for curing chronic diseases (e.g., drug designing) as well as supporting clinicians both in diagnosis (e.g., images-based diagnosis) and patient curing (e.g., computer based information analysis on information gathered from patient). In this paper we survey on examples of computer based techniques applied in both biology and clinical contexts. The reported applications are also results of experiences in real case applications at University Medical School of Catanzaro and also part of experiences of the National project Staywell SH 2.0 involving many research centers and companies aiming to study and improve citizen wellness.

Computer-Aided Discovery of Formal Specification Behavioral Requirements and Requirement to Implementation Mappings

DTIC Science & Technology

2014-01-01

the executable SRM is developed according to the specification and marketing documents. Hence, for example, the Vehicles, Car, and Truck classes in...transitions ternary relation: transitions ⊆ states x transitionIDs x states, such as <"Init", "Tr1", " stP "> • A conditions unary relation bound to

An expert support system for breast cancer diagnosis using color wavelet features.

PubMed

Issac Niwas, S; Palanisamy, P; Chibbar, Rajni; Zhang, W J

2012-10-01

Breast cancer diagnosis can be done through the pathologic assessments of breast tissue samples such as core needle biopsy technique. The result of analysis on this sample by pathologist is crucial for breast cancer patient. In this paper, nucleus of tissue samples are investigated after decomposition by means of the Log-Gabor wavelet on HSV color domain and an algorithm is developed to compute the color wavelet features. These features are used for breast cancer diagnosis using Support Vector Machine (SVM) classifier algorithm. The ability of properly trained SVM is to correctly classify patterns and make them particularly suitable for use in an expert system that aids in the diagnosis of cancer tissue samples. The results are compared with other multivariate classifiers such as Naïves Bayes classifier and Artificial Neural Network. The overall accuracy of the proposed method using SVM classifier will be further useful for automation in cancer diagnosis.

Computer-Aided Diagnosis of Solid Breast Lesions Using an Ultrasonic Multi-Feature Analysis Procedure

DTIC Science & Technology

2011-01-01

areas. We quantified morphometric features by geometric and fractal analysis of traced lesion boundaries. Although no single parameter can reliably...These include acoustic descriptors (“echogenicity,” “heterogeneity,” “shadowing”) and morphometric descriptors (“area,” “aspect ratio,” “border...quantitative descriptors; some morphometric features (such as border irregularity) also were particularly effective in lesion classification. Our

Computer-aided diagnosis of prostate cancer using a deep convolutional neural network from multiparametric MRI.

PubMed

Song, Yang; Zhang, Yu-Dong; Yan, Xu; Liu, Hui; Zhou, Minxiong; Hu, Bingwen; Yang, Guang

2018-04-16

Deep learning is the most promising methodology for automatic computer-aided diagnosis of prostate cancer (PCa) with multiparametric MRI (mp-MRI). To develop an automatic approach based on deep convolutional neural network (DCNN) to classify PCa and noncancerous tissues (NC) with mp-MRI. Retrospective. In all, 195 patients with localized PCa were collected from a PROSTATEx database. In total, 159/17/19 patients with 444/48/55 observations (215/23/23 PCas and 229/25/32 NCs) were randomly selected for training/validation/testing, respectively. T 2 -weighted, diffusion-weighted, and apparent diffusion coefficient images. A radiologist manually labeled the regions of interest of PCas and NCs and estimated the Prostate Imaging Reporting and Data System (PI-RADS) scores for each region. Inspired by VGG-Net, we designed a patch-based DCNN model to distinguish between PCa and NCs based on a combination of mp-MRI data. Additionally, an enhanced prediction method was used to improve the prediction accuracy. The performance of DCNN prediction was tested using a receiver operating characteristic (ROC) curve, and the area under the ROC curve (AUC), sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated. Moreover, the predicted result was compared with the PI-RADS score to evaluate its clinical value using decision curve analysis. Two-sided Wilcoxon signed-rank test with statistical significance set at 0.05. The DCNN produced excellent diagnostic performance in distinguishing between PCa and NC for testing datasets with an AUC of 0.944 (95% confidence interval: 0.876-0.994), sensitivity of 87.0%, specificity of 90.6%, PPV of 87.0%, and NPV of 90.6%. The decision curve analysis revealed that the joint model of PI-RADS and DCNN provided additional net benefits compared with the DCNN model and the PI-RADS scheme. The proposed DCNN-based model with enhanced prediction yielded high performance in statistical analysis, suggesting that DCNN could be used in computer-aided diagnosis (CAD) for PCa classification. 3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018. © 2018 International Society for Magnetic Resonance in Medicine.

Examples of Nonconservatism in the CARE 3 Program

NASA Technical Reports Server (NTRS)

Dotson, Kelly J.

1988-01-01

This paper presents parameter regions in the CARE 3 (Computer-Aided Reliability Estimation version 3) computer program where the program overestimates the reliability of a modeled system without warning the user. Five simple models of fault-tolerant computer systems are analyzed; and, the parameter regions where reliability is overestimated are given. The source of the error in the reliability estimates for models which incorporate transient fault occurrences was not readily apparent. However, the source of much of the error for models with permanent and intermittent faults can be attributed to the choice of values for the run-time parameters of the program.

Shin splints--a literature review.

PubMed

Bates, P

1985-09-01

"Shin splints" is not a specific diagnosis. It is merely a descriptive term that describes chronic exertional shin pain in an athlete. The evidence seems clear that shin splint pain has many different causes and this reflects the variation in the anatomy. It would be preferable to describe shin splint pain by location and aetiology, for example, lower medial tibial pain due to periostitis or upper lateral tibial pain due to elevated compartment pressure. This would aid communication between physicians and also direct therapy more accurately.

Self-care of elderly people after the diagnosis of acquired immunodeficiency syndrome.

PubMed

Araujo, Graciela Machado de; Leite, Marinês Tambara; Hildebrandt, Leila Mariza; Oliveski, Cinthia Cristina; Beuter, Margrid

2018-01-01

to characterize the seropositive elderly for the Human Immunodeficiency Virus and Acquired Immunodeficiency Syndrome (HIV/AIDS) in their socio-demographic aspects; to understand how the elderly take care of themselves from the diagnosis of HIV/AIDS. Qualitative, descriptive, exploratory research conducted at a Voluntary Counseling and Testing Center with 10 elderly people receiving treatment for HIV/AIDS. The data were analyzed according to the content analysis. Data show the elderly people's lack of knowledge about HIV/AIDS transmission, the experience of being elderly and having HIV/AIDS, caring for oneself and life after diagnosis of HIV/AIDS in their daily lives. Final considerations: The diagnosis of HIV/AIDS seropositivity in the elderly generates a blend of feelings and fears that lead to food changes, adherence to treatment and the renunciation of daily and social habits, manifested as ways of self-care.

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.

Use of pattern recognition and neural networks for non-metric sex diagnosis from lateral shape of calvarium: an innovative model for computer-aided diagnosis in forensic and physical anthropology.

PubMed

Cavalli, Fabio; Lusnig, Luca; Trentin, Edmondo

2017-05-01

Sex determination on skeletal remains is one of the most important diagnosis in forensic cases and in demographic studies on ancient populations. Our purpose is to realize an automatic operator-independent method to determine the sex from the bone shape and to test an intelligent, automatic pattern recognition system in an anthropological domain. Our multiple-classifier system is based exclusively on the morphological variants of a curve that represents the sagittal profile of the calvarium, modeled via artificial neural networks, and yields an accuracy higher than 80 %. The application of this system to other bone profiles is expected to further improve the sensibility of the methodology.

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.

Accuracy of computer-aided diagnosis based on narrow-band imaging endocytoscopy for diagnosing colorectal lesions: comparison with experts.

PubMed

Misawa, Masashi; Kudo, Shin-Ei; Mori, Yuichi; Takeda, Kenichi; Maeda, Yasuharu; Kataoka, Shinichi; Nakamura, Hiroki; Kudo, Toyoki; Wakamura, Kunihiko; Hayashi, Takemasa; Katagiri, Atsushi; Baba, Toshiyuki; Ishida, Fumio; Inoue, Haruhiro; Nimura, Yukitaka; Oda, Msahiro; Mori, Kensaku

2017-05-01

Real-time characterization of colorectal lesions during colonoscopy is important for reducing medical costs, given that the need for a pathological diagnosis can be omitted if the accuracy of the diagnostic modality is sufficiently high. However, it is sometimes difficult for community-based gastroenterologists to achieve the required level of diagnostic accuracy. In this regard, we developed a computer-aided diagnosis (CAD) system based on endocytoscopy (EC) to evaluate cellular, glandular, and vessel structure atypia in vivo. The purpose of this study was to compare the diagnostic ability and efficacy of this CAD system with the performances of human expert and trainee endoscopists. We developed a CAD system based on EC with narrow-band imaging that allowed microvascular evaluation without dye (ECV-CAD). The CAD algorithm was programmed based on texture analysis and provided a two-class diagnosis of neoplastic or non-neoplastic, with probabilities. We validated the diagnostic ability of the ECV-CAD system using 173 randomly selected EC images (49 non-neoplasms, 124 neoplasms). The images were evaluated by the CAD and by four expert endoscopists and three trainees. The diagnostic accuracies for distinguishing between neoplasms and non-neoplasms were calculated. ECV-CAD had higher overall diagnostic accuracy than trainees (87.8 vs 63.4%; [Formula: see text]), but similar to experts (87.8 vs 84.2%; [Formula: see text]). With regard to high-confidence cases, the overall accuracy of ECV-CAD was also higher than trainees (93.5 vs 71.7%; [Formula: see text]) and comparable to experts (93.5 vs 90.8%; [Formula: see text]). ECV-CAD showed better diagnostic accuracy than trainee endoscopists and was comparable to that of experts. ECV-CAD could thus be a powerful decision-making tool for less-experienced endoscopists.

Computer-aided diagnosis of breast microcalcifications based on dual-tree complex wavelet transform.

PubMed

Jian, Wushuai; Sun, Xueyan; Luo, Shuqian

2012-12-19

Digital mammography is the most reliable imaging modality for breast carcinoma diagnosis and breast micro-calcifications is regarded as one of the most important signs on imaging diagnosis. In this paper, a computer-aided diagnosis (CAD) system is presented for breast micro-calcifications based on dual-tree complex wavelet transform (DT-CWT) to facilitate radiologists like double reading. Firstly, 25 abnormal ROIs were extracted according to the center and diameter of the lesions manually and 25 normal ROIs were selected randomly. Then micro-calcifications were segmented by combining space and frequency domain techniques. We extracted three texture features based on wavelet (Haar, DB4, DT-CWT) transform. Totally 14 descriptors were introduced to define the characteristics of the suspicious micro-calcifications. Principal Component Analysis (PCA) was used to transform these descriptors to a compact and efficient vector expression. Support Vector Machine (SVM) classifier was used to classify potential micro-calcifications. Finally, we used the receiver operating characteristic (ROC) curve and free-response operating characteristic (FROC) curve to evaluate the performance of the CAD system. The results of SVM classifications based on different wavelets shows DT-CWT has a better performance. Compared with other results, DT-CWT method achieved an accuracy of 96% and 100% for the classification of normal and abnormal ROIs, and the classification of benign and malignant micro-calcifications respectively. In FROC analysis, our CAD system for clinical dataset detection achieved a sensitivity of 83.5% at a false positive per image of 1.85. Compared with general wavelets, DT-CWT could describe the features more effectively, and our CAD system had a competitive performance.

Computer-aided diagnosis of breast microcalcifications based on dual-tree complex wavelet transform

PubMed Central

2012-01-01

Background Digital mammography is the most reliable imaging modality for breast carcinoma diagnosis and breast micro-calcifications is regarded as one of the most important signs on imaging diagnosis. In this paper, a computer-aided diagnosis (CAD) system is presented for breast micro-calcifications based on dual-tree complex wavelet transform (DT-CWT) to facilitate radiologists like double reading. Methods Firstly, 25 abnormal ROIs were extracted according to the center and diameter of the lesions manually and 25 normal ROIs were selected randomly. Then micro-calcifications were segmented by combining space and frequency domain techniques. We extracted three texture features based on wavelet (Haar, DB4, DT-CWT) transform. Totally 14 descriptors were introduced to define the characteristics of the suspicious micro-calcifications. Principal Component Analysis (PCA) was used to transform these descriptors to a compact and efficient vector expression. Support Vector Machine (SVM) classifier was used to classify potential micro-calcifications. Finally, we used the receiver operating characteristic (ROC) curve and free-response operating characteristic (FROC) curve to evaluate the performance of the CAD system. Results The results of SVM classifications based on different wavelets shows DT-CWT has a better performance. Compared with other results, DT-CWT method achieved an accuracy of 96% and 100% for the classification of normal and abnormal ROIs, and the classification of benign and malignant micro-calcifications respectively. In FROC analysis, our CAD system for clinical dataset detection achieved a sensitivity of 83.5% at a false positive per image of 1.85. Conclusions Compared with general wavelets, DT-CWT could describe the features more effectively, and our CAD system had a competitive performance. PMID:23253202

The impact of pharmacophore modeling in drug design.

PubMed

Guner, Osman F

2005-07-01

With the reliable use of computer simulations in scientific research, it is possible to achieve significant increases in productivity as well as a reduction in research costs compared with experimental approaches. For example, computer-simulation can substantially enchance productivity by focusing the scientist to better, more informed choices, while also driving the 'fail-early' concept to result in a significant reduction in cost. Pharmacophore modeling is a reliable computer-aided design tool used in the discovery of new classes of compounds for a given therapeutic category. This commentary will briefly review the benefits and applications of this technology in drug discovery and design, and will also highlight its historical evolution. The two most commonly used approaches for pharmacophore model development will be discussed, and several examples of how this technology was successfully applied to identify new potent leads will be provided. The article concludes with a brief outline of the controversial issue of patentability of pharmacophore models.

Multispectral medical image fusion in Contourlet domain for computer based diagnosis of Alzheimer's disease.

PubMed

Bhateja, Vikrant; Moin, Aisha; Srivastava, Anuja; Bao, Le Nguyen; Lay-Ekuakille, Aimé; Le, Dac-Nhuong

2016-07-01

Computer based diagnosis of Alzheimer's disease can be performed by dint of the analysis of the functional and structural changes in the brain. Multispectral image fusion deliberates upon fusion of the complementary information while discarding the surplus information to achieve a solitary image which encloses both spatial and spectral details. This paper presents a Non-Sub-sampled Contourlet Transform (NSCT) based multispectral image fusion model for computer-aided diagnosis of Alzheimer's disease. The proposed fusion methodology involves color transformation of the input multispectral image. The multispectral image in YIQ color space is decomposed using NSCT followed by dimensionality reduction using modified Principal Component Analysis algorithm on the low frequency coefficients. Further, the high frequency coefficients are enhanced using non-linear enhancement function. Two different fusion rules are then applied to the low-pass and high-pass sub-bands: Phase congruency is applied to low frequency coefficients and a combination of directive contrast and normalized Shannon entropy is applied to high frequency coefficients. The superiority of the fusion response is depicted by the comparisons made with the other state-of-the-art fusion approaches (in terms of various fusion metrics).

Multispectral medical image fusion in Contourlet domain for computer based diagnosis of Alzheimer’s disease

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

Bhateja, Vikrant, E-mail: bhateja.vikrant@gmail.com, E-mail: nhuongld@hus.edu.vn; Moin, Aisha; Srivastava, Anuja

Computer based diagnosis of Alzheimer’s disease can be performed by dint of the analysis of the functional and structural changes in the brain. Multispectral image fusion deliberates upon fusion of the complementary information while discarding the surplus information to achieve a solitary image which encloses both spatial and spectral details. This paper presents a Non-Sub-sampled Contourlet Transform (NSCT) based multispectral image fusion model for computer-aided diagnosis of Alzheimer’s disease. The proposed fusion methodology involves color transformation of the input multispectral image. The multispectral image in YIQ color space is decomposed using NSCT followed by dimensionality reduction using modified Principal Componentmore » Analysis algorithm on the low frequency coefficients. Further, the high frequency coefficients are enhanced using non-linear enhancement function. Two different fusion rules are then applied to the low-pass and high-pass sub-bands: Phase congruency is applied to low frequency coefficients and a combination of directive contrast and normalized Shannon entropy is applied to high frequency coefficients. The superiority of the fusion response is depicted by the comparisons made with the other state-of-the-art fusion approaches (in terms of various fusion metrics).« less

[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.

Towards a computer-aided diagnosis system for vocal cord diseases.

PubMed

Verikas, A; Gelzinis, A; Bacauskiene, M; Uloza, V

2006-01-01

The objective of this work is to investigate a possibility of creating a computer-aided decision support system for an automated analysis of vocal cord images aiming to categorize diseases of vocal cords. The problem is treated as a pattern recognition task. To obtain a concise and informative representation of a vocal cord image, colour, texture, and geometrical features are used. The representation is further analyzed by a pattern classifier categorizing the image into healthy, diffuse, and nodular classes. The approach developed was tested on 785 vocal cord images collected at the Department of Otolaryngology, Kaunas University of Medicine, Lithuania. A correct classification rate of over 87% was obtained when categorizing a set of unseen images into the aforementioned three classes. Bearing in mind the high similarity of the decision classes, the results obtained are rather encouraging and the developed tools could be very helpful for assuring objective analysis of the images of laryngeal diseases.

From Phonomecanocardiography to Phonocardiography computer aided

NASA Astrophysics Data System (ADS)

Granados, J.; Tavera, F.; López, G.; Velázquez, J. M.; Hernández, R. T.; López, G. A.

2017-01-01

Due to lack of training doctors to identify many of the disorders in the heart by conventional listening, it is necessary to add an objective and methodological analysis to support this technique. In order to obtain information of the performance of the heart to be able to diagnose heart disease through a simple, cost-effective procedure by means of a data acquisition system, we have obtained Phonocardiograms (PCG), which are images of the sounds emitted by the heart. A program of acoustic, visual and artificial vision recognition was elaborated to interpret them. Based on the results of previous research of cardiologists a code of interpretation of PCG and associated diseases was elaborated. Also a site, within the university campus, of experimental sampling of cardiac data was created. Phonocardiography computer-aided is a viable and low cost procedure which provides additional medical information to make a diagnosis of complex heart diseases. We show some previous results.

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.

Building a medical image processing algorithm verification database

NASA Astrophysics Data System (ADS)

Brown, C. Wayne

2000-06-01

The design of a database containing head Computed Tomography (CT) studies is presented, along with a justification for the database's composition. The database will be used to validate software algorithms that screen normal head CT studies from studies that contain pathology. The database is designed to have the following major properties: (1) a size sufficient for statistical viability, (2) inclusion of both normal (no pathology) and abnormal scans, (3) inclusion of scans due to equipment malfunction, technologist error, and uncooperative patients, (4) inclusion of data sets from multiple scanner manufacturers, (5) inclusion of data sets from different gender and age groups, and (6) three independent diagnosis of each data set. Designed correctly, the database will provide a partial basis for FDA (United States Food and Drug Administration) approval of image processing algorithms for clinical use. Our goal for the database is the proof of viability of screening head CT's for normal anatomy using computer algorithms. To put this work into context, a classification scheme for 'computer aided diagnosis' systems is proposed.

Impact of accelerated progression to AIDS on public health monitoring of late HIV diagnosis.

PubMed

Sabharwal, Charulata J; Sepkowitz, Kent; Mehta, Reshma; Shepard, Colin; Bodach, Sara; Torian, Lucia; Begier, Elizabeth M

2011-03-01

Some patients develop AIDS within a year of HIV infection ("accelerated progression"). Classifying such cases as late HIV diagnosis may lead to inaccurate evaluation of HIV testing efforts. We sought to determine this group's contribution to overall late diagnosis rates. To identify cases of accelerated progression (development of AIDS within 12 months of a negative HIV test), we reviewed published HIV seroconverter cohort studies and used New York City's (NYC) HIV/AIDS surveillance registry. From the literature review, three seroconverter cohort studies revealed that 1.0-3.6% of participants had accelerated progression to AIDS. Applying this frequency estimate to the number of new infections in NYC (4762) for 2006 calculated by the Centers for Diseases Control and Prevention's incidence formula, we estimated that 3.6-13.0% of 1317 NYC HIV cases who are diagnosed with AIDS within 12 months of HIV diagnosis are accelerated progressors, not persons HIV infected for many years who did not test and present with AIDS (i.e., delayed diagnosis). In addition, our analysis of the 2006 NYC surveillance registry confirmed the occurrence of accelerated progression in a population-based setting; 67 accelerated progressors were reported and 9 (13%) could be confirmed through follow-up medical record review. With increased HIV testing initiatives, the irreducible proportion of AIDS cases with accelerated progression must be considered when interpreting late diagnosis data.

Semi-automated detection of anterior cruciate ligament injury from MRI.

PubMed

Štajduhar, Ivan; Mamula, Mihaela; Miletić, Damir; Ünal, Gözde

2017-03-01

A radiologist's work in detecting various injuries or pathologies from radiological scans can be tiresome, time consuming and prone to errors. The field of computer-aided diagnosis aims to reduce these factors by introducing a level of automation in the process. In this paper, we deal with the problem of detecting the presence of anterior cruciate ligament (ACL) injury in a human knee. We examine the possibility of aiding the diagnosis process by building a decision-support model for detecting the presence of milder ACL injuries (not requiring operative treatment) and complete ACL ruptures (requiring operative treatment) from sagittal plane magnetic resonance (MR) volumes of human knees. Histogram of oriented gradient (HOG) descriptors and gist descriptors are extracted from manually selected rectangular regions of interest enveloping the wider cruciate ligament area. Performance of two machine-learning models is explored, coupled with both feature extraction methods: support vector machine (SVM) and random forests model. Model generalisation properties were determined by performing multiple iterations of stratified 10-fold cross validation whilst observing the area under the curve (AUC) score. Sagittal plane knee joint MR data was retrospectively gathered at the Clinical Hospital Centre Rijeka, Croatia, from 2007 until 2014. Type of ACL injury was established in a double-blind fashion by comparing the retrospectively set diagnosis against the prospective opinion of another radiologist. After clean up, the resulting dataset consisted of 917 usable labelled exam sequences of left or right knees. Experimental results suggest that a linear-kernel SVM learned from HOG descriptors has the best generalisation properties among the experimental models compared, having an area under the curve of 0.894 for the injury-detection problem and 0.943 for the complete-rupture-detection problem. Although the problem of performing semi-automated ACL-injury diagnosis by observing knee-joint MR volumes alone is a difficult one, experimental results suggest potential clinical application of computer-aided decision making, both for detecting milder injuries and detecting complete ruptures. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

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.

An Efficient Computational Framework for the Analysis of Whole Slide Images: Application to Follicular Lymphoma Immunohistochemistry

PubMed Central

Samsi, Siddharth; Krishnamurthy, Ashok K.; Gurcan, Metin N.

2012-01-01

Follicular Lymphoma (FL) is one of the most common non-Hodgkin Lymphoma in the United States. Diagnosis and grading of FL is based on the review of histopathological tissue sections under a microscope and is influenced by human factors such as fatigue and reader bias. Computer-aided image analysis tools can help improve the accuracy of diagnosis and grading and act as another tool at the pathologist’s disposal. Our group has been developing algorithms for identifying follicles in immunohistochemical images. These algorithms have been tested and validated on small images extracted from whole slide images. However, the use of these algorithms for analyzing the entire whole slide image requires significant changes to the processing methodology since the images are relatively large (on the order of 100k × 100k pixels). In this paper we discuss the challenges involved in analyzing whole slide images and propose potential computational methodologies for addressing these challenges. We discuss the use of parallel computing tools on commodity clusters and compare performance of the serial and parallel implementations of our approach. PMID:22962572

A fuzzy system for helping medical diagnosis of malformations of cortical development.

PubMed

Alayón, Silvia; Robertson, Richard; Warfield, Simon K; Ruiz-Alzola, Juan

2007-06-01

Malformations of the cerebral cortex are recognized as a common cause of developmental delay, neurological deficits, mental retardation and epilepsy. Currently, the diagnosis of cerebral cortical malformations is based on a subjective interpretation of neuroimaging characteristics of the cerebral gray matter and underlying white matter. There is no automated system for aiding the observer in making the diagnosis of a cortical malformation. In this paper a fuzzy rule-based system is proposed as a solution for this problem. The system collects the available expert knowledge about cortical malformations and assists the medical observer in arriving at a correct diagnosis. Moreover, the system allows the study of the influence of the various factors that take part in the decision. The evaluation of the system has been carried out by comparing the automated diagnostic algorithm with known case examples of various malformations due to abnormal cortical organization. An exhaustive evaluation of the system by comparison with published cases and a ROC analysis is presented in the paper.

A Fuzzy System for Helping Medical Diagnosis of Malformations of Cortical Development

PubMed Central

Alayón, Silvia; Robertson, Richard; Warfield, Simon K.; Ruiz-Alzola, Juan

2007-01-01

Malformations of the cerebral cortex are recognized as a common cause of developmental delay, neurological deficits, mental retardation and epilepsy. Currently, the diagnosis of cerebral cortical malformations is based on a subjective interpretation of neuroimaging characteristics of the cerebral gray matter and underlying white matter. There is no automated system for aiding the observer in making the diagnosis of a cortical malformation. In this paper a fuzzy rule-based system is proposed as a solution for this problem. The system collects the available expert knowledge about cortical malformations and assists the medical observer in arriving at a correct diagnosis. Moreover, the system allows the study of the influence of the various factors that take part in the decision. The evaluation of the system has been carried out by comparing the automated diagnostic algorithm with known case examples of various malformations due to abnormal cortical organization. An exhaustive evaluation of the system by comparison with published cases and a ROC analysis is presented in the paper. PMID:17197247

Computer-aided Classification of Mammographic Masses Using Visually Sensitive Image Features

PubMed Central

Wang, Yunzhi; Aghaei, Faranak; Zarafshani, Ali; Qiu, Yuchen; Qian, Wei; Zheng, Bin

2017-01-01

Purpose To develop a new computer-aided diagnosis (CAD) scheme that computes visually sensitive image features routinely used by radiologists to develop a machine learning classifier and distinguish between the malignant and benign breast masses detected from digital mammograms. Methods An image dataset including 301 breast masses was retrospectively selected. From each segmented mass region, we computed image features that mimic five categories of visually sensitive features routinely used by radiologists in reading mammograms. We then selected five optimal features in the five feature categories and applied logistic regression models for classification. A new CAD interface was also designed to show lesion segmentation, computed feature values and classification score. Results Areas under ROC curves (AUC) were 0.786±0.026 and 0.758±0.027 when to classify mass regions depicting on two view images, respectively. By fusing classification scores computed from two regions, AUC increased to 0.806±0.025. Conclusion This study demonstrated a new approach to develop CAD scheme based on 5 visually sensitive image features. Combining with a “visual aid” interface, CAD results may be much more easily explainable to the observers and increase their confidence to consider CAD generated classification results than using other conventional CAD approaches, which involve many complicated and visually insensitive texture features. PMID:27911353

Computer Aided Teaching in Photogrammetry, Remote Sensing, and Geomatics - A Status Review

NASA Astrophysics Data System (ADS)

Vyas, A.; Koenig, G.

2014-04-01

Education and training play vital role in the utilization of the technology. Shared and coordinated knowledge that geospatial technology and GIS deliver provides a deeper understanding of our present and will also help to better understand our future development. But it is not enough to explain new technological developments during congresses or workshops; it is also necessary to promote these new ideas and to distribute the knowledge by applying new learning strategies. This paper will review the status of computer aided teaching advances during the last decade, with a particular emphasis on photogrammetry, remote sensing, and geomatics. Some best practise examples will be presented featuring prominently recent Massive Open Online Courses (MOOCs) related to our fields. The consideration of mainly free online learning resources will include a commentary on quality and perceived effectiveness.

HIV / AIDS: Symptoms, Diagnosis, Prevention and Treatment

MedlinePlus

Skip Navigation Bar Home Current Issue Past Issues HIV / AIDS HIV / AIDS: Symptoms , Diagnosis, Prevention and Treatment Past Issues / ... Most people who have become recently infected with HIV will not have any symptoms. They may, however, ...

Alternative Teaching Aids, or Why We Can Do Without the New Technology in Political Education.

ERIC Educational Resources Information Center

Langeveld, Willem

Social studies educators should refrain from using computer-assisted instruction as much as possible; instead, they should create a program that reveals the hard facts of a computerized society and its dangers to civil liberties and human dignity. Past examples of the standardizing effects of technology reach as far back as the printing press.…

A series of PDB-related databanks for everyday needs.

PubMed

Touw, Wouter G; Baakman, Coos; Black, Jon; te Beek, Tim A H; Krieger, E; Joosten, Robbie P; Vriend, Gert

2015-01-01

We present a series of databanks (http://swift.cmbi.ru.nl/gv/facilities/) that hold information that is computationally derived from Protein Data Bank (PDB) entries and that might augment macromolecular structure studies. These derived databanks run parallel to the PDB, i.e. they have one entry per PDB entry. Several of the well-established databanks such as HSSP, PDBREPORT and PDB_REDO have been updated and/or improved. The software that creates the DSSP databank, for example, has been rewritten to better cope with π-helices. A large number of databanks have been added to aid computational structural biology; some examples are lists of residues that make crystal contacts, lists of contacting residues using a series of contact definitions or lists of residue accessibilities. PDB files are not the optimal presentation of the underlying data for many studies. We therefore made a series of databanks that hold PDB files in an easier to use or more consistent representation. The BDB databank holds X-ray PDB files with consistently represented B-factors. We also added several visualization tools to aid the users of our databanks. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

3D reconstruction of the optic nerve head using stereo fundus images for computer-aided diagnosis of glaucoma

NASA Astrophysics Data System (ADS)

Tang, Li; Kwon, Young H.; Alward, Wallace L. M.; Greenlee, Emily C.; Lee, Kyungmoo; Garvin, Mona K.; Abràmoff, Michael D.

2010-03-01

The shape of the optic nerve head (ONH) is reconstructed automatically using stereo fundus color images by a robust stereo matching algorithm, which is needed for a quantitative estimate of the amount of nerve fiber loss for patients with glaucoma. Compared to natural scene stereo, fundus images are noisy because of the limits on illumination conditions and imperfections of the optics of the eye, posing challenges to conventional stereo matching approaches. In this paper, multi scale pixel feature vectors which are robust to noise are formulated using a combination of both pixel intensity and gradient features in scale space. Feature vectors associated with potential correspondences are compared with a disparity based matching score. The deep structures of the optic disc are reconstructed with a stack of disparity estimates in scale space. Optical coherence tomography (OCT) data was collected at the same time, and depth information from 3D segmentation was registered with the stereo fundus images to provide the ground truth for performance evaluation. In experiments, the proposed algorithm produces estimates for the shape of the ONH that are close to the OCT based shape, and it shows great potential to help computer-aided diagnosis of glaucoma and other related retinal diseases.

Computer-aided diagnosis with radiogenomics: analysis of the relationship between genotype and morphological changes of the brain magnetic resonance images.

PubMed

Kai, Chiharu; Uchiyama, Yoshikazu; Shiraishi, Junji; Fujita, Hiroshi; Doi, Kunio

2018-05-10

In the post-genome era, a novel research field, 'radiomics' has been developed to offer a new viewpoint for the use of genotypes in radiology and medicine research which have traditionally focused on the analysis of imaging phenotypes. The present study analyzed brain morphological changes related to the individual's genotype. Our data consisted of magnetic resonance (MR) images of patients with mild cognitive impairment (MCI) and Alzheimer's disease (AD), as well as their apolipoprotein E (APOE) genotypes. First, statistical parametric mapping (SPM) 12 was used for three-dimensional anatomical standardization of the brain MR images. A total of 30 normal images were used to create a standard normal brain image. Z-score maps were generated to identify the differences between an abnormal image and the standard normal brain. Our experimental results revealed that cerebral atrophies, depending on genotypes, can occur in different locations and that morphological changes may differ between MCI and AD. Using a classifier to characterize cerebral atrophies related to an individual's genotype, we developed a computer-aided diagnosis (CAD) scheme to identify the disease. For the early detection of cerebral diseases, a screening system using MR images, called Brain Check-up, is widely performed in Japan. Therefore, our proposed CAD scheme would be used in Brain Check-up.

Segmentation of White Blood Cells From Microscopic Images Using a Novel Combination of K-Means Clustering and Modified Watershed Algorithm.

PubMed

Ghane, Narjes; Vard, Alireza; Talebi, Ardeshir; Nematollahy, Pardis

2017-01-01

Recognition of white blood cells (WBCs) is the first step to diagnose some particular diseases such as acquired immune deficiency syndrome, leukemia, and other blood-related diseases that are usually done by pathologists using an optical microscope. This process is time-consuming, extremely tedious, and expensive and needs experienced experts in this field. Thus, a computer-aided diagnosis system that assists pathologists in the diagnostic process can be so effective. Segmentation of WBCs is usually a first step in developing a computer-aided diagnosis system. The main purpose of this paper is to segment WBCs from microscopic images. For this purpose, we present a novel combination of thresholding, k-means clustering, and modified watershed algorithms in three stages including (1) segmentation of WBCs from a microscopic image, (2) extraction of nuclei from cell's image, and (3) separation of overlapping cells and nuclei. The evaluation results of the proposed method show that similarity measures, precision, and sensitivity respectively were 92.07, 96.07, and 94.30% for nucleus segmentation and 92.93, 97.41, and 93.78% for cell segmentation. In addition, statistical analysis presents high similarity between manual segmentation and the results obtained by the proposed method.

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).

Computer-aided diagnosis of retinopathy in retinal fundus images of preterm infants via quantification of vascular tortuosity

PubMed Central

Oloumi, Faraz; Rangayyan, Rangaraj M.; Ells, Anna L.

2016-01-01

Abstract. Retinopathy of prematurity (ROP), a disorder of the retina occurring in preterm infants, is the leading cause of preventable childhood blindness. An active phase of ROP that requires treatment is associated with the presence of plus disease, which is diagnosed clinically in a qualitative manner by visual assessment of the existence of a certain level of increase in the thickness and tortuosity of retinal vessels. The present study performs computer-aided diagnosis (CAD) of plus disease via quantitative measurement of tortuosity in retinal fundus images of preterm infants. Digital image processing techniques were developed for the detection of retinal vessels and measurement of their tortuosity. The total lengths of abnormally tortuous vessels in each quadrant and the entire image were then computed. A minimum-length diagnostic-decision-making criterion was developed to assess the diagnostic sensitivity and specificity of the values obtained. The area (Az) under the receiver operating characteristic curve was used to assess the overall diagnostic accuracy of the methods. Using a set of 19 retinal fundus images of preterm infants with plus disease and 91 without plus disease, the proposed methods provided an overall diagnostic accuracy of Az=0.98. Using the total length of all abnormally tortuous vessel segments in an image, our techniques are capable of CAD of plus disease with high accuracy without the need for manual selection of vessels to analyze. The proposed methods may be used in a clinical or teleophthalmological setting. PMID:28018938

Efficient and Extensible Quasi-Explicit Modular Nonlinear Multiscale Battery Model: GH-MSMD

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

Kim, Gi-Heon; Smith, Kandler; Lawrence-Simon, Jake

Complex physics and long computation time hinder the adoption of computer aided engineering models in the design of large-format battery cells and systems. A modular, efficient battery simulation model -- the multiscale multidomain (MSMD) model -- was previously introduced to aid the scale-up of Li-ion material and electrode designs to complete cell and pack designs, capturing electrochemical interplay with 3-D electronic current pathways and thermal response. Here, this paper enhances the computational efficiency of the MSMD model using a separation of time-scales principle to decompose model field variables. The decomposition provides a quasi-explicit linkage between the multiple length-scale domains andmore » thus reduces time-consuming nested iteration when solving model equations across multiple domains. In addition to particle-, electrode- and cell-length scales treated in the previous work, the present formulation extends to bus bar- and multi-cell module-length scales. We provide example simulations for several variants of GH electrode-domain models.« less

Efficient and Extensible Quasi-Explicit Modular Nonlinear Multiscale Battery Model: GH-MSMD

DOE PAGES

Kim, Gi-Heon; Smith, Kandler; Lawrence-Simon, Jake; ...

2017-03-24

Complex physics and long computation time hinder the adoption of computer aided engineering models in the design of large-format battery cells and systems. A modular, efficient battery simulation model -- the multiscale multidomain (MSMD) model -- was previously introduced to aid the scale-up of Li-ion material and electrode designs to complete cell and pack designs, capturing electrochemical interplay with 3-D electronic current pathways and thermal response. Here, this paper enhances the computational efficiency of the MSMD model using a separation of time-scales principle to decompose model field variables. The decomposition provides a quasi-explicit linkage between the multiple length-scale domains andmore » thus reduces time-consuming nested iteration when solving model equations across multiple domains. In addition to particle-, electrode- and cell-length scales treated in the previous work, the present formulation extends to bus bar- and multi-cell module-length scales. We provide example simulations for several variants of GH electrode-domain models.« less

Paper simulation techniques in user requirements analysis for interactive computer systems

NASA Technical Reports Server (NTRS)

Ramsey, H. R.; Atwood, M. E.; Willoughby, J. K.

1979-01-01

This paper describes the use of a technique called 'paper simulation' in the analysis of user requirements for interactive computer systems. In a paper simulation, the user solves problems with the aid of a 'computer', as in normal man-in-the-loop simulation. In this procedure, though, the computer does not exist, but is simulated by the experimenters. This allows simulated problem solving early in the design effort, and allows the properties and degree of structure of the system and its dialogue to be varied. The technique, and a method of analyzing the results, are illustrated with examples from a recent paper simulation exercise involving a Space Shuttle flight design task

A paradigm shift in orthognathic surgery? A comparison of navigation, computer-aided designed/computer-aided manufactured splints, and "classic" intermaxillary splints to surgical transfer of virtual orthognathic planning.

PubMed

Zinser, Max J; Sailer, Hermann F; Ritter, Lutz; Braumann, Bert; Maegele, Marc; Zöller, Joachim E

2013-12-01

Advances in computers and imaging have permitted the adoption of 3-dimensional (3D) virtual planning protocols in orthognathic surgery, which may allow a paradigm shift when the virtual planning can be transferred properly. The purpose of this investigation was to compare the versatility and precision of innovative computer-aided designed and computer-aided manufactured (CAD/CAM) surgical splints, intraoperative navigation, and "classic" intermaxillary occlusal splints for surgical transfer of virtual orthognathic planning. The protocols consisted of maxillofacial imaging, diagnosis, virtual orthognathic planning, and surgical planning transfer using newly designed CAD/CAM splints (approach A), navigation (approach B), and intermaxillary occlusal splints (approach C). In this prospective observational study, all patients underwent bimaxillary osteotomy. Eight patients were treated using approach A, 10 using approach B, and 12 using approach C. These techniques were evaluated by applying 13 hard and 7 soft tissue parameters to compare the virtual orthognathic planning (T0) with the postoperative result (T1) using 3D cephalometry and image fusion (ΔT1 vs T0). The highest precision (ΔT1 vs T0) for the maxillary planning transfer was observed with CAD/CAM splints (<0.23 mm; P > .05) followed by surgical "waferless" navigation (<0.61 mm, P < .05) and classic intermaxillary occlusal splints (<1.1 mm; P < .05). Only the innovative CAD/CAM splints kept the condyles in their central position in the temporomandibular joint. However, no technique enables a precise prediction of the mandible and soft tissue. CAD/CAM splints and surgical navigation provide a reliable, innovative, and precise approach for the transfer of virtual orthognathic planning. These computer-assisted techniques may offer an alternate approach to the use of classic intermaxillary occlusal splints. Copyright © 2013 American Association of Oral and Maxillofacial Surgeons. Published by Elsevier Inc. All rights reserved.

Faultfinder: A diagnostic expert system with graceful degradation for onboard aircraft applications

NASA Technical Reports Server (NTRS)

Abbott, Kathy H.; Schutte, Paul C.; Palmer, Michael T.; Ricks, Wendell R.

1988-01-01

A research effort was conducted to explore the application of artificial intelligence technology to automation of fault monitoring and diagnosis as an aid to the flight crew. Human diagnostic reasoning was analyzed and actual accident and incident cases were reconstructed. Based on this analysis and reconstruction, diagnostic concepts were conceived and implemented for an aircraft's engine and hydraulic subsystems. These concepts are embedded within a multistage approach to diagnosis that reasons about time-based, causal, and qualitative information, and enables a certain amount of graceful degradation. The diagnostic concepts are implemented in a computer program called Faultfinder that serves as a research prototype.

PyEEG: an open source Python module for EEG/MEG feature extraction.

PubMed

Bao, Forrest Sheng; Liu, Xin; Zhang, Christina

2011-01-01

Computer-aided diagnosis of neural diseases from EEG signals (or other physiological signals that can be treated as time series, e.g., MEG) is an emerging field that has gained much attention in past years. Extracting features is a key component in the analysis of EEG signals. In our previous works, we have implemented many EEG feature extraction functions in the Python programming language. As Python is gaining more ground in scientific computing, an open source Python module for extracting EEG features has the potential to save much time for computational neuroscientists. In this paper, we introduce PyEEG, an open source Python module for EEG feature extraction.

[Automated identification, interpretation and classification of focal changes in the lungs on the images obtained at computed tomography for lung cancer screening].

PubMed

Barchuk, A A; Podolsky, M D; Tarakanov, S A; Kotsyuba, I Yu; Gaidukov, V S; Kuznetsov, V I; Merabishvili, V M; Barchuk, A S; Levchenko, E V; Filochkina, A V; Arseniev, A I

2015-01-01

This review article analyzes data of literature devoted to the description, interpretation and classification of focal (nodal) changes in the lungs detected by computed tomography of the chest cavity. There are discussed possible criteria for determining the most likely of their character--primary and metastatic tumor processes, inflammation, scarring, and autoimmune changes, tuberculosis and others. Identification of the most characteristic, reliable and statistically significant evidences of a variety of pathological processes in the lungs including the use of modern computer-aided detection and diagnosis of sites will optimize the diagnostic measures and ensure processing of a large volume of medical data in a short time.

Fifty years of computer analysis in chest imaging: rule-based, machine learning, deep learning.

PubMed

van Ginneken, Bram

2017-03-01

Half a century ago, the term "computer-aided diagnosis" (CAD) was introduced in the scientific literature. Pulmonary imaging, with chest radiography and computed tomography, has always been one of the focus areas in this field. In this study, I describe how machine learning became the dominant technology for tackling CAD in the lungs, generally producing better results than do classical rule-based approaches, and how the field is now rapidly changing: in the last few years, we have seen how even better results can be obtained with deep learning. The key differences among rule-based processing, machine learning, and deep learning are summarized and illustrated for various applications of CAD in the chest.

UNSEDATED COMPUTED TOMOGRAPHY FOR DIAGNOSIS OF PELVIC CANAL OBSTRUCTION IN A LEOPARD GECKO (EUBLEPHARIS MACULARIUS).

PubMed

DeCourcy, Kelly; Hostnik, Eric T; Lorbach, Josh; Knoblaugh, Sue

2016-12-01

An adult leopard gecko ( Eublepharis macularius ) presented for lethargy, hyporexia, weight loss, decreased passage of waste, and a palpable caudal coelomic mass. Computed tomography showed a heterogeneous hyperattenuating (∼143 Hounsfield units) structure within the right caudal coelom. The distal colon-coprodeum lumen or urinary bladder was hypothesized as the most likely location for the heterogeneous structure. Medical support consisted of warm water and lubricant enema, as well as a heated environment. Medical intervention aided the passage of a plug comprised centrally of cholesterol and urates with peripheral stratified layers of fibrin, macrophages, heterophils, and bacteria. Within 24 hr, a follow-up computed tomography scan showed resolution of the pelvic canal plug.

PyEEG: An Open Source Python Module for EEG/MEG Feature Extraction

PubMed Central

Bao, Forrest Sheng; Liu, Xin; Zhang, Christina

2011-01-01

Computer-aided diagnosis of neural diseases from EEG signals (or other physiological signals that can be treated as time series, e.g., MEG) is an emerging field that has gained much attention in past years. Extracting features is a key component in the analysis of EEG signals. In our previous works, we have implemented many EEG feature extraction functions in the Python programming language. As Python is gaining more ground in scientific computing, an open source Python module for extracting EEG features has the potential to save much time for computational neuroscientists. In this paper, we introduce PyEEG, an open source Python module for EEG feature extraction. PMID:21512582

Computer-aided diagnosis with potential application to rapid detection of disease outbreaks.

PubMed

Burr, Tom; Koster, Frederick; Picard, Rick; Forslund, Dave; Wokoun, Doug; Joyce, Ed; Brillman, Judith; Froman, Phil; Lee, Jack

2007-04-15

Our objectives are to quickly interpret symptoms of emergency patients to identify likely syndromes and to improve population-wide disease outbreak detection. We constructed a database of 248 syndromes, each syndrome having an estimated probability of producing any of 85 symptoms, with some two-way, three-way, and five-way probabilities reflecting correlations among symptoms. Using these multi-way probabilities in conjunction with an iterative proportional fitting algorithm allows estimation of full conditional probabilities. Combining these conditional probabilities with misdiagnosis error rates and incidence rates via Bayes theorem, the probability of each syndrome is estimated. We tested a prototype of computer-aided differential diagnosis (CADDY) on simulated data and on more than 100 real cases, including West Nile Virus, Q fever, SARS, anthrax, plague, tularaemia and toxic shock cases. We conclude that: (1) it is important to determine whether the unrecorded positive status of a symptom means that the status is negative or that the status is unknown; (2) inclusion of misdiagnosis error rates produces more realistic results; (3) the naive Bayes classifier, which assumes all symptoms behave independently, is slightly outperformed by CADDY, which includes available multi-symptom information on correlations; as more information regarding symptom correlations becomes available, the advantage of CADDY over the naive Bayes classifier should increase; (4) overlooking low-probability, high-consequence events is less likely if the standard output summary is augmented with a list of rare syndromes that are consistent with observed symptoms, and (5) accumulating patient-level probabilities across a larger population can aid in biosurveillance for disease outbreaks. c 2007 John Wiley & Sons, Ltd.

Interactive computer graphics - Why's, wherefore's and examples

NASA Technical Reports Server (NTRS)

Gregory, T. J.; Carmichael, R. L.

1983-01-01

The benefits of using computer graphics in design are briefly reviewed. It is shown that computer graphics substantially aids productivity by permitting errors in design to be found immediately and by greatly reducing the cost of fixing the errors and the cost of redoing the process. The possibilities offered by computer-generated displays in terms of information content are emphasized, along with the form in which the information is transferred. The human being is ideally and naturally suited to dealing with information in picture format, and the content rate in communication with pictures is several orders of magnitude greater than with words or even graphs. Since science and engineering involve communicating ideas, concepts, and information, the benefits of computer graphics cannot be overestimated.

Computer-Aided Diagnosis Based on Convolutional Neural Network System for Colorectal Polyp Classification: Preliminary Experience.

PubMed

Komeda, Yoriaki; Handa, Hisashi; Watanabe, Tomohiro; Nomura, Takanobu; Kitahashi, Misaki; Sakurai, Toshiharu; Okamoto, Ayana; Minami, Tomohiro; Kono, Masashi; Arizumi, Tadaaki; Takenaka, Mamoru; Hagiwara, Satoru; Matsui, Shigenaga; Nishida, Naoshi; Kashida, Hiroshi; Kudo, Masatoshi

2017-01-01

Computer-aided diagnosis (CAD) is becoming a next-generation tool for the diagnosis of human disease. CAD for colon polyps has been suggested as a particularly useful tool for trainee colonoscopists, as the use of a CAD system avoids the complications associated with endoscopic resections. In addition to conventional CAD, a convolutional neural network (CNN) system utilizing artificial intelligence (AI) has been developing rapidly over the past 5 years. We attempted to generate a unique CNN-CAD system with an AI function that studied endoscopic images extracted from movies obtained with colonoscopes used in routine examinations. Here, we report our preliminary results of this novel CNN-CAD system for the diagnosis of colon polyps. A total of 1,200 images from cases of colonoscopy performed between January 2010 and December 2016 at Kindai University Hospital were used. These images were extracted from the video of actual endoscopic examinations. Additional video images from 10 cases of unlearned processes were retrospectively assessed in a pilot study. They were simply diagnosed as either an adenomatous or nonadenomatous polyp. The number of images used by AI to learn to distinguish adenomatous from nonadenomatous was 1,200:600. These images were extracted from the videos of actual endoscopic examinations. The size of each image was adjusted to 256 × 256 pixels. A 10-hold cross-validation was carried out. The accuracy of the 10-hold cross-validation is 0.751, where the accuracy is the ratio of the number of correct answers over the number of all the answers produced by the CNN. The decisions by the CNN were correct in 7 of 10 cases. A CNN-CAD system using routine colonoscopy might be useful for the rapid diagnosis of colorectal polyp classification. Further prospective studies in an in vivo setting are required to confirm the effectiveness of a CNN-CAD system in routine colonoscopy. © 2017 S. Karger AG, Basel.

Computer-aided-diagnosis (CAD) for colposcopy

NASA Astrophysics Data System (ADS)

Lange, Holger; Ferris, Daron G.

2005-04-01

Uterine cervical cancer is the second most common cancer among women worldwide. Colposcopy is a diagnostic method, whereby a physician (colposcopist) visually inspects the lower genital tract (cervix, vulva and vagina), with special emphasis on the subjective appearance of metaplastic epithelium comprising the transformation zone on the cervix. Cervical cancer precursor lesions and invasive cancer exhibit certain distinctly abnormal morphologic features. Lesion characteristics such as margin; color or opacity; blood vessel caliber, intercapillary spacing and distribution; and contour are considered by colposcopists to derive a clinical diagnosis. Clinicians and academia have suggested and shown proof of concept that automated image analysis of cervical imagery can be used for cervical cancer screening and diagnosis, having the potential to have a direct impact on improving women"s health care and reducing associated costs. STI Medical Systems is developing a Computer-Aided-Diagnosis (CAD) system for colposcopy -- ColpoCAD. At the heart of ColpoCAD is a complex multi-sensor, multi-data and multi-feature image analysis system. A functional description is presented of the envisioned ColpoCAD system, broken down into: Modality Data Management System, Image Enhancement, Feature Extraction, Reference Database, and Diagnosis and directed Biopsies. The system design and development process of the image analysis system is outlined. The system design provides a modular and open architecture built on feature based processing. The core feature set includes the visual features used by colposcopists. This feature set can be extended to include new features introduced by new instrument technologies, like fluorescence and impedance, and any other plausible feature that can be extracted from the cervical data. Preliminary results of our research on detecting the three most important features: blood vessel structures, acetowhite regions and lesion margins are shown. As this is a new and very complex field in medical image processing, the hope is that this paper can provide a framework and basis to encourage and facilitate collaboration and discussion between industry, academia, and medical practitioners.

Role of Gist and PHOG Features in Computer-Aided Diagnosis of Tuberculosis without Segmentation

PubMed Central

Chauhan, Arun; Chauhan, Devesh; Rout, Chittaranjan

2014-01-01

Purpose Effective diagnosis of tuberculosis (TB) relies on accurate interpretation of radiological patterns found in a chest radiograph (CXR). Lack of skilled radiologists and other resources, especially in developing countries, hinders its efficient diagnosis. Computer-aided diagnosis (CAD) methods provide second opinion to the radiologists for their findings and thereby assist in better diagnosis of cancer and other diseases including TB. However, existing CAD methods for TB are based on the extraction of textural features from manually or semi-automatically segmented CXRs. These methods are prone to errors and cannot be implemented in X-ray machines for automated classification. Methods Gabor, Gist, histogram of oriented gradients (HOG), and pyramid histogram of oriented gradients (PHOG) features extracted from the whole image can be implemented into existing X-ray machines to discriminate between TB and non-TB CXRs in an automated manner. Localized features were extracted for the above methods using various parameters, such as frequency range, blocks and region of interest. The performance of these features was evaluated against textural features. Two digital CXR image datasets (8-bit DA and 14-bit DB) were used for evaluating the performance of these features. Results Gist (accuracy 94.2% for DA, 86.0% for DB) and PHOG (accuracy 92.3% for DA, 92.0% for DB) features provided better results for both the datasets. These features were implemented to develop a MATLAB toolbox, TB-Xpredict, which is freely available for academic use at http://sourceforge.net/projects/tbxpredict/. This toolbox provides both automated training and prediction modules and does not require expertise in image processing for operation. Conclusion Since the features used in TB-Xpredict do not require segmentation, the toolbox can easily be implemented in X-ray machines. This toolbox can effectively be used for the mass screening of TB in high-burden areas with improved efficiency. PMID:25390291

Accurate, efficient, and (iso)geometrically flexible collocation methods for phase-field models

NASA Astrophysics Data System (ADS)

Gomez, Hector; Reali, Alessandro; Sangalli, Giancarlo

2014-04-01

We propose new collocation methods for phase-field models. Our algorithms are based on isogeometric analysis, a new technology that makes use of functions from computational geometry, such as, for example, Non-Uniform Rational B-Splines (NURBS). NURBS exhibit excellent approximability and controllable global smoothness, and can represent exactly most geometries encapsulated in Computer Aided Design (CAD) models. These attributes permitted us to derive accurate, efficient, and geometrically flexible collocation methods for phase-field models. The performance of our method is demonstrated by several numerical examples of phase separation modeled by the Cahn-Hilliard equation. We feel that our method successfully combines the geometrical flexibility of finite elements with the accuracy and simplicity of pseudo-spectral collocation methods, and is a viable alternative to classical collocation methods.

Modeling, simulation, and analysis at Sandia National Laboratories for health care systems

NASA Astrophysics Data System (ADS)

Polito, Joseph

1994-12-01

Modeling, Simulation, and Analysis are special competencies of the Department of Energy (DOE) National Laboratories which have been developed and refined through years of national defense work. Today, many of these skills are being applied to the problem of understanding the performance of medical devices and treatments. At Sandia National Laboratories we are developing models at all three levels of health care delivery: (1) phenomenology models for Observation and Test, (2) model-based outcomes simulations for Diagnosis and Prescription, and (3) model-based design and control simulations for the Administration of Treatment. A sampling of specific applications include non-invasive sensors for blood glucose, ultrasonic scanning for development of prosthetics, automated breast cancer diagnosis, laser burn debridement, surgical staple deformation, minimally invasive control for administration of a photodynamic drug, and human-friendly decision support aids for computer-aided diagnosis. These and other projects are being performed at Sandia with support from the DOE and in cooperation with medical research centers and private companies. Our objective is to leverage government engineering, modeling, and simulation skills with the biotechnical expertise of the health care community to create a more knowledge-rich environment for decision making and treatment.

Amplify scientific discovery with artificial intelligence

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

Gil, Yolanda; Greaves, Mark T.; Hendler, James

Computing innovations have fundamentally changed many aspects of scientific inquiry. For example, advances in robotics, high-end computing, networking, and databases now underlie much of what we do in science such as gene sequencing, general number crunching, sharing information between scientists, and analyzing large amounts of data. As computing has evolved at a rapid pace, so too has its impact in science, with the most recent computing innovations repeatedly being brought to bear to facilitate new forms of inquiry. Recently, advances in Artificial Intelligence (AI) have deeply penetrated many consumer sectors, including for example Apple’s Siri™ speech recognition system, real-time automatedmore » language translation services, and a new generation of self-driving cars and self-navigating drones. However, AI has yet to achieve comparable levels of penetration in scientific inquiry, despite its tremendous potential in aiding computers to help scientists tackle tasks that require scientific reasoning. We contend that advances in AI will transform the practice of science as we are increasingly able to effectively and jointly harness human and machine intelligence in the pursuit of major scientific challenges.« less

High-resolution computer-aided moire

NASA Astrophysics Data System (ADS)

Sciammarella, Cesar A.; Bhat, Gopalakrishna K.

1991-12-01

This paper presents a high resolution computer assisted moire technique for the measurement of displacements and strains at the microscopic level. The detection of micro-displacements using a moire grid and the problem associated with the recovery of displacement field from the sampled values of the grid intensity are discussed. A two dimensional Fourier transform method for the extraction of displacements from the image of the moire grid is outlined. An example of application of the technique to the measurement of strains and stresses in the vicinity of the crack tip in a compact tension specimen is given.

Simple geometric algorithms to aid in clearance management for robotic mechanisms

NASA Technical Reports Server (NTRS)

Copeland, E. L.; Ray, L. D.; Peticolas, J. D.

1981-01-01

Global geometric shapes such as lines, planes, circles, spheres, cylinders, and the associated computational algorithms which provide relatively inexpensive estimates of minimum spatial clearance for safe operations were selected. The Space Shuttle, remote manipulator system, and the Power Extension Package are used as an example. Robotic mechanisms operate in quarters limited by external structures and the problem of clearance is often of considerable interest. Safe clearance management is simple and suited to real time calculation, whereas contact prediction requires more precision, sophistication, and computational overhead.

ODIN system technology module library, 1972 - 1973

NASA Technical Reports Server (NTRS)

Hague, D. S.; Watson, D. A.; Glatt, C. R.; Jones, R. T.; Galipeau, J.; Phoa, Y. T.; White, R. J.

1978-01-01

ODIN/RLV is a digital computing system for the synthesis and optimization of reusable launch vehicle preliminary designs. The system consists of a library of technology modules in the form of independent computer programs and an executive program, ODINEX, which operates on the technology modules. The technology module library contains programs for estimating all major military flight vehicle system characteristics, for example, geometry, aerodynamics, economics, propulsion, inertia and volumetric properties, trajectories and missions, steady state aeroelasticity and flutter, and stability and control. A general system optimization module, a computer graphics module, and a program precompiler are available as user aids in the ODIN/RLV program technology module library.

Applying Nonverbal Techniques to Organizational Diagnosis.

ERIC Educational Resources Information Center

Tubbs, Stewart L.; Koske, W. Cary

Ongoing research programs conducted at General Motors Institute are motivated by the practical objective of improving the company's organizational effectiveness. Computer technology is being used whenever possible; for example, a technique developed by Herman Chernoff was used to process data from a survey of employee attitudes into 18 different…

Texture Feature Extraction and Classification for Iris Diagnosis

NASA Astrophysics Data System (ADS)

Ma, Lin; Li, Naimin

Appling computer aided techniques in iris image processing, and combining occidental iridology with the traditional Chinese medicine is a challenging research area in digital image processing and artificial intelligence. This paper proposes an iridology model that consists the iris image pre-processing, texture feature analysis and disease classification. To the pre-processing, a 2-step iris localization approach is proposed; a 2-D Gabor filter based texture analysis and a texture fractal dimension estimation method are proposed for pathological feature extraction; and at last support vector machines are constructed to recognize 2 typical diseases such as the alimentary canal disease and the nerve system disease. Experimental results show that the proposed iridology diagnosis model is quite effective and promising for medical diagnosis and health surveillance for both hospital and public use.

Functional tremor.

PubMed

Schwingenschuh, P; Deuschl, G

2016-01-01

Functional tremor is the commonest reported functional movement disorder. A confident clinical diagnosis of functional tremor is often possible based on the following "positive" criteria: a sudden tremor onset, unusual disease course, often with fluctuations or remissions, distractibility of the tremor if attention is removed from the affected body part, tremor entrainment, tremor variability, and a coactivation sign. Many patients show excessive exhaustion during examination. Other somatizations may be revealed in the medical history and patients may show additional functional neurologic symptoms and signs. In cases where the clinical diagnosis remains challenging, providing a "laboratory-supported" level of certainty aids an early positive diagnosis. In rare cases, in which the distinction from Parkinson's disease is difficult, dopamine transporter single-photon emission computed tomography (DAT-SPECT) can be indicated. © 2016 Elsevier B.V. All rights reserved.

The application of virtual reality systems as a support of digital manufacturing and logistics

NASA Astrophysics Data System (ADS)

Golda, G.; Kampa, A.; Paprocka, I.

2016-08-01

Modern trends in development of computer aided techniques are heading toward the integration of design competitive products and so-called "digital manufacturing and logistics", supported by computer simulation software. All phases of product lifecycle: starting from design of a new product, through planning and control of manufacturing, assembly, internal logistics and repairs, quality control, distribution to customers and after-sale service, up to its recycling or utilization should be aided and managed by advanced packages of product lifecycle management software. Important problems for providing the efficient flow of materials in supply chain management of whole product lifecycle, using computer simulation will be described on that paper. Authors will pay attention to the processes of acquiring relevant information and correct data, necessary for virtual modeling and computer simulation of integrated manufacturing and logistics systems. The article describes possibilities of use an applications of virtual reality software for modeling and simulation the production and logistics processes in enterprise in different aspects of product lifecycle management. The authors demonstrate effective method of creating computer simulations for digital manufacturing and logistics and show modeled and programmed examples and solutions. They pay attention to development trends and show options of the applications that go beyond enterprise.

Abdominal hernias: Radiological features

PubMed Central

Lassandro, Francesco; Iasiello, Francesca; Pizza, Nunzia Luisa; Valente, Tullio; Stefano, Maria Luisa Mangoni di Santo; Grassi, Roberto; Muto, Roberto

2011-01-01

Abdominal wall hernias are common diseases of the abdomen with a global incidence approximately 4%-5%. They are distinguished in external, diaphragmatic and internal hernias on the basis of their localisation. Groin hernias are the most common with a prevalence of 75%, followed by femoral (15%) and umbilical (8%). There is a higher prevalence in males (M:F, 8:1). Diagnosis is usually made on physical examination. However, clinical diagnosis may be difficult, especially in patients with obesity, pain or abdominal wall scarring. In these cases, abdominal imaging may be the first clue to the correct diagnosis and to confirm suspected complications. Different imaging modalities are used: conventional radiographs or barium studies, ultrasonography and Computed Tomography. Imaging modalities can aid in the differential diagnosis of palpable abdominal wall masses and can help to define hernial contents such as fatty tissue, bowel, other organs or fluid. This work focuses on the main radiological findings of abdominal herniations. PMID:21860678

Computer-aided diagnosis for osteoporosis using chest 3D CT images

NASA Astrophysics Data System (ADS)

Yoneda, K.; Matsuhiro, M.; Suzuki, H.; Kawata, Y.; Niki, N.; Nakano, Y.; Ohmatsu, H.; Kusumoto, M.; Tsuchida, T.; Eguchi, K.; Kaneko, M.

2016-03-01

The patients of osteoporosis comprised of about 13 million people in Japan and it is one of the problems the aging society has. In order to prevent the osteoporosis, it is necessary to do early detection and treatment. Multi-slice CT technology has been improving the three dimensional (3-D) image analysis with higher body axis resolution and shorter scan time. The 3-D image analysis using multi-slice CT images of thoracic vertebra can be used as a support to diagnose osteoporosis and at the same time can be used for lung cancer diagnosis which may lead to early detection. We develop automatic extraction and partitioning algorithm for spinal column by analyzing vertebral body structure, and the analysis algorithm of the vertebral body using shape analysis and a bone density measurement for the diagnosis of osteoporosis. Osteoporosis diagnosis support system obtained high extraction rate of the thoracic vertebral in both normal and low doses.

Texture feature extraction based on a uniformity estimation method for local brightness and structure in chest CT images.

PubMed

Peng, Shao-Hu; Kim, Deok-Hwan; Lee, Seok-Lyong; Lim, Myung-Kwan

2010-01-01

Texture feature is one of most important feature analysis methods in the computer-aided diagnosis (CAD) systems for disease diagnosis. In this paper, we propose a Uniformity Estimation Method (UEM) for local brightness and structure to detect the pathological change in the chest CT images. Based on the characteristics of the chest CT images, we extract texture features by proposing an extension of rotation invariant LBP (ELBP(riu4)) and the gradient orientation difference so as to represent a uniform pattern of the brightness and structure in the image. The utilization of the ELBP(riu4) and the gradient orientation difference allows us to extract rotation invariant texture features in multiple directions. Beyond this, we propose to employ the integral image technique to speed up the texture feature computation of the spatial gray level dependent method (SGLDM). Copyright © 2010 Elsevier Ltd. All rights reserved.

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.

[The new methods to define the staffing requirements for doctors,
nurses and nurses aides: an example of their implementation in an Italian hospital].

PubMed

Laquintana, Dario; Pazzaglia, Silvia; Demarchi, Antonia

2017-01-01

. The new methods to define the staffing requirements for doctors, nurses and nurses aides: an example of their implementation in an Italian hospital. The Italian government, after the transposition of European Union legislation on working hours, made a declaration of commitment to increase the number of staff of the National Health Service (NHS). The method for assessing the staffing needs innovates the old one that dated back a few decades. To implement the method proposed by the Ministry of Health to an Italian hospital and assess its impact on staffing and costs. The model was implemented on all the wards, multiplying the minutes of care expected in 2016, dividing the result by 60 to obtain the hours of care, and further dividing by the number of yearly hours of work of a nurse (1418). Same was done for nurses aides. The minutes of care were related to mean weight of the Diagnosis Related Groups of the ward and the results obtained compared to the actual staffing of nurses and nurses aides. The costs of the differences were calculated. The implementation of the model produced an excess of 23 nurses and a scarcity of 95 nurses aides compared to the actual staffing, with an increase of the costs of € 1.828.562,00. The results obtained and the criticisms received so far show the need of major changes. The data from international studies that associate staffing and patients outcomes and the nurse/patient ratio are macro-indicators already available that may orient choices and investments on the health care professions.

Current laboratory diagnosis of opportunistic enteric parasites in human immunodeficiency virus-infected patients

PubMed Central

De, Anuradha

2013-01-01

Diarrhea is a major cause of morbidity and mortality in human immunodeficiency virus (HIV)-infected individuals. Opportunistic enteric parasitic infections are encountered in 30-60% of HIV seropositive patients in developed countries and in 90% of patients in developing countries. Once the CD4+ cell count drops below 200 cells/μl, patients are considered to have developed acquired immunodeficiency syndrome (AIDS), with the risk of an AIDS-defining illness or opportunistic infection significantly increasing. Opportunistic enteric parasites encountered in these patients are Cryptosporidium, Isospora, Cyclospora, and microsporidia; as well as those more commonly associated with gastrointestinal disease, for example, Giardia intestinalis, Entamoeba histolytica, Strongyloides stercoralis, and also rarely Balantidium coli. In view of AIDS explosion in India, opportunistic enteric parasites are becoming increasingly important and it has to be identified properly. Apart from wet mounts, concentration methods for stool samples and special staining techniques for identification of these parasites, commercially available fecal immunoassays are widely available for the majority of enteric protozoa. Molecular methods such as polymerase chain reaction (PCR), PCR-restriction fragment length polymorphism, flow cytometry, and sodium dodecyl sulphate-polyacrylamide gel electrophoresis (SDS-PAGE), have also come in the pipeline for early diagnosis of these infections. Proper disposal of the feces to prevent contamination of the soil and water, boiling/filtering drinking water along with improved personal hygiene might go a long way in preventing these enteric parasitic infections. PMID:23961436

Computer-aided diagnosis based on enhancement of degraded fundus photographs.

PubMed

Jin, Kai; Zhou, Mei; Wang, Shaoze; Lou, Lixia; Xu, Yufeng; Ye, Juan; Qian, Dahong

2018-05-01

Retinal imaging is an important and effective tool for detecting retinal diseases. However, degraded images caused by the aberrations of the eye can disguise lesions, so that a diseased eye can be mistakenly diagnosed as normal. In this work, we propose a new image enhancement method to improve the quality of degraded images. A new method is used to enhance degraded-quality fundus images. In this method, the image is converted from the input RGB colour space to LAB colour space and then each normalized component is enhanced using contrast-limited adaptive histogram equalization. Human visual system (HVS)-based fundus image quality assessment, combined with diagnosis by experts, is used to evaluate the enhancement. The study included 191 degraded-quality fundus photographs of 143 subjects with optic media opacity. Objective quality assessment of image enhancement (range: 0-1) indicated that our method improved colour retinal image quality from an average of 0.0773 (variance 0.0801) to an average of 0.3973 (variance 0.0756). Following enhancement, area under curves (AUC) were 0.996 for the glaucoma classifier, 0.989 for the diabetic retinopathy (DR) classifier, 0.975 for the age-related macular degeneration (AMD) classifier and 0.979 for the other retinal diseases classifier. The relatively simple method for enhancing degraded-quality fundus images achieves superior image enhancement, as demonstrated in a qualitative HVS-based image quality assessment. This retinal image enhancement may, therefore, be employed to assist ophthalmologists in more efficient screening of retinal diseases and the development of computer-aided diagnosis. © 2017 Acta Ophthalmologica Scandinavica Foundation. Published by John Wiley & Sons Ltd.

A new 3D texture feature based computer-aided diagnosis approach to differentiate pulmonary nodules

NASA Astrophysics Data System (ADS)

Han, Fangfang; Wang, Huafeng; Song, Bowen; Zhang, Guopeng; Lu, Hongbing; Moore, William; Zhao, Hong; Liang, Zhengrong

2013-02-01

To distinguish malignant pulmonary nodules from benign ones is of much importance in computer-aided diagnosis of lung diseases. Compared to many previous methods which are based on shape or growth assessing of nodules, this proposed three-dimensional (3D) texture feature based approach extracted fifty kinds of 3D textural features from gray level, gradient and curvature co-occurrence matrix, and more derivatives of the volume data of the nodules. To evaluate the presented approach, the Lung Image Database Consortium public database was downloaded. Each case of the database contains an annotation file, which indicates the diagnosis results from up to four radiologists. In order to relieve partial-volume effect, interpolation process was carried out to those volume data with image slice thickness more than 1mm, and thus we had categorized the downloaded datasets to five groups to validate the proposed approach, one group of thickness less than 1mm, two types of thickness range from 1mm to 1.25mm and greater than 1.25mm (each type contains two groups, one with interpolation and the other without). Since support vector machine is based on statistical learning theory and aims to learn for predicting future data, so it was chosen as the classifier to perform the differentiation task. The measure on the performance was based on the area under the curve (AUC) of Receiver Operating Characteristics. From 284 nodules (122 malignant and 162 benign ones), the validation experiments reported a mean of 0.9051 and standard deviation of 0.0397 for the AUC value on average over 100 randomizations.

Computer-aided diagnosis of focal liver lesions by use of physicians' subjective classification of echogenic patterns in baseline and contrast-enhanced ultrasonography.

PubMed

Sugimoto, Katsutoshi; Shiraishi, Junji; Moriyasu, Fuminori; Doi, Kunio

2009-04-01

To develop a computer-aided diagnostic (CAD) scheme for classifying focal liver lesions (FLLs) by use of physicians' subjective classification of echogenic patterns of FLLs on baseline and contrast-enhanced ultrasonography (US). A total of 137 hepatic lesions in 137 patients were evaluated with B-mode and NC100100 (Sonazoid)-enhanced pulse-inversion US; lesions included 74 hepatocellular carcinomas (HCCs) (23: well-differentiated, 36: moderately differentiated, 15: poorly differentiated HCCs), 33 liver metastases, and 30 liver hemangiomas. Three physicians evaluated single images at B-mode and arterial phases with a cine mode. Physicians were asked to classify each lesion into one of eight B-mode and one of eight enhancement patterns, but did not make a diagnosis. To classify five types of FLLs, we employed a decision tree model with four decision nodes and four artificial neural networks (ANNs). The results of the physicians' pattern classifications were used successively for four different ANNs in making decisions at each of the decision nodes in the decision tree model. The classification accuracies for the 137 FLLs were 84.8% for metastasis, 93.3% for hemangioma, and 98.6% for all HCCs. In addition, the classification accuracies for histological differentiation types of HCCs were 65.2% for well-differentiated HCC, 41.7% for moderately differentiated HCC, and 80.0% for poorly differentiated HCC. This CAD scheme has the potential to improve the diagnostic accuracy of liver lesions. However, the accuracy in the histologic differential diagnosis of HCC based on baseline and contrast-enhanced US is still limited.

Vector Observation-Aided/Attitude-Rate Estimation Using Global Positioning System Signals

NASA Technical Reports Server (NTRS)

Oshman, Yaakov; Markley, F. Landis

1997-01-01

A sequential filtering algorithm is presented for attitude and attitude-rate estimation from Global Positioning System (GPS) differential carrier phase measurements. A third-order, minimal-parameter method for solving the attitude matrix kinematic equation is used to parameterize the filter's state, which renders the resulting estimator computationally efficient. Borrowing from tracking theory concepts, the angular acceleration is modeled as an exponentially autocorrelated stochastic process, thus avoiding the use of the uncertain spacecraft dynamic model. The new formulation facilitates the use of aiding vector observations in a unified filtering algorithm, which can enhance the method's robustness and accuracy. Numerical examples are used to demonstrate the performance of the method.

Shin splints--a literature review.

PubMed Central

Bates, P

1985-01-01

"Shin splints" is not a specific diagnosis. It is merely a descriptive term that describes chronic exertional shin pain in an athlete. The evidence seems clear that shin splint pain has many different causes and this reflects the variation in the anatomy. It would be preferable to describe shin splint pain by location and aetiology, for example, lower medial tibial pain due to periostitis or upper lateral tibial pain due to elevated compartment pressure. This would aid communication between physicians and also direct therapy more accurately. Images p132-a PMID:3907743

A New Approach to Predicting the Thermal Environment in Buildings at the Early Design Stage. Building Research Establishment Current Paper 2/74.

ERIC Educational Resources Information Center

Milbank, N. O.

The paper argues that existing computer programs for thermal predictions do not produce suitable information for architects, particularly at the early stages of design. It reviews the important building features that determine the thermal environment and the need for heating and cooling plant. Graphical design aids are proposed, with examples to…

Computer Aided Process Planning of Machined Metal Parts

DTIC Science & Technology

1984-09-01

the manufac- turer to accentuate the positive to assist marketing . Machine usage costs and facility loadings are frequently critical. For example...Variant systems currently on the market include Multiplan (TM of OIR, Inc.), CY-Miplan (TM of Computervision), PICAPP (TM of PICAPP, Inc.) and CSD...Multiproduct, Multistage Manufacturing Systems, Journal of Engineering for Industry, ASME, August 1977. Hitomi, K. and I. Ham, Product Mix and Machine Loading

A Comparative Study of Computer-Aided Clinical Diagnosis of Birth Defects.

DTIC Science & Technology

1981-01-21

SUPPRESSIBLE HYPERPARATHYROIDISM TYPE NEONATAL FAMILIAL HYPOCHONDROPLASIA HYPOGLYCEMIA TYPE FAMILIAL NEONATAL HYPOGLYCEMIA TYPE LEUCINE INDUCED...disease. There are also causal links between disease nodes. These are unidirectional links indicating that one disease can cause the other. These links...contains the finding and has no superior which does.4 If f5 was then entered, D8 and D9 would quality to be evoked. This would cause D1 to be deactivated

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

AI in manufacturing

NASA Astrophysics Data System (ADS)

Gross, John E.; Minato, Rick; Smith, David M.; Loftin, R. B.; Savely, Robert T.

1991-10-01

AI techniques are shown to have been useful in such aerospace industry tasks as vehicle configuration layouts, process planning, tool design, numerically-controlled programming of tools, production scheduling, and equipment testing and diagnosis. Accounts are given of illustrative experiences at the production facilities of three major aerospace defense contractors. Also discussed is NASA's autonomous Intelligent Computer-Aided Training System, for such ambitious manned programs as Space Station Freedom, which employs five different modules to constitute its job-independent training architecture.

Image calibration and registration in cone-beam computed tomogram for measuring the accuracy of computer-aided implant surgery

NASA Astrophysics Data System (ADS)

Lam, Walter Y. H.; Ngan, Henry Y. T.; Wat, Peter Y. P.; Luk, Henry W. K.; Goto, Tazuko K.; Pow, Edmond H. N.

2015-02-01

Medical radiography is the use of radiation to "see through" a human body without breaching its integrity (surface). With computed tomography (CT)/cone beam computed tomography (CBCT), three-dimensional (3D) imaging can be produced. These imagings not only facilitate disease diagnosis but also enable computer-aided surgical planning/navigation. In dentistry, the common method for transfer of the virtual surgical planning to the patient (reality) is the use of surgical stent either with a preloaded planning (static) like a channel or a real time surgical navigation (dynamic) after registration with fiducial markers (RF). This paper describes using the corner of a cube as a radiopaque fiducial marker on an acrylic (plastic) stent, this RF allows robust calibration and registration of Cartesian (x, y, z)- coordinates for linking up the patient (reality) and the imaging (virtuality) and hence the surgical planning can be transferred in either static or dynamic way. The accuracy of computer-aided implant surgery was measured with reference to coordinates. In our preliminary model surgery, a dental implant was planned virtually and placed with preloaded surgical guide. The deviation of the placed implant apex from the planning was x=+0.56mm [more right], y=- 0.05mm [deeper], z=-0.26mm [more lingual]) which was within clinically 2mm safety range. For comparison with the virtual planning, the physically placed implant was CT/CBCT scanned and errors may be introduced. The difference of the actual implant apex to the virtual apex was x=0.00mm, y=+0.21mm [shallower], z=-1.35mm [more lingual] and this should be brought in mind when interpret the results.

A Computer-Aided Analysis Method of SPECT Brain Images for Quantitative Treatment Monitoring: Performance Evaluations and Clinical Applications.

PubMed

Zheng, Xiujuan; Wei, Wentao; Huang, Qiu; Song, Shaoli; Wan, Jieqing; Huang, Gang

2017-01-01

The objective and quantitative analysis of longitudinal single photon emission computed tomography (SPECT) images are significant for the treatment monitoring of brain disorders. Therefore, a computer aided analysis (CAA) method is introduced to extract a change-rate map (CRM) as a parametric image for quantifying the changes of regional cerebral blood flow (rCBF) in longitudinal SPECT brain images. The performances of the CAA-CRM approach in treatment monitoring are evaluated by the computer simulations and clinical applications. The results of computer simulations show that the derived CRMs have high similarities with their ground truths when the lesion size is larger than system spatial resolution and the change rate is higher than 20%. In clinical applications, the CAA-CRM approach is used to assess the treatment of 50 patients with brain ischemia. The results demonstrate that CAA-CRM approach has a 93.4% accuracy of recovered region's localization. Moreover, the quantitative indexes of recovered regions derived from CRM are all significantly different among the groups and highly correlated with the experienced clinical diagnosis. In conclusion, the proposed CAA-CRM approach provides a convenient solution to generate a parametric image and derive the quantitative indexes from the longitudinal SPECT brain images for treatment monitoring.

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.

The Application of Artificial Intelligence Principles to Teaching and Training

ERIC Educational Resources Information Center

Shaw, Keith

2008-01-01

This paper compares and contrasts the use of AI principles in industrial training with more normal computer-based training (CBT) approaches. A number of applications of CBT are illustrated (for example simulations, tutorial presentations, fault diagnosis, management games, industrial relations exercises) and compared with an alternative approach…

Computer graphics applications to crew displays

NASA Technical Reports Server (NTRS)

Wyzkoski, J.

1983-01-01

Astronauts are provided much data and information via the monochrome CRT displays on the orbiter. For this project two areas were investigated for the possible introduction of computer graphics to enhance and extend the utility of these displays. One involved reviewing the current orbiter displays and identifying those which could be improved via computer graphics. As an example, the tabular data on electrical power distribution and control was enhanced by the addition of color and bar charts. The other dealt with the development of an aid to berthing a payload with the Remote Manipulator System (RMS). This aid consists of a graphics display of the top, front and side views of the payload and cargo bay and point of resolution (POR) position and attitude data for the current location of the payload. The initial implementation was on an IBM PC clone. The demonstration software installed in the Johnson Space Center Manipulator Development Facility (MD) was reviewed. Due to current hardware limitations, the MDF verision is slow, i.e., about a 40+ seond update rate and, hence, not real-time. Despite this fact, the evaluation of this additional visual cue as an RMS operator aid indicates that this display, with modifications for speed, etc., can assist the crew. Further development is appropriate.

Lotus-on-chip: computer-aided design and 3D direct laser writing of bioinspired surfaces for controlling the wettability of materials and devices.

PubMed

Lantada, Andrés Díaz; Hengsbach, Stefan; Bade, Klaus

2017-10-16

In this study we present the combination of a math-based design strategy with direct laser writing as high-precision technology for promoting solid free-form fabrication of multi-scale biomimetic surfaces. Results show a remarkable control of surface topography and wettability properties. Different examples of surfaces inspired on the lotus leaf, which to our knowledge are obtained for the first time following a computer-aided design with this degree of precision, are presented. Design and manufacturing strategies towards microfluidic systems whose fluid driving capabilities are obtained just by promoting a design-controlled wettability of their surfaces, are also discussed and illustrated by means of conceptual proofs. According to our experience, the synergies between the presented computer-aided design strategy and the capabilities of direct laser writing, supported by innovative writing strategies to promote final size while maintaining high precision, constitute a relevant step forward towards materials and devices with design-controlled multi-scale and micro-structured surfaces for advanced functionalities. To our knowledge, the surface geometry of the lotus leaf, which has relevant industrial applications thanks to its hydrophobic and self-cleaning behavior, has not yet been adequately modeled and manufactured in an additive way with the degree of precision that we present here.

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.

Parallelization of ARC3D with Computer-Aided Tools

NASA Technical Reports Server (NTRS)

Jin, Haoqiang; Hribar, Michelle; Yan, Jerry; Saini, Subhash (Technical Monitor)

1998-01-01

A series of efforts have been devoted to investigating methods of porting and parallelizing applications quickly and efficiently for new architectures, such as the SCSI Origin 2000 and Cray T3E. This report presents the parallelization of a CFD application, ARC3D, using the computer-aided tools, Cesspools. Steps of parallelizing this code and requirements of achieving better performance are discussed. The generated parallel version has achieved reasonably well performance, for example, having a speedup of 30 for 36 Cray T3E processors. However, this performance could not be obtained without modification of the original serial code. It is suggested that in many cases improving serial code and performing necessary code transformations are important parts for the automated parallelization process although user intervention in many of these parts are still necessary. Nevertheless, development and improvement of useful software tools, such as Cesspools, can help trim down many tedious parallelization details and improve the processing efficiency.

Deep Learning in Gastrointestinal Endoscopy.

PubMed

Patel, Vivek; Armstrong, David; Ganguli, Malika; Roopra, Sandeep; Kantipudi, Neha; Albashir, Siwar; Kamath, Markad V

2016-01-01

Gastrointestinal (GI) endoscopy is used to inspect the lumen or interior of the GI tract for several purposes, including, (1) making a clinical diagnosis, in real time, based on the visual appearances; (2) taking targeted tissue samples for subsequent histopathological examination; and (3) in some cases, performing therapeutic interventions targeted at specific lesions. GI endoscopy is therefore predicated on the assumption that the operator-the endoscopist-is able to identify and characterize abnormalities or lesions accurately and reproducibly. However, as in other areas of clinical medicine, such as histopathology and radiology, many studies have documented marked interobserver and intraobserver variability in lesion recognition. Thus, there is a clear need and opportunity for techniques or methodologies that will enhance the quality of lesion recognition and diagnosis and improve the outcomes of GI endoscopy. Deep learning models provide a basis to make better clinical decisions in medical image analysis. Biomedical image segmentation, classification, and registration can be improved with deep learning. Recent evidence suggests that the application of deep learning methods to medical image analysis can contribute significantly to computer-aided diagnosis. Deep learning models are usually considered to be more flexible and provide reliable solutions for image analysis problems compared to conventional computer vision models. The use of fast computers offers the possibility of real-time support that is important for endoscopic diagnosis, which has to be made in real time. Advanced graphics processing units and cloud computing have also favored the use of machine learning, and more particularly, deep learning for patient care. This paper reviews the rapidly evolving literature on the feasibility of applying deep learning algorithms to endoscopic imaging.

Example-Based Super-Resolution Fluorescence Microscopy.

PubMed

Jia, Shu; Han, Boran; Kutz, J Nathan

2018-04-23

Capturing biological dynamics with high spatiotemporal resolution demands the advancement in imaging technologies. Super-resolution fluorescence microscopy offers spatial resolution surpassing the diffraction limit to resolve near-molecular-level details. While various strategies have been reported to improve the temporal resolution of super-resolution imaging, all super-resolution techniques are still fundamentally limited by the trade-off associated with the longer image acquisition time that is needed to achieve higher spatial information. Here, we demonstrated an example-based, computational method that aims to obtain super-resolution images using conventional imaging without increasing the imaging time. With a low-resolution image input, the method provides an estimate of its super-resolution image based on an example database that contains super- and low-resolution image pairs of biological structures of interest. The computational imaging of cellular microtubules agrees approximately with the experimental super-resolution STORM results. This new approach may offer potential improvements in temporal resolution for experimental super-resolution fluorescence microscopy and provide a new path for large-data aided biomedical imaging.

Post-processing methods of rendering and visualizing 3-D reconstructed tomographic images

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

Wong, S.T.C.

The purpose of this presentation is to discuss the computer processing techniques of tomographic images, after they have been generated by imaging scanners, for volume visualization. Volume visualization is concerned with the representation, manipulation, and rendering of volumetric data. Since the first digital images were produced from computed tomography (CT) scanners in the mid 1970s, applications of visualization in medicine have expanded dramatically. Today, three-dimensional (3D) medical visualization has expanded from using CT data, the first inherently digital source of 3D medical data, to using data from various medical imaging modalities, including magnetic resonance scanners, positron emission scanners, digital ultrasound,more » electronic and confocal microscopy, and other medical imaging modalities. We have advanced from rendering anatomy to aid diagnosis and visualize complex anatomic structures to planning and assisting surgery and radiation treatment. New, more accurate and cost-effective procedures for clinical services and biomedical research have become possible by integrating computer graphics technology with medical images. This trend is particularly noticeable in current market-driven health care environment. For example, interventional imaging, image-guided surgery, and stereotactic and visualization techniques are now stemming into surgical practice. In this presentation, we discuss only computer-display-based approaches of volumetric medical visualization. That is, we assume that the display device available is two-dimensional (2D) in nature and all analysis of multidimensional image data is to be carried out via the 2D screen of the device. There are technologies such as holography and virtual reality that do provide a {open_quotes}true 3D screen{close_quotes}. To confine the scope, this presentation will not discuss such approaches.« less

Computer-based rhythm diagnosis and its possible influence on nonexpert electrocardiogram readers.

PubMed

Hakacova, Nina; Trägårdh-Johansson, Elin; Wagner, Galen S; Maynard, Charles; Pahlm, Olle

2012-01-01

Systems providing computer-based analysis of the resting electrocardiogram (ECG) seek to improve the quality of health care by providing accurate and timely automatic diagnosis of, for example, cardiac rhythm to clinicians. The accuracy of these diagnoses, however, remains questionable. We tested the hypothesis that (a) 2 independent automated ECG systems have better accuracy in rhythm diagnosis than nonexpert clinicians and (b) both systems provide correct diagnostic suggestions in a large percentage of cases where the diagnosis of nonexpert clinicians is incorrect. Five hundred ECGs were manually analyzed by 2 senior experts, 3 nonexpert clinicians, and automatically by 2 automated systems. The accuracy of the nonexpert rhythm statements was compared with the accuracy of each system statement. The proportion of rhythm statements when the clinician's diagnoses were incorrect and the systems instead provided correct diagnosis was assessed. A total of 420 sinus rhythms and 156 rhythm disturbances were recognized by expert reading. Significance of the difference in accuracy between nonexperts and systems was P = .45 for system A and P = .11 for system B. The percentage of correct automated diagnoses in cases when the clinician was incorrect was 28% ± 10% for system A and 25% ± 11% for system B (P = .09). The rhythm diagnoses of automated systems did not reach better average accuracy than those of nonexpert readings. The computer diagnosis of rhythm can be incorrect in cases where the clinicians fail in reaching the correct ECG diagnosis. Copyright © 2012. Published by Elsevier Inc.

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.

Effects of Response to 2014-2015 Ebola Outbreak on Deaths from Malaria, HIV/AIDS, and Tuberculosis, West Africa.

PubMed

Parpia, Alyssa S; Ndeffo-Mbah, Martial L; Wenzel, Natasha S; Galvani, Alison P

2016-03-01

Response to the 2014-2015 Ebola outbreak in West Africa overwhelmed the healthcare systems of Guinea, Liberia, and Sierra Leone, reducing access to health services for diagnosis and treatment for the major diseases that are endemic to the region: malaria, HIV/AIDS, and tuberculosis. To estimate the repercussions of the Ebola outbreak on the populations at risk for these diseases, we developed computational models for disease transmission and infection progression. We estimated that a 50% reduction in access to healthcare services during the Ebola outbreak exacerbated malaria, HIV/AIDS, and tuberculosis mortality rates by additional death counts of 6,269 (2,564-12,407) in Guinea; 1,535 (522-2,8780) in Liberia; and 2,819 (844-4,844) in Sierra Leone. The 2014-2015 Ebola outbreak was catastrophic in these countries, and its indirect impact of increasing the mortality rates of other diseases was also substantial.

Novel Treatment Planning of Hemimandibular Hyperplasia by the Use of Three-Dimensional Computer-Aided-Design and Computer-Aided-Manufacturing Technologies.

PubMed

Hatamleh, Muhanad M; Yeung, Elizabeth; Osher, Jonas; Huppa, Chrisopher

2017-05-01

Hemimandibular hyperplasia is characterized by an obvious overgrowth in the size of the mandible on one side, which can extend up to the midline causing facial asymmetry. Surgical resection of the overgrowth depends heavily on the skill and experience of the surgeon. This report describes a novel methodology of applying three-dimensional computer-aided-design and computer-aided-manufacturing principles in improving the outcome of surgery in 2 mandibular hyperplasia patients. Both patients had their cone beam computer tomography (CBCT) scan performed. CMF Pro Plan software (v. 2.1) was used to process the scan data into virtual 3-dimensional models of the maxilla and mandible. Head tilt was adjusted manually by following horizontal reference. Facial asymmetry secondary to mandibular hypertrophy was obvious on frontal and lateral views. Simulation functions were followed including mirror imaging of the unaffected mandibular side into the hyperplastic side and position was optimized by translation and orientation functions. Reconstruction of virtual symmetry was assessed and checked by running 3-dimensional measurements. Then, subtraction functions were used to create a 3-dimensional template defining the outline of the lower mandibular osteotomy needed. Precision of mandibular teeth was enhanced by amalgamating the CBCT scan with e-cast scan of the patient lower teeth. 3-Matic software (v. 10.0) was used in designing cutting guide(s) that define the amount of overgrowth to be resected. The top section of the guide was resting on the teeth hence ensuring stability and accuracy while positioning it. The guide design was exported as an .stl file and printed using in-house 3-dimensional printer in biocompatible resin. Three-dimensional technologies of both softwares (CMF Pro Plan and 3-Matic) are accurate and reliable methods in the diagnosis, treatment planning, and designing of cutting guides that optimize surgical correction of hemimandibular hyperplasia at timely and cost-effect manner.

Computer Science and Statistics. Proceedings of the Symposium on the Interface (18th) Held on March 19-21, 1986 in Fort Collins, Colorado.

DTIC Science & Technology

1987-08-26

example, expert systems research would benefit examples are the Acute Renal Failure [15] system, the if it could attract statisticians to assist in...research projects including the Acute Renal Failure [15] system, the 6. EXPLAINING COMPLEX REASONING INTERNIST-] [22] system for diagnosis within the...the MEDAS and Acute Renal Failure systems. task at any point in reasoning about a case is constrained to Entropy-discriminate makes use of a measure

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.

Image segmentation of pyramid style identifier based on Support Vector Machine for colorectal endoscopic images.

PubMed

Okamoto, Takumi; Koide, Tetsushi; Sugi, Koki; Shimizu, Tatsuya; Anh-Tuan Hoang; Tamaki, Toru; Raytchev, Bisser; Kaneda, Kazufumi; Kominami, Yoko; Yoshida, Shigeto; Mieno, Hiroshi; Tanaka, Shinji

2015-08-01

With the increase of colorectal cancer patients in recent years, the needs of quantitative evaluation of colorectal cancer are increased, and the computer-aided diagnosis (CAD) system which supports doctor's diagnosis is essential. In this paper, a hardware design of type identification module in CAD system for colorectal endoscopic images with narrow band imaging (NBI) magnification is proposed for real-time processing of full high definition image (1920 × 1080 pixel). A pyramid style image segmentation with SVMs for multi-size scan windows, which can be implemented on an FPGA with small circuit area and achieve high accuracy, is proposed for actual complex colorectal endoscopic images.

Foreign body aspiration in adult airways: therapeutic approach

PubMed Central

Hewlett, Justin C.; Rickman, Otis B.; Lentz, Robert J.; Prakash, Udaya B.

2017-01-01

Tracheobronchial foreign body (FB) aspiration is an uncommon but potentially life-threatening event in adults. Symptoms typically consist of a choking event followed by cough and dyspnea, however, these findings are inconsistent and symptoms may mimic more chronic lung diseases such as asthma or chronic obstructive pulmonary disease. Chest radiography and computed tomography can provide information regarding the location and characteristics of foreign bodies and aid in diagnosis. Bronchoscopy remains the gold standard for diagnosis and management of FB aspiration. The authors describe the typical clinical presentation, diagnostic evaluation, and bronchoscopic management of foreign bodies in adult airways with a focus on bronchoscopic techniques and potential complications of FB extraction. PMID:29221325

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 diagnosis of prostate cancer using multi-parametric MRI: comparison between PUN and Tofts models

NASA Astrophysics Data System (ADS)

Mazzetti, S.; Giannini, V.; Russo, F.; Regge, D.

2018-05-01

Computer-aided diagnosis (CAD) systems are increasingly being used in clinical settings to report multi-parametric magnetic resonance imaging (mp-MRI) of the prostate. Usually, CAD systems automatically highlight cancer-suspicious regions to the radiologist, reducing reader variability and interpretation errors. Nevertheless, implementing this software requires the selection of which mp-MRI parameters can best discriminate between malignant and non-malignant regions. To exploit functional information, some parameters are derived from dynamic contrast-enhanced (DCE) acquisitions. In particular, much CAD software employs pharmacokinetic features, such as K trans and k ep, derived from the Tofts model, to estimate a likelihood map of malignancy. However, non-pharmacokinetic models can be also used to describe DCE-MRI curves, without any requirement for prior knowledge or measurement of the arterial input function, which could potentially lead to large errors in parameter estimation. In this work, we implemented an empirical function derived from the phenomenological universalities (PUN) class to fit DCE-MRI. The parameters of the PUN model are used in combination with T2-weighted and diffusion-weighted acquisitions to feed a support vector machine classifier to produce a voxel-wise malignancy likelihood map of the prostate. The results were all compared to those for a CAD system based on Tofts pharmacokinetic features to describe DCE-MRI curves, using different quality aspects of image segmentation, while also evaluating the number and size of false positive (FP) candidate regions. This study included 61 patients with 70 biopsy-proven prostate cancers (PCa). The metrics used to evaluate segmentation quality between the two CAD systems were not statistically different, although the PUN-based CAD reported a lower number of FP, with reduced size compared to the Tofts-based CAD. In conclusion, the CAD software based on PUN parameters is a feasible means with which to detect PCa, without affecting segmentation quality, and hence it could be successfully applied in clinical settings, improving the automated diagnosis process and reducing computational complexity.

Computer aided detection in prostate cancer diagnostics: A promising alternative to biopsy? A retrospective study from 104 lesions with histological ground truth.

PubMed

Thon, Anika; Teichgräber, Ulf; Tennstedt-Schenk, Cornelia; Hadjidemetriou, Stathis; Winzler, Sven; Malich, Ansgar; Papageorgiou, Ismini

2017-01-01

Prostate cancer (PCa) diagnosis by means of multiparametric magnetic resonance imaging (mpMRI) is a current challenge for the development of computer-aided detection (CAD) tools. An innovative CAD-software (Watson Elementary™) was proposed to achieve high sensitivity and specificity, as well as to allege a correlate to Gleason grade. To assess the performance of Watson Elementary™ in automated PCa diagnosis in our hospital´s database of MRI-guided prostate biopsies. The evaluation was retrospective for 104 lesions (47 PCa, 57 benign) from 79, 64.61±6.64 year old patients using 3T T2-weighted imaging, Apparent Diffusion Coefficient (ADC) maps and dynamic contrast enhancement series. Watson Elementary™ utilizes signal intensity, diffusion properties and kinetic profile to compute a proportional Gleason grade predictor, termed Malignancy Attention Index (MAI). The analysis focused on (i) the CAD sensitivity and specificity to classify suspect lesions and (ii) the MAI correlation with the histopathological ground truth. The software revealed a sensitivity of 46.80% for PCa classification. The specificity for PCa was found to be 75.43% with a positive predictive value of 61.11%, a negative predictive value of 63.23% and a false discovery rate of 38.89%. CAD classified PCa and benign lesions with equal probability (P 0.06, χ2 test). Accordingly, receiver operating characteristic analysis suggests a poor predictive value for MAI with an area under curve of 0.65 (P 0.02), which is not superior to the performance of board certified observers. Moreover, MAI revealed no significant correlation with Gleason grade (P 0.60, Pearson´s correlation). The tested CAD software for mpMRI analysis was a weak PCa biomarker in this dataset. Targeted prostate biopsy and histology remains the gold standard for prostate cancer diagnosis.

Computer aided detection in prostate cancer diagnostics: A promising alternative to biopsy? A retrospective study from 104 lesions with histological ground truth

PubMed Central

Thon, Anika; Teichgräber, Ulf; Tennstedt-Schenk, Cornelia; Hadjidemetriou, Stathis; Winzler, Sven; Malich, Ansgar

2017-01-01

Background Prostate cancer (PCa) diagnosis by means of multiparametric magnetic resonance imaging (mpMRI) is a current challenge for the development of computer-aided detection (CAD) tools. An innovative CAD-software (Watson Elementary™) was proposed to achieve high sensitivity and specificity, as well as to allege a correlate to Gleason grade. Aim/Objective To assess the performance of Watson Elementary™ in automated PCa diagnosis in our hospital´s database of MRI-guided prostate biopsies. Methods The evaluation was retrospective for 104 lesions (47 PCa, 57 benign) from 79, 64.61±6.64 year old patients using 3T T2-weighted imaging, Apparent Diffusion Coefficient (ADC) maps and dynamic contrast enhancement series. Watson Elementary™ utilizes signal intensity, diffusion properties and kinetic profile to compute a proportional Gleason grade predictor, termed Malignancy Attention Index (MAI). The analysis focused on (i) the CAD sensitivity and specificity to classify suspect lesions and (ii) the MAI correlation with the histopathological ground truth. Results The software revealed a sensitivity of 46.80% for PCa classification. The specificity for PCa was found to be 75.43% with a positive predictive value of 61.11%, a negative predictive value of 63.23% and a false discovery rate of 38.89%. CAD classified PCa and benign lesions with equal probability (P 0.06, χ2 test). Accordingly, receiver operating characteristic analysis suggests a poor predictive value for MAI with an area under curve of 0.65 (P 0.02), which is not superior to the performance of board certified observers. Moreover, MAI revealed no significant correlation with Gleason grade (P 0.60, Pearson´s correlation). Conclusion The tested CAD software for mpMRI analysis was a weak PCa biomarker in this dataset. Targeted prostate biopsy and histology remains the gold standard for prostate cancer diagnosis. PMID:29023572

Automated quantitative muscle biopsy analysis system

NASA Technical Reports Server (NTRS)

Castleman, Kenneth R. (Inventor)

1980-01-01

An automated system to aid the diagnosis of neuromuscular diseases by producing fiber size histograms utilizing histochemically stained muscle biopsy tissue. Televised images of the microscopic fibers are processed electronically by a multi-microprocessor computer, which isolates, measures, and classifies the fibers and displays the fiber size distribution. The architecture of the multi-microprocessor computer, which is iterated to any required degree of complexity, features a series of individual microprocessors P.sub.n each receiving data from a shared memory M.sub.n-1 and outputing processed data to a separate shared memory M.sub.n+1 under control of a program stored in dedicated memory M.sub.n.

[Application of SPECT/CT in neurosurgical practice].

PubMed

Golanov, A V; Kotel'nikova, T M; Melikian, A G; Dolgushin, M B; Sorokin, V S; Soboleva, O I; Khokhlova, E V; Gorlachev, G E; Krasnianskiĭ, S A

2012-01-01

The paper presents the experience of application of single-photon emission computed tomography (SPECT) and CT in neurosurgery. Combination of these two techniques in the single system provides higher precision of both methods. The novel technique allows assessment of tumor spread in the brain, differential diagnosis of tumor regrowth and radiation-induced necrosis, evaluation of cerebral perfusion in epilepsy, traumatic brain injury (TBI), and diagnostics of secondary CNS lesions. Examples of primary diagnosis, dynamic follow-up and differential diagnosis of cerebral neoplasms, localization of epileptogenic foci in planning of surgery, prediction of outcome after TBI and evaluation of spread of metastatic skeletal involvement and further application of acquire data are presented.

Visions of visualization aids - Design philosophy and observations

NASA Technical Reports Server (NTRS)

Ellis, Stephen R.

1989-01-01

Aids for the visualization of high-dimensional scientific or other data must be designed. Simply casting multidimensional data into a two-dimensional or three-dimensional spatial metaphor does not guarantee that the presentation will provide insight or a parsimonious description of phenomena implicit in the data. Useful visualization, in contrast to glitzy, high-tech, computer-graphics imagery, is generally based on preexisting theoretical beliefs concerning the underlying phenomena. These beliefs guide selection and formatting of the plotted variables. Visualization tools are useful for understanding naturally three-dimensional data bases such as those used by pilots or astronauts. Two examples of such aids for spatial maneuvering illustrate that informative geometric distortion may be introduced to assist visualization and that visualization of complex dynamics alone may not be adequate to provide the necessary insight into the underlying processes.

Computer-aided diagnosis of pulmonary diseases using x-ray darkfield radiography

NASA Astrophysics Data System (ADS)

Einarsdóttir, Hildur; Yaroshenko, Andre; Velroyen, Astrid; Bech, Martin; Hellbach, Katharina; Auweter, Sigrid; Yildirim, Önder; Meinel, Felix G.; Eickelberg, Oliver; Reiser, Maximilian; Larsen, Rasmus; Kjær Ersbøll, Bjarne; Pfeiffer, Franz

2015-12-01

In this work we develop a computer-aided diagnosis (CAD) scheme for classification of pulmonary disease for grating-based x-ray radiography. In addition to conventional transmission radiography, the grating-based technique provides a dark-field imaging modality, which utilizes the scattering properties of the x-rays. This modality has shown great potential for diagnosing early stage emphysema and fibrosis in mouse lungs in vivo. The CAD scheme is developed to assist radiologists and other medical experts to develop new diagnostic methods when evaluating grating-based images. The scheme consists of three stages: (i) automatic lung segmentation; (ii) feature extraction from lung shape and dark-field image intensities; (iii) classification between healthy, emphysema and fibrosis lungs. A study of 102 mice was conducted with 34 healthy, 52 emphysema and 16 fibrosis subjects. Each image was manually annotated to build an experimental dataset. System performance was assessed by: (i) determining the quality of the segmentations; (ii) validating emphysema and fibrosis recognition by a linear support vector machine using leave-one-out cross-validation. In terms of segmentation quality, we obtained an overlap percentage (Ω) 92.63  ±  3.65%, Dice Similarity Coefficient (DSC) 89.74  ±  8.84% and Jaccard Similarity Coefficient 82.39  ±  12.62%. For classification, the accuracy, sensitivity and specificity of diseased lung recognition was 100%. Classification between emphysema and fibrosis resulted in an accuracy of 93%, whilst the sensitivity was 94% and specificity 88%. In addition to the automatic classification of lungs, deviation maps created by the CAD scheme provide a visual aid for medical experts to further assess the severity of pulmonary disease in the lung, and highlights regions affected.

Applications of patient-specific 3D printing in medicine.

PubMed

Heller, Martin; Bauer, Heide-Katharina; Goetze, Elisabeth; Gielisch, Matthias; Roth, Klaus E; Drees, Philipp; Maier, Gerrit S; Dorweiler, Bernhard; Ghazy, Ahmed; Neufurth, Meik; Müller, Werner E G; Schröder, Heinz C; Wang, Xiaohong; Vahl, Christian-Friedrich; Al-Nawas, Bilal

Already three decades ago, the potential of medical 3D printing (3DP) or rapid prototyping for improved patient treatment began to be recognized. Since then, more and more medical indications in different surgical disciplines have been improved by using this new technique. Numerous examples have demonstrated the enormous benefit of 3DP in the medical care of patients by, for example, planning complex surgical interventions preoperatively, reducing implantation steps and anesthesia times, and helping with intraoperative orientation. At the beginning of every individual 3D model, patient-specific data on the basis of computed tomography (CT), magnetic resonance imaging (MRI), or ultrasound data is generated, which is then digitalized and processed using computer-aided design/computer-aided manufacturing (CAD/CAM) software. Finally, the resulting data sets are used to generate 3D-printed models or even implants. There are a variety of different application areas in the various medical fields, eg, drill or positioning templates, or surgical guides in maxillofacial surgery, or patient-specific implants in orthopedics. Furthermore, in vascular surgery it is possible to visualize pathologies such as aortic aneurysms so as to improve the planning of surgical treatment. Although rapid prototyping of individual models and implants is already applied very successfully in regenerative medicine, most of the materials used for 3DP are not yet suitable for implantation in the body. Therefore, it will be necessary in future to develop novel therapy approaches and design new materials in order to completely reconstruct natural tissue.

Wind-US Flow Calculations for the M2129 S-Duct Using Structured and Unstructured Grids

NASA Technical Reports Server (NTRS)

Mohler, Stanley R., Jr.

2003-01-01

Computational Fluid Dynamics (CFD) flow solutions for the M2129 diffusing S-duct with and without vane effectors were computed by the Wind-US flow solver. Both structured and unstructured 3-D grids were used. Without vane effectors, the duct exhibited massive flow separation in both experiment and CFD. With vane effectors installed, the flow remained attached and aerodynamic losses were reduced. Total pressure recovery and distortion near the duct outlet were computed from the solutions and compared favorably to experimental values. These calculations are part of a validation effort for the Wind-US code. They also provide an example case to aid engineers in learning to use the Wind-US software.

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.

Digital ocular fundus imaging: a review.

PubMed

Bernardes, Rui; Serranho, Pedro; Lobo, Conceição

2011-01-01

Ocular fundus imaging plays a key role in monitoring the health status of the human eye. Currently, a large number of imaging modalities allow the assessment and/or quantification of ocular changes from a healthy status. This review focuses on the main digital fundus imaging modality, color fundus photography, with a brief overview of complementary techniques, such as fluorescein angiography. While focusing on two-dimensional color fundus photography, the authors address the evolution from nondigital to digital imaging and its impact on diagnosis. They also compare several studies performed along the transitional path of this technology. Retinal image processing and analysis, automated disease detection and identification of the stage of diabetic retinopathy (DR) are addressed as well. The authors emphasize the problems of image segmentation, focusing on the major landmark structures of the ocular fundus: the vascular network, optic disk and the fovea. Several proposed approaches for the automatic detection of signs of disease onset and progression, such as microaneurysms, are surveyed. A thorough comparison is conducted among different studies with regard to the number of eyes/subjects, imaging modality, fundus camera used, field of view and image resolution to identify the large variation in characteristics from one study to another. Similarly, the main features of the proposed classifications and algorithms for the automatic detection of DR are compared, thereby addressing computer-aided diagnosis and computer-aided detection for use in screening programs. Copyright © 2011 S. Karger AG, Basel.

Academic consortium for the evaluation of computer-aided diagnosis (CADx) in mammography

NASA Astrophysics Data System (ADS)

Mun, Seong K.; Freedman, Matthew T.; Wu, Chris Y.; Lo, Shih-Chung B.; Floyd, Carey E., Jr.; Lo, Joseph Y.; Chan, Heang-Ping; Helvie, Mark A.; Petrick, Nicholas; Sahiner, Berkman; Wei, Datong; Chakraborty, Dev P.; Clarke, Laurence P.; Kallergi, Maria; Clark, Bob; Kim, Yongmin

1995-04-01

Computer aided diagnosis (CADx) is a promising technology for the detection of breast cancer in screening mammography. A number of different approaches have been developed for CADx research that have achieved significant levels of performance. Research teams now recognize the need for a careful and detailed evaluation study of approaches to accelerate the development of CADx, to make CADx more clinically relevant and to optimize the CADx algorithms based on unbiased evaluations. The results of such a comparative study may provide each of the participating teams with new insights into the optimization of their individual CADx algorithms. This consortium of experienced CADx researchers is working as a group to compare results of the algorithms and to optimize the performance of CADx algorithms by learning from each other. Each institution will be contributing an equal number of cases that will be collected under a standard protocol for case selection, truth determination, and data acquisition to establish a common and unbiased database for the evaluation study. An evaluation procedure for the comparison studies are being developed to analyze the results of individual algorithms for each of the test cases in the common database. Optimization of individual CADx algorithms can be made based on the comparison studies. The consortium effort is expected to accelerate the eventual clinical implementation of CADx algorithms at participating institutions.

Evaluation of image compression for computer-aided diagnosis of breast tumors in 3D sonography

NASA Astrophysics Data System (ADS)

Chen, We-Min; Huang, Yu-Len; Tao, Chi-Chuan; Chen, Dar-Ren; Moon, Woo-Kyung

2006-03-01

Medical imaging examinations form the basis for physicians diagnosing diseases, as evidenced by the increasing use of digital medical images for picture archiving and communications systems (PACS). However, with enlarged medical image databases and rapid growth of patients' case reports, PACS requires image compression to accelerate the image transmission rate and conserve disk space for diminishing implementation costs. For this purpose, JPEG and JPEG2000 have been accepted as legal formats for the digital imaging and communications in medicine (DICOM). The high compression ratio is felt to be useful for medical imagery. Therefore, this study evaluates the compression ratios of JPEG and JPEG2000 standards for computer-aided diagnosis (CAD) of breast tumors in 3-D medical ultrasound (US) images. The 3-D US data sets with various compression ratios are compressed using the two efficacious image compression standards. The reconstructed data sets are then diagnosed by a previous proposed CAD system. The diagnostic accuracy is measured based on receiver operating characteristic (ROC) analysis. Namely, the ROC curves are used to compare the diagnostic performance of two or more reconstructed images. Analysis results ensure a comparison of the compression ratios by using JPEG and JPEG2000 for 3-D US images. Results of this study provide the possible bit rates using JPEG and JPEG2000 for 3-D breast US images.

Web-based computer-aided-diagnosis (CAD) system for bone age assessment (BAA) of children

NASA Astrophysics Data System (ADS)

Zhang, Aifeng; Uyeda, Joshua; Tsao, Sinchai; Ma, Kevin; Vachon, Linda A.; Liu, Brent J.; Huang, H. K.

2008-03-01

Bone age assessment (BAA) of children is a clinical procedure frequently performed in pediatric radiology to evaluate the stage of skeletal maturation based on a left hand and wrist radiograph. The most commonly used standard: Greulich and Pyle (G&P) Hand Atlas was developed 50 years ago and exclusively based on Caucasian population. Moreover, inter- & intra-observer discrepancies using this method create a need of an objective and automatic BAA method. A digital hand atlas (DHA) has been collected with 1,400 hand images of normal children from Asian, African American, Caucasian and Hispanic descends. Based on DHA, a fully automatic, objective computer-aided-diagnosis (CAD) method was developed and it was adapted to specific population. To bring DHA and CAD method to the clinical environment as a useful tool in assisting radiologist to achieve higher accuracy in BAA, a web-based system with direct connection to a clinical site is designed as a novel clinical implementation approach for online and real time BAA. The core of the system, a CAD server receives the image from clinical site, processes it by the CAD method and finally, generates report. A web service publishes the results and radiologists at the clinical site can review it online within minutes. This prototype can be easily extended to multiple clinical sites and will provide the foundation for broader use of the CAD system for BAA.

Diagnosis of Diabetes Mellitus by Extraction of Morphological Features of Red Blood Cells Using an Artificial Neural Network.

PubMed

Palanisamy, Vinupritha; Mariamichael, Anburajan

2016-10-01

Background and Aim: Diabetes mellitus is a metabolic disorder characterized by varying hyperglycemias either due to insufficient secretion of insulin by the pancreas or improper utilization of glucose. The study was aimed to investigate the association of morphological features of erythrocytes among normal and diabetic subjects and its gender-based changes and thereby to develop a computer aided tool to diagnose diabetes using features extracted from RBC. Materials and Methods: The study involved 138 normal and 144 diabetic subjects. The blood was drawn from the subjects and the blood smear prepared was digitized using Zeiss fluorescent microscope. The digitized images were pre-processed and texture segmentation was performed to extract the various morphological features. The Pearson correlation test was performed and subsequently, classification of subjects as normal and diabetes was carried out by a neural network classifier based on the features that demonstrated significance at the level of P <0.05. Result: The proposed system demonstrated an overall accuracy, sensitivity, specificity, positive predictive value and negative predictive value of 93.3, 93.71, 92.8, 93.1 and 93.5% respectively. Conclusion: The morphological features exhibited a statistically significant difference (P<0.01) between the normal and diabetic cells, suggesting that it could be helpful in the diagnosis of Diabetes mellitus using a computer aided system. © Georg Thieme Verlag KG Stuttgart · New York.

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 diagnosis with textural features for breast lesions in sonograms.

PubMed

Chen, Dar-Ren; Huang, Yu-Len; Lin, Sheng-Hsiung

2011-04-01

Computer-aided diagnosis (CAD) systems provided second beneficial support reference and enhance the diagnostic accuracy. This paper was aimed to develop and evaluate a CAD with texture analysis in the classification of breast tumors for ultrasound images. The ultrasound (US) dataset evaluated in this study composed of 1020 sonograms of region of interest (ROI) subimages from 255 patients. Two-view sonogram (longitudinal and transverse views) and four different rectangular regions were utilized to analyze each tumor. Six practical textural features from the US images were performed to classify breast tumors as benign or malignant. However, the textural features always perform as a high dimensional vector; high dimensional vector is unfavorable to differentiate breast tumors in practice. The principal component analysis (PCA) was used to reduce the dimension of textural feature vector and then the image retrieval technique was performed to differentiate between benign and malignant tumors. In the experiments, all the cases were sampled with k-fold cross-validation (k=10) to evaluate the performance with receiver operating characteristic (ROC) curve. The area (A(Z)) under the ROC curve for the proposed CAD system with the specific textural features was 0.925±0.019. The classification ability for breast tumor with textural information is satisfactory. This system differentiates benign from malignant breast tumors with a good result and is therefore clinically useful to provide a second opinion. Copyright © 2010 Elsevier Ltd. All rights reserved.

Analysis of Experimental Investigations of the Planing Process of the Surface of Water

NASA Technical Reports Server (NTRS)

Sottorf, W.

1944-01-01

Pressure distribution and spray measurements were carried out on rectangular flat and V-bottom planing surfaces. Lift, resistance, and center of pressure data are analyzed and it is shown how these values may be computed for the pure planing procees of a flat or V-bottom suface of arbitrary beam, load and speed, the method being illustrated with the aid of an example.

Computer Aided System for Developing Aircrew Training (CASDAT).

DTIC Science & Technology

1983-03-01

sequence of training within the phase of training. An example lesson code and title is: FAPA 20 fuel system The lesson reference number can be...syllabus. Some typical titles and their sequence numbers are: FAPA 20 Fuel System FAPA 40 Power Plant System FAPA 60 Hydraulic System FAPA 80...portion of the syllabus worksheet. 59 NAVTRAEQUIPCEN 79-C-0076-1 SYLLABUS WORKSHEET *** FAPA 20 NORMAL COMMUNCATIONS VT-VIDEO TAPE NIL-MEDIATED

Digitizing for Computer-Aided Finite Element Model Generation.

DTIC Science & Technology

1979-10-10

this approach is a collection of programs developed over the last eight years at the University of Arizona, and called the GIFTS system. This paper...briefly describes the latest version of the system, GIFTS -5, and demonstrates its suitability in a design environment by simple examples. The programs...constituting the GIFTS system were used as a tool for research in many areas, including mesh generation, finite element data base design, interactive

Candidate R&D Thrusts for the Software Technology Initiative.

DTIC Science & Technology

1981-05-01

computer-aided design and manufacturing efforts provide examples of multiple representations and multiple manipulation modes. R&D difficulties exist in...farfetched, but the potential payoffs are enormous. References Birk, J., and R. Kelley. Research Needed to Advance the State of Knowledge in Robotics . In...and specifica- tion languages would be benefical . This R&D effort may also result in fusion with management tools with which an acquisition manager

Artificial intelligence programming languages for computer aided manufacturing

NASA Technical Reports Server (NTRS)

Rieger, C.; Samet, H.; Rosenberg, J.

1979-01-01

Eight Artificial Intelligence programming languages (SAIL, LISP, MICROPLANNER, CONNIVER, MLISP, POP-2, AL, and QLISP) are presented and surveyed, with examples of their use in an automated shop environment. Control structures are compared, and distinctive features of each language are highlighted. A simple programming task is used to illustrate programs in SAIL, LISP, MICROPLANNER, and CONNIVER. The report assumes reader knowledge of programming concepts, but not necessarily of the languages surveyed.

Computer-aided system for diagnosing thyroid nodules on ultrasound: A comparison with radiologist-based clinical assessments.

PubMed

Gao, Luying; Liu, Ruyu; Jiang, Yuxin; Song, Wenfeng; Wang, Ying; Liu, Jia; Wang, Juanjuan; Wu, Dongqian; Li, Shuai; Hao, Aimin; Zhang, Bo

2018-04-01

The purpose of this study was to compare the diagnostic efficiency of a thyroid ultrasound computer-aided diagnosis (CAD) system with that of 1 radiologist. This study retrospectively reviewed 342 surgically resected thyroid nodules from July 2013 to December 2013 at our center. The nodules were assessed on typical ultrasound images using the CAD system and reviewed by 1 experienced radiologist. The radiologist stratified the risk of malignancy using the Thyroid Imaging Reporting and Data Systems (TIRADS) and the American Thyroid Association (ATA) guidelines. The radiologist, using TI-RADS and ATA guidelines, performed better than the CAD system (P < .01). The sensitivity of the CAD system was similar to that of an experienced radiologist (P > .05; P < .01; and P > .05). However, we found that the CAD system had lower specificity (P < .01). The sensitivity of a thyroid ultrasound CAD system in differentiating nodules was similar to that of an experienced radiologist. However, the CAD system had lower specificity. © 2017 Wiley Periodicals, Inc.

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.

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

Histological Image Feature Mining Reveals Emergent Diagnostic Properties for Renal Cancer

PubMed Central

Kothari, Sonal; Phan, John H.; Young, Andrew N.; Wang, May D.

2016-01-01

Computer-aided histological image classification systems are important for making objective and timely cancer diagnostic decisions. These systems use combinations of image features that quantify a variety of image properties. Because researchers tend to validate their diagnostic systems on specific cancer endpoints, it is difficult to predict which image features will perform well given a new cancer endpoint. In this paper, we define a comprehensive set of common image features (consisting of 12 distinct feature subsets) that quantify a variety of image properties. We use a data-mining approach to determine which feature subsets and image properties emerge as part of an “optimal” diagnostic model when applied to specific cancer endpoints. Our goal is to assess the performance of such comprehensive image feature sets for application to a wide variety of diagnostic problems. We perform this study on 12 endpoints including 6 renal tumor subtype endpoints and 6 renal cancer grade endpoints. Keywords-histology, image mining, computer-aided diagnosis PMID:28163980

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 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.

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.

Lung lobe segmentation based on statistical atlas and graph cuts

NASA Astrophysics Data System (ADS)

Nimura, Yukitaka; Kitasaka, Takayuki; Honma, Hirotoshi; Takabatake, Hirotsugu; Mori, Masaki; Natori, Hiroshi; Mori, Kensaku

2012-03-01

This paper presents a novel method that can extract lung lobes by utilizing probability atlas and multilabel graph cuts. Information about pulmonary structures plays very important role for decision of the treatment strategy and surgical planning. The human lungs are divided into five anatomical regions, the lung lobes. Precise segmentation and recognition of lung lobes are indispensable tasks in computer aided diagnosis systems and computer aided surgery systems. A lot of methods for lung lobe segmentation are proposed. However, these methods only target the normal cases. Therefore, these methods cannot extract the lung lobes in abnormal cases, such as COPD cases. To extract lung lobes in abnormal cases, this paper propose a lung lobe segmentation method based on probability atlas of lobe location and multilabel graph cuts. The process consists of three components; normalization based on the patient's physique, probability atlas generation, and segmentation based on graph cuts. We apply this method to six cases of chest CT images including COPD cases. Jaccard index was 79.1%.

Addition of flexible body option to the TOLA computer program, part 1

NASA Technical Reports Server (NTRS)

Dick, J. W.; Benda, B. J.

1975-01-01

This report describes a flexible body option that was developed and added to the Takeoff and Landing Analysis (TOLA) computer program. The addition of the flexible body option to TOLA allows it to be used to study essentially any conventional type airplane in the ground operating environment. It provides the capability to predict the total motion of selected points on the analytical methods incorporated in the program and operating instructions for the option are described. A program listing is included along with several example problems to aid in interpretation of the operating instructions and to illustrate program usage.

Sizing of complex structure by the integration of several different optimal design algorithms

NASA Technical Reports Server (NTRS)

Sobieszczanski, J.

1974-01-01

Practical design of large-scale structures can be accomplished with the aid of the digital computer by bringing together in one computer program algorithms of nonlinear mathematical programing and optimality criteria with weight-strength and other so-called engineering methods. Applications of this approach to aviation structures are discussed with a detailed description of how the total problem of structural sizing can be broken down into subproblems for best utilization of each algorithm and for efficient organization of the program into iterative loops. Typical results are examined for a number of examples.

Computational Modeling in Plasma Processing for 300 mm Wafers

NASA Technical Reports Server (NTRS)

Meyyappan, Meyya; Arnold, James O. (Technical Monitor)

1997-01-01

Migration toward 300 mm wafer size has been initiated recently due to process economics and to meet future demands for integrated circuits. A major issue facing the semiconductor community at this juncture is development of suitable processing equipment, for example, plasma processing reactors that can accomodate 300 mm wafers. In this Invited Talk, scaling of reactors will be discussed with the aid of computational fluid dynamics results. We have undertaken reactor simulations using CFD with reactor geometry, pressure, and precursor flow rates as parameters in a systematic investigation. These simulations provide guidelines for scaling up in reactor design.

Bridging CAGD knowledge into CAD/CG applications: Mathematical theories as stepping stones of innovations

NASA Astrophysics Data System (ADS)

Gobithaasan, R. U.; Miura, Kenjiro T.; Hassan, Mohamad Nor

2014-07-01

Computer Aided Geometric Design (CAGD) which surpasses the underlying theories of Computer Aided Design (CAD) and Computer Graphics (CG) has been taught in a number of Malaysian universities under the umbrella of Mathematical Sciences' faculty/department. On the other hand, CAD/CG is taught either under the Engineering or Computer Science Faculty. Even though CAGD researchers/educators/students (denoted as contributors) have been enriching this field of study by means of article/journal publication, many fail to convert the idea into constructive innovation due to the gap that occurs between CAGD contributors and practitioners (engineers/product/designers/architects/artists). This paper addresses this issue by advocating a number of technologies that can be used to transform CAGD contributors into innovators where immediate impact in terms of practical application can be experienced by the CAD/CG practitioners. The underlying principle of solving this issue is twofold. First would be to expose the CAGD contributors on ways to turn mathematical ideas into plug-ins and second is to impart relevant CAGD theories to CAD/CG to practitioners. Both cases are discussed in detail and the final section shows examples to illustrate the importance of turning mathematical knowledge into innovations.

Survival after diagnosis of AIDS: a prospective observational study of 2625 patients. Royal Free/Chelsea and Westminster Hospitals Collaborative Group.

PubMed Central

Mocroft, A.; Youle, M.; Morcinek, J.; Sabin, C. A.; Gazzard, B.; Johnson, M. A.; Phillips, A. N.

1997-01-01

OBJECTIVE: To estimate median survival and changes in survival in patients diagnosed as having AIDS. DESIGN: Prospective observational study. SETTING: Clinics in two large London hospitals. SUBJECTS: 2625 patients with AIDS seen between 1982 and July 1995. MAIN OUTCOME MEASURES: Survival, estimated using lifetable analyses, and factors associated with survival, identified from Cox proportional hazards models. RESULTS: Median survival (20 months) was longer than previous estimates. The CD4 lymphocyte count at or before initial AIDS defining illness decreased significantly over time from 90 x 10(6)/1 during 1987 or earlier to 40 x 10(6)/1 during 1994 and 1995 (P < 0.0001). In the first three months after diagnosis, patients in whom AIDS was diagnosed after 1987 had a much lower risk of death (relative risk 0.44, 95% confidence interval 0.22 to 0.86; P = 0.017) than patients diagnosed before 1987. When the diagnosis was based on oesophageal candidiasis or Kaposi's sarcoma, patients had a lower risk of death than when the diagnosis was based on Pneumocystis carinii pneumonia (0.21 (0.07 to 0.59). P = 0.0030 and 0.37 (0.16 to 0.83), P = 0.016). Three months after AIDS diagnosis, the risk of death was similar in patients whose diagnosis was made after and before 1987 (1.02 (0.79 to 1.31), P = 0.91). There were no differences in survival between patients diagnosed during 1988-90, 1991-3, or 1994-5. CONCLUSIONS: In later years, patients were much more likely to survive their initial illness, but long term survival has remained poor. The decrease in CD4 lymphocyte count at AIDS diagnosis indicates that patients are being diagnosed as having AIDS at ever more advanced stages of immunodeficiency. PMID:9040386

[30 years since the first AIDS cases were reported: history and the present part III].

PubMed

Brůčková, Marie

2012-12-01

The end of the article features the development of HIV/AIDS diagnosis and its implementation in the Czech Republic. The establishment of the National Reference Laboratory for AIDS (NRL AIDS) at the National Institute of Public Health late in 1985 is mentioned and its responsibilities as the methodology centre in the areas of HIV/AIDS laboratory diagnosis and epidemiology are specified. In cooperation with the respective experts, a pilot HIV/AIDS prevalence study was conducted in the Czech Republic. The general criteria for HIV/AIDS laboratory diagnosis were set for both blood transfusion service and microbiology laboratories. Early in 1987, mass screening of blood donors was introduced in blood transfusion centres and in the second half of the same year, the HIV screening program was extended to selected microbiology laboratories. The NRL AIDS established a unified data reporting system, analyzed the results at the national level, and since 1989, has been reporting the outcomes to the international AIDS, and later HIV/AIDS, reporting system. The NRL AIDS also participated in a number of international projects in the areas of the research and development of laboratory techniques and epidemiological surveillance.

Automatic glaucoma diagnosis through medical imaging informatics.

PubMed

Liu, Jiang; Zhang, Zhuo; Wong, Damon Wing Kee; Xu, Yanwu; Yin, Fengshou; Cheng, Jun; Tan, Ngan Meng; Kwoh, Chee Keong; Xu, Dong; Tham, Yih Chung; Aung, Tin; Wong, Tien Yin

2013-01-01

Computer-aided diagnosis for screening utilizes computer-based analytical methodologies to process patient information. Glaucoma is the leading irreversible cause of blindness. Due to the lack of an effective and standard screening practice, more than 50% of the cases are undiagnosed, which prevents the early treatment of the disease. To design an automatic glaucoma diagnosis architecture automatic glaucoma diagnosis through medical imaging informatics (AGLAIA-MII) that combines patient personal data, medical retinal fundus image, and patient's genome information for screening. 2258 cases from a population study were used to evaluate the screening software. These cases were attributed with patient personal data, retinal images and quality controlled genome data. Utilizing the multiple kernel learning-based classifier, AGLAIA-MII, combined patient personal data, major image features, and important genome single nucleotide polymorphism (SNP) features. Receiver operating characteristic curves were plotted to compare AGLAIA-MII's performance with classifiers using patient personal data, images, and genome SNP separately. AGLAIA-MII was able to achieve an area under curve value of 0.866, better than 0.551, 0.722 and 0.810 by the individual personal data, image and genome information components, respectively. AGLAIA-MII also demonstrated a substantial improvement over the current glaucoma screening approach based on intraocular pressure. AGLAIA-MII demonstrates for the first time the capability of integrating patients' personal data, medical retinal image and genome information for automatic glaucoma diagnosis and screening in a large dataset from a population study. It paves the way for a holistic approach for automatic objective glaucoma diagnosis and screening.

Computer-Aided Molecular Design of Bis-phosphine Oxide Lanthanide Extractants

DOE PAGES

McCann, Billy W.; Silva, Nuwan De; Windus, Theresa L.; ...

2016-02-17

Computer-aided molecular design and high-throughput screening of viable host architectures can significantly reduce the efforts in the design of novel ligands for efficient extraction of rare earth elements. This paper presents a computational approach to the deliberate design of bis-phosphine oxide host architectures that are structurally organized for complexation of trivalent lanthanides. Molecule building software, HostDesigner, was interfaced with molecular mechanics software, PCModel, providing a tool for generating and screening millions of potential R 2(O)P-link-P(O)R 2 ligand geometries. The molecular mechanics ranking of ligand structures is consistent with both the solution-phase free energies of complexation obtained with density functional theorymore » and the performance of known bis-phosphine oxide extractants. For the case where link is -CH 2-, evaluation of the ligand geometry provides the first characterization of a steric origin for the ‘anomalous aryl strengthening’ effect. The design approach has identified a number of novel bis-phosphine oxide ligands that are better organized for lanthanide complexation than previously studied examples.« less

Computer-aided diagnosis of lung cancer: the effect of training data sets on classification accuracy of lung nodules.

PubMed

Gong, Jing; Liu, Ji-Yu; Sun, Xi-Wen; Zheng, Bin; Nie, Sheng-Dong

2018-02-05

This study aims to develop a computer-aided diagnosis (CADx) scheme for classification between malignant and benign lung nodules, and also assess whether CADx performance changes in detecting nodules associated with early and advanced stage lung cancer. The study involves 243 biopsy-confirmed pulmonary nodules. Among them, 76 are benign, 81 are stage I and 86 are stage III malignant nodules. The cases are separated into three data sets involving: (1) all nodules, (2) benign and stage I malignant nodules, and (3) benign and stage III malignant nodules. A CADx scheme is applied to segment lung nodules depicted on computed tomography images and we initially computed 66 3D image features. Then, three machine learning models namely, a support vector machine, naïve Bayes classifier and linear discriminant analysis, are separately trained and tested by using three data sets and a leave-one-case-out cross-validation method embedded with a Relief-F feature selection algorithm. When separately using three data sets to train and test three classifiers, the average areas under receiver operating characteristic curves (AUC) are 0.94, 0.90 and 0.99, respectively. When using the classifiers trained using data sets with all nodules, average AUC values are 0.88 and 0.99 for detecting early and advanced stage nodules, respectively. AUC values computed from three classifiers trained using the same data set are consistent without statistically significant difference (p  >  0.05). This study demonstrates (1) the feasibility of applying a CADx scheme to accurately distinguish between benign and malignant lung nodules, and (2) a positive trend between CADx performance and cancer progression stage. Thus, in order to increase CADx performance in detecting subtle and early cancer, training data sets should include more diverse early stage cancer cases.

Computer-aided diagnosis of lung cancer: the effect of training data sets on classification accuracy of lung nodules

NASA Astrophysics Data System (ADS)

Gong, Jing; Liu, Ji-Yu; Sun, Xi-Wen; Zheng, Bin; Nie, Sheng-Dong

2018-02-01

This study aims to develop a computer-aided diagnosis (CADx) scheme for classification between malignant and benign lung nodules, and also assess whether CADx performance changes in detecting nodules associated with early and advanced stage lung cancer. The study involves 243 biopsy-confirmed pulmonary nodules. Among them, 76 are benign, 81 are stage I and 86 are stage III malignant nodules. The cases are separated into three data sets involving: (1) all nodules, (2) benign and stage I malignant nodules, and (3) benign and stage III malignant nodules. A CADx scheme is applied to segment lung nodules depicted on computed tomography images and we initially computed 66 3D image features. Then, three machine learning models namely, a support vector machine, naïve Bayes classifier and linear discriminant analysis, are separately trained and tested by using three data sets and a leave-one-case-out cross-validation method embedded with a Relief-F feature selection algorithm. When separately using three data sets to train and test three classifiers, the average areas under receiver operating characteristic curves (AUC) are 0.94, 0.90 and 0.99, respectively. When using the classifiers trained using data sets with all nodules, average AUC values are 0.88 and 0.99 for detecting early and advanced stage nodules, respectively. AUC values computed from three classifiers trained using the same data set are consistent without statistically significant difference (p  >  0.05). This study demonstrates (1) the feasibility of applying a CADx scheme to accurately distinguish between benign and malignant lung nodules, and (2) a positive trend between CADx performance and cancer progression stage. Thus, in order to increase CADx performance in detecting subtle and early cancer, training data sets should include more diverse early stage cancer cases.

Is AIDS a Biasing Factor in Teacher Judgment?

ERIC Educational Resources Information Center

Walker, David W.; Hulecki, Mary B.

1989-01-01

Regular-education, third-grade teachers (n=91) in Indiana reviewed one of two psychological reports, identical except that one reported a diagnosis of Acquired Immune Deficiency Syndrome (AIDS) and one reported a diagnosis of rheumatic fever. AIDS was not found to be a biasing factor in teachers' judgments regarding special education placement.…

Standardized evaluation of algorithms for computer-aided diagnosis of dementia based on structural MRI: the CADDementia challenge.

PubMed

Bron, Esther E; Smits, Marion; van der Flier, Wiesje M; Vrenken, Hugo; Barkhof, Frederik; Scheltens, Philip; Papma, Janne M; Steketee, Rebecca M E; Méndez Orellana, Carolina; Meijboom, Rozanna; Pinto, Madalena; Meireles, Joana R; Garrett, Carolina; Bastos-Leite, António J; Abdulkadir, Ahmed; Ronneberger, Olaf; Amoroso, Nicola; Bellotti, Roberto; Cárdenas-Peña, David; Álvarez-Meza, Andrés M; Dolph, Chester V; Iftekharuddin, Khan M; Eskildsen, Simon F; Coupé, Pierrick; Fonov, Vladimir S; Franke, Katja; Gaser, Christian; Ledig, Christian; Guerrero, Ricardo; Tong, Tong; Gray, Katherine R; Moradi, Elaheh; Tohka, Jussi; Routier, Alexandre; Durrleman, Stanley; Sarica, Alessia; Di Fatta, Giuseppe; Sensi, Francesco; Chincarini, Andrea; Smith, Garry M; Stoyanov, Zhivko V; Sørensen, Lauge; Nielsen, Mads; Tangaro, Sabina; Inglese, Paolo; Wachinger, Christian; Reuter, Martin; van Swieten, John C; Niessen, Wiro J; Klein, Stefan

2015-05-01

Algorithms for computer-aided diagnosis of dementia based on structural MRI have demonstrated high performance in the literature, but are difficult to compare as different data sets and methodology were used for evaluation. In addition, it is unclear how the algorithms would perform on previously unseen data, and thus, how they would perform in clinical practice when there is no real opportunity to adapt the algorithm to the data at hand. To address these comparability, generalizability and clinical applicability issues, we organized a grand challenge that aimed to objectively compare algorithms based on a clinically representative multi-center data set. Using clinical practice as the starting point, the goal was to reproduce the clinical diagnosis. Therefore, we evaluated algorithms for multi-class classification of three diagnostic groups: patients with probable Alzheimer's disease, patients with mild cognitive impairment and healthy controls. The diagnosis based on clinical criteria was used as reference standard, as it was the best available reference despite its known limitations. For evaluation, a previously unseen test set was used consisting of 354 T1-weighted MRI scans with the diagnoses blinded. Fifteen research teams participated with a total of 29 algorithms. The algorithms were trained on a small training set (n=30) and optionally on data from other sources (e.g., the Alzheimer's Disease Neuroimaging Initiative, the Australian Imaging Biomarkers and Lifestyle flagship study of aging). The best performing algorithm yielded an accuracy of 63.0% and an area under the receiver-operating-characteristic curve (AUC) of 78.8%. In general, the best performances were achieved using feature extraction based on voxel-based morphometry or a combination of features that included volume, cortical thickness, shape and intensity. The challenge is open for new submissions via the web-based framework: http://caddementia.grand-challenge.org. Copyright © 2015 Elsevier Inc. All rights reserved.

Extended Wordsearches in Chemistry

NASA Astrophysics Data System (ADS)

Cotton, Simon

1998-04-01

Students can be encouraged to develop their factual knowledge by use of puzzles. One strategy described here is the extended wordsearch, where the wordsearch element generates a number of words or phrases from which the answers to a series of questions are selected. The wordsearch can be generated with the aid of computer programs, though in order to make them suitable for students with dyslexia or other learning difficulties, a simpler form is more appropriate. These problems can be employed in a variety of contexts, for example, as topic tests and classroom end-of-lesson fillers. An example is provided in the area of calcium chemistry. Sources of suitable software are listed.

A review of fuzzy cognitive maps in medicine: Taxonomy, methods, and applications.

PubMed

Amirkhani, Abdollah; Papageorgiou, Elpiniki I; Mohseni, Akram; Mosavi, Mohammad R

2017-04-01

A high percentage of medical errors, committed because of physician's lack of experience, huge volume of data to be analyzed, and inaccessibility to medical records of previous patients, can be reduced using computer-aided techniques. Therefore, designing more efficient medical decision-support systems (MDSSs) to assist physicians in decision-making is crucially important. Through combining the properties of fuzzy logic and neural networks, fuzzy cognitive maps (FCMs) are among the latest, most efficient, and strongest artificial intelligence techniques for modeling complex systems. This review study is conducted to identify different FCM structures used in MDSS designs. The best structure for each medical application can be introduced by studying the properties of FCM structures. This paper surveys the most important decision- making methods and applications of FCMs in the medical field in recent years. To investigate the efficiency and capability of different FCM models in designing MDSSs, medical applications are categorized into four key areas: decision-making, diagnosis, prediction, and classification. Also, various diagnosis and decision support problems addressed by FCMs in recent years are reviewed with the goal of introducing different types of FCMs and determining their contribution to the improvements made in the fields of medical diagnosis and treatment. In this survey, a general trend for future studies in this field is provided by analyzing various FCM structures used for medical purposes, and the results from each category. Due to the unique specifications of FCMs in integrating human knowledge and experience with computer-aided techniques, they are among practical instruments for MDSS design. In the not too distant future, they will have a significant role in medical sciences. Copyright © 2017 Elsevier B.V. All rights reserved.

Continuous measurements of mandibular cortical width on dental panoramic radiographs for computer-aided diagnosis of osteoporosis

NASA Astrophysics Data System (ADS)

Kavitha, M. S.; Asano, Akira; Taguchi, Akira

2011-03-01

The aim of this study is to develop a computer-aided osteoporosis diagnosis system that automatically determines the inferior cortical width of the mandible continuously on dental panoramic radiographs to realize statistically more robust measurements than the conventional one-point measurements. The cortical width was continuously measured on dental panoramic radiographs by enhancing the original image, determining cortical boundaries, and finally evaluating the distance between boundaries continuously throughout the region of interest. The diagnostic performance using the average width calculated from the continuous measurement was compared with BMD at lumbar spine and femoral neck in 100 postmenopausal women of whom 50 to the development of the tool and 50 to its validation with no history of osteoporosis was evaluated. We experimentally showed the superiority of our method with improved sensitivity and specificity of identifying the development subjects were 90.0% and 75.0% in women with low spinal BMD and 81.8% and 69.2% in those with low femoral BMD, respectively. The corresponding values in the validation subjects were 93.3% and 82.9% at the lumbar spine and 92.3% and 75.7% at the femoral neck, respectively in terms of efficacy for diagnosing osteoporosis. We also assessed the diagnosis and classification of women with osteoporosis using support vector machine employing the average and variance of the continuous measurements gave excellent discrimination ability. It yields sensitivity and specificity of 90.9% and 83.8%, respectively with lumbar spine and 90.0% and 69.1%, respectively with femoral neck BMD. Performance comparison and simplicity of this method indicate that our computeraided system is readily applicable to clinical practice.

Breast Histopathological Image Retrieval Based on Latent Dirichlet Allocation.

PubMed

Ma, Yibing; Jiang, Zhiguo; Zhang, Haopeng; Xie, Fengying; Zheng, Yushan; Shi, Huaqiang; Zhao, Yu

2017-07-01

In the field of pathology, whole slide image (WSI) has become the major carrier of visual and diagnostic information. Content-based image retrieval among WSIs can aid the diagnosis of an unknown pathological image by finding its similar regions in WSIs with diagnostic information. However, the huge size and complex content of WSI pose several challenges for retrieval. In this paper, we propose an unsupervised, accurate, and fast retrieval method for a breast histopathological image. Specifically, the method presents a local statistical feature of nuclei for morphology and distribution of nuclei, and employs the Gabor feature to describe the texture information. The latent Dirichlet allocation model is utilized for high-level semantic mining. Locality-sensitive hashing is used to speed up the search. Experiments on a WSI database with more than 8000 images from 15 types of breast histopathology demonstrate that our method achieves about 0.9 retrieval precision as well as promising efficiency. Based on the proposed framework, we are developing a search engine for an online digital slide browsing and retrieval platform, which can be applied in computer-aided diagnosis, pathology education, and WSI archiving and management.

A cloud platform for remote diagnosis of breast cancer in mammography by fusion of machine and human intelligence

NASA Astrophysics Data System (ADS)

Jiang, Guodong; Fan, Ming; Li, Lihua

2016-03-01

Mammography is the gold standard for breast cancer screening, reducing mortality by about 30%. The application of a computer-aided detection (CAD) system to assist a single radiologist is important to further improve mammographic sensitivity for breast cancer detection. In this study, a design and realization of the prototype for remote diagnosis system in mammography based on cloud platform were proposed. To build this system, technologies were utilized including medical image information construction, cloud infrastructure and human-machine diagnosis model. Specifically, on one hand, web platform for remote diagnosis was established by J2EE web technology. Moreover, background design was realized through Hadoop open-source framework. On the other hand, storage system was built up with Hadoop distributed file system (HDFS) technology which enables users to easily develop and run on massive data application, and give full play to the advantages of cloud computing which is characterized by high efficiency, scalability and low cost. In addition, the CAD system was realized through MapReduce frame. The diagnosis module in this system implemented the algorithms of fusion of machine and human intelligence. Specifically, we combined results of diagnoses from doctors' experience and traditional CAD by using the man-machine intelligent fusion model based on Alpha-Integration and multi-agent algorithm. Finally, the applications on different levels of this system in the platform were also discussed. This diagnosis system will have great importance for the balanced health resource, lower medical expense and improvement of accuracy of diagnosis in basic medical institutes.

Survival Outcomes and Effect of Early vs. Deferred cART Among HIV-Infected Patients Diagnosed at the Time of an AIDS-Defining Event: A Cohort Analysis

PubMed Central

Mussini, Cristina; Johnson, Margaret; d'Arminio Monforte, Antonella; Antinori, Andrea; Gill, M. John; Sighinolfi, Laura; Uberti-Foppa, Caterina; Borghi, Vanni; Sabin, Caroline

2011-01-01

Objectives We analyzed clinical progression among persons diagnosed with HIV at the time of an AIDS-defining event, and assessed the impact on outcome of timing of combined antiretroviral treatment (cART). Methods Retrospective, European and Canadian multicohort study.. Patients were diagnosed with HIV from 1997–2004 and had clinical AIDS from 30 days before to 14 days after diagnosis. Clinical progression (new AIDS event, death) was described using Kaplan-Meier analysis stratifying by type of AIDS event. Factors associated with progression were identified with multivariable Cox regression. Progression rates were compared between those starting early (<30 days after AIDS event) or deferred (30–270 days after AIDS event) cART. Results The median (interquartile range) CD4 count and viral load (VL) at diagnosis of the 584 patients were 42 (16, 119) cells/µL and 5.2 (4.5, 5.7) log10 copies/mL. Clinical progression was observed in 165 (28.3%) patients. Older age, a higher VL at diagnosis, and a diagnosis of non-Hodgkin lymphoma (NHL) (vs. other AIDS events) were independently associated with disease progression. Of 366 patients with an opportunistic infection, 178 (48.6%) received early cART. There was no significant difference in clinical progression between those initiating cART early and those deferring treatment (adjusted hazard ratio 1.32 [95% confidence interval 0.87, 2.00], p = 0.20). Conclusions Older patients and patients with high VL or NHL at diagnosis had a worse outcome. Our data suggest that earlier initiation of cART may be beneficial among HIV-infected patients diagnosed with clinical AIDS in our setting. PMID:22043301

Intravital Computer Morphometry on Protozoa: A Method for Monitoring of the Morphofunctional Disorders in Cells Exposed in the Cell Phone Communication Electromagnetic Field.

PubMed

Uskalova, D V; Igolkina, Yu V; Sarapultseva, E I

2016-08-01

Morphofunctional disorders in unicellular aquatic protozoa - Spirostomum ambiguum infusorians after 30-, 60-, and 360-min exposure in electromagnetic field at a radiation frequency of 1 GHz and energy flow density of 50 μW/cm(2) were analyzed by intravital computer morphometry. Significant disorders in morphometric values correlated with low mobility of the protozoa. The results suggested the use of intravital computer morphometry on the protozoa for early diagnosis of radiation-induced effects of the mobile communication electromagnetic field, for example, low mobility of spermatozoa.

Impact of the mass media on calls to the CDC National AIDS Hotline.

PubMed

Fan, D P

1996-06-01

This paper considers new computer methodologies for assessing the impact of different types of public health information. The example used public service announcements (PSAs) and mass media news to predict the volume of attempts to call the CDC National AIDS Hotline from December 1992 through to the end of 1993. The analysis relied solely on data from electronic databases. Newspaper stories and television news transcripts were obtained from the NEXIS electronic database and were scored by machine for AIDS coverage. The PSA database was generated by computer monitoring of advertising distributed by the Centers for Disease Control and Prevention (CDC) and by others. The volume of call attempts was collected automatically by the public branch exchange (PBX) of the Hotline telephone system. The call attempts, the PSAs and the news story data were related to each other using both a standard time series method and the statistical model of ideodynamics. The analysis indicated that the only significant explanatory variable for the call attempts was PSAs produced by the CDC. One possible explanation was that these commercials all included the Hotline telephone number while the other information sources did not.

Computational modeling of cardiac hemodynamics: Current status and future outlook

NASA Astrophysics Data System (ADS)

Mittal, Rajat; Seo, Jung Hee; Vedula, Vijay; Choi, Young J.; Liu, Hang; Huang, H. Howie; Jain, Saurabh; Younes, Laurent; Abraham, Theodore; George, Richard T.

2016-01-01

The proliferation of four-dimensional imaging technologies, increasing computational speeds, improved simulation algorithms, and the widespread availability of powerful computing platforms is enabling simulations of cardiac hemodynamics with unprecedented speed and fidelity. Since cardiovascular disease is intimately linked to cardiovascular hemodynamics, accurate assessment of the patient's hemodynamic state is critical for the diagnosis and treatment of heart disease. Unfortunately, while a variety of invasive and non-invasive approaches for measuring cardiac hemodynamics are in widespread use, they still only provide an incomplete picture of the hemodynamic state of a patient. In this context, computational modeling of cardiac hemodynamics presents as a powerful non-invasive modality that can fill this information gap, and significantly impact the diagnosis as well as the treatment of cardiac disease. This article reviews the current status of this field as well as the emerging trends and challenges in cardiovascular health, computing, modeling and simulation and that are expected to play a key role in its future development. Some recent advances in modeling and simulations of cardiac flow are described by using examples from our own work as well as the research of other groups.

Analysis of Interval Changes on Mammograms for Computer Aided Diagnosis

DTIC Science & Technology

2000-05-01

tizer was calibrated so that the gray values were linearly and erage pixel values in the template and ROI, respectively. The inversely proportional to the...earlier for linearly and inversely proportional to the OD within the alignment of the breast regions, except that the regions to be range 0-4 OD...results versely proportional to the radial distance r from the nipple. in a decrease in the value of (to 20 mm. This decrease helps For the data set

On Interpreting Stereo Disparity

DTIC Science & Technology

1989-04-01

denominators shall now be examined in some detail. The term _," (R) can h, expanded (with the aid of double angle formulas) as -x[&(x,y) .(cos 20, sin 20...histogram computations: Expand eight- connectivity regions about a central pixel until the desired number of inputs have been scanned. In this example, it...takes two iterations of the algorithm to locate the second line segment. For this figure, line segments are depicted with black; expanding serach

Proceedings of the 1997 Space Control Conference, Volume 2

DTIC Science & Technology

1997-03-27

of attitude information are used in our orbit determination. The attitude history buffer on MSX holds quaternions and time tags at 100-second...being able to use the attitude quaternions , DYNAMO can also compute the park-mode attitude of MSX if, for example, some of the raw on-board attitude ... used to aid the target discrimination process. THE MSX SPACECRAFT The SBV sensor was launched on the BMDO supported MSX spacecraft on 24 April

A structurally oriented simulation system

NASA Technical Reports Server (NTRS)

Aran, Z.

1973-01-01

The computer program SOSS (Structurally Oriented Simulation System) is designed to be used as an experimental aid in the study of reliable systems. Basically, SOSS can simulate the structure and behavior of a discrete-time, finite-state, time-invariant system at various levels of structural definition. A general description of the program is given along with its modes of operation, command language of the basic system, future features to be incorporated in SOSS, and an example of usage.

Computer aided fringe pattern analysis

NASA Astrophysics Data System (ADS)

Sciammarella, Cesar A.

The paper reviews the basic laws of fringe pattern interpretation. The different techniques that are currently utilized are presented using a common frame of reference stressing the fact that these techniques are different variations of the same basic principle. Digital and analog techniques are discussed. Currently available hardware is presented and the relationships between hardware and the operations of pattern fringe processing are pointed out. Examples are given to illustrate the ideas discussed in the paper.

Dynamic simulation of Static Var Compensators in distribution systems

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

Koessler, R.J.

1992-08-01

This paper is a system study guide for the correction of voltage dips due to large motor startups with Static Var Compensators (SVCs). The method utilizes time simulations, which are an important aid in the equipment design and specification. The paper illustrates the process of setting-up a computer model and performing time simulations. The study process is demonstrated through an example, the Shawnee feeder in the Niagara Mohawk Power Corporation service area.

JPRS Report, Science & Technology, USSR: Electronics & Electrical Engineering.

DTIC Science & Technology

1988-02-23

calculations or design examples are cited in this purely theoretical treatment, it is noted that experimental data from an on-board microprocessor controlled ...The requirements placed on the design of the semiconductor devices used in such systems can be divided into two groups : 1) Assure the requisite...describes a computer-aided approach to the design of resonant arrays that results in equal losses in the on and off states of such control devices. An

A new 3D viewer as an interface between the ASDEX Upgrade CAD models and data from plasma modelling and experiment

NASA Astrophysics Data System (ADS)

Lunt, T.; Fuchs, J. C.; Mank, K.; Feng, Y.; Brochard, F.; Herrmann, A.; Rohde, V.; Endstrasser, N.; ASDEX Upgrade Team

2010-11-01

A generally available and easy-to-use viewer for the simultaneous visualisation of the ASDEX Upgrade vacuum vessel computer aided design models, diagnostics and magnetic geometry, solutions of 3D plasma simulation codes and 2D camera images was developed. Here we report on the working principle of this software and give several examples of its technical and scientific application.

Clinical MR-mammography: are computer-assisted methods superior to visual or manual measurements for curve type analysis? A systematic approach.

PubMed

Baltzer, Pascal Andreas Thomas; Freiberg, Christian; Beger, Sebastian; Vag, Tibor; Dietzel, Matthias; Herzog, Aimee B; Gajda, Mieczyslaw; Camara, Oumar; Kaiser, Werner A

2009-09-01

Enhancement characteristics after administration of a contrast agent are regarded as a major criterion for differential diagnosis in magnetic resonance mammography (MRM). However, no consensus exists about the best measurement method to assess contrast enhancement kinetics. This systematic investigation was performed to compare visual estimation with manual region of interest (ROI) and computer-aided diagnosis (CAD) analysis for time curve measurements in MRM. A total of 329 patients undergoing surgery after MRM (1.5 T) were analyzed prospectively. Dynamic data were measured using visual estimation, including ROI as well as CAD methods, and classified depending on initial signal increase and delayed enhancement. Pathology revealed 469 lesions (279 malignant, 190 benign). Kappa agreement between the methods ranged from 0.78 to 0.81. Diagnostic accuracies of 74.4% (visual), 75.7% (ROI), and 76.6% (CAD) were found without statistical significant differences. According to our results, curve type measurements are useful as a diagnostic criterion in breast lesions irrespective of the method used.

High-Throughput Histopathological Image Analysis via Robust Cell Segmentation and Hashing

PubMed Central

Zhang, Xiaofan; Xing, Fuyong; Su, Hai; Yang, Lin; Zhang, Shaoting

2015-01-01

Computer-aided diagnosis of histopathological images usually requires to examine all cells for accurate diagnosis. Traditional computational methods may have efficiency issues when performing cell-level analysis. In this paper, we propose a robust and scalable solution to enable such analysis in a real-time fashion. Specifically, a robust segmentation method is developed to delineate cells accurately using Gaussian-based hierarchical voting and repulsive balloon model. A large-scale image retrieval approach is also designed to examine and classify each cell of a testing image by comparing it with a massive database, e.g., half-million cells extracted from the training dataset. We evaluate this proposed framework on a challenging and important clinical use case, i.e., differentiation of two types of lung cancers (the adenocarcinoma and squamous carcinoma), using thousands of lung microscopic tissue images extracted from hundreds of patients. Our method has achieved promising accuracy and running time by searching among half-million cells. PMID:26599156

Computer-Aided Diagnosis of Micro-Malignant Melanoma Lesions Applying Support Vector Machines.

PubMed

Jaworek-Korjakowska, Joanna

2016-01-01

Background. One of the fatal disorders causing death is malignant melanoma, the deadliest form of skin cancer. The aim of the modern dermatology is the early detection of skin cancer, which usually results in reducing the mortality rate and less extensive treatment. This paper presents a study on classification of melanoma in the early stage of development using SVMs as a useful technique for data classification. Method. In this paper an automatic algorithm for the classification of melanomas in their early stage, with a diameter under 5 mm, has been presented. The system contains the following steps: image enhancement, lesion segmentation, feature calculation and selection, and classification stage using SVMs. Results. The algorithm has been tested on 200 images including 70 melanomas and 130 benign lesions. The SVM classifier achieved sensitivity of 90% and specificity of 96%. The results indicate that the proposed approach captured most of the malignant cases and could provide reliable information for effective skin mole examination. Conclusions. Micro-melanomas due to the small size and low advancement of development create enormous difficulties during the diagnosis even for experts. The use of advanced equipment and sophisticated computer systems can help in the early diagnosis of skin lesions.

[Cardiology for the veterinary practice--information processing with the help of a computer program, with a working example].

PubMed

Bohn, F K; Emmerichs, H; Müller, H

1991-06-01

Description of a PC-Program "Cardiology for the Veterinary Practice", title "Kardiag", with Illustrations and a report of a congenital heart disease in a one year old, male, Newfoundland dog, with the use of the described PC-Program. After euthanasia an autopsy was performed which verified the clinical diagnosis.

Estimation of salient regions related to chronic gastritis using gastric X-ray images.

PubMed

Togo, Ren; Ishihara, Kenta; Ogawa, Takahiro; Haseyama, Miki

2016-10-01

Since technical knowledge and a high degree of experience are necessary for diagnosis of chronic gastritis, computer-aided diagnosis (CAD) systems that analyze gastric X-ray images are desirable in the field of medicine. Therefore, a new method that estimates salient regions related to chronic gastritis/non-gastritis for supporting diagnosis is presented in this paper. In order to estimate salient regions related to chronic gastritis/non-gastritis, the proposed method monitors the distance between a target image feature and Support Vector Machine (SVM)-based hyperplane for its classification. Furthermore, our method realizes removal of the influence of regions outside the stomach by using positional relationships between the stomach and other organs. Consequently, since the proposed method successfully estimates salient regions of gastric X-ray images for which chronic gastritis and non-gastritis are unknown, visual support for inexperienced clinicians becomes feasible. Copyright © 2016 Elsevier Ltd. All rights reserved.

Mixture model-based clustering and logistic regression for automatic detection of microaneurysms in retinal images

NASA Astrophysics Data System (ADS)

Sánchez, Clara I.; Hornero, Roberto; Mayo, Agustín; García, María

2009-02-01

Diabetic Retinopathy is one of the leading causes of blindness and vision defects in developed countries. An early detection and diagnosis is crucial to avoid visual complication. Microaneurysms are the first ocular signs of the presence of this ocular disease. Their detection is of paramount importance for the development of a computer-aided diagnosis technique which permits a prompt diagnosis of the disease. However, the detection of microaneurysms in retinal images is a difficult task due to the wide variability that these images usually present in screening programs. We propose a statistical approach based on mixture model-based clustering and logistic regression which is robust to the changes in the appearance of retinal fundus images. The method is evaluated on the public database proposed by the Retinal Online Challenge in order to obtain an objective performance measure and to allow a comparative study with other proposed algorithms.

Computer-assisted versus conventional free fibula flap technique for craniofacial reconstruction: an outcomes comparison.

PubMed

Seruya, Mitchel; Fisher, Mark; Rodriguez, Eduardo D

2013-11-01

There has been rising interest in computer-aided design/computer-aided manufacturing for preoperative planning and execution of osseous free flap reconstruction. The purpose of this study was to compare outcomes between computer-assisted and conventional fibula free flap techniques for craniofacial reconstruction. A two-center, retrospective review was carried out on patients who underwent fibula free flap surgery for craniofacial reconstruction from 2003 to 2012. Patients were categorized by the type of reconstructive technique: conventional (between 2003 and 2009) or computer-aided design/computer-aided manufacturing (from 2010 to 2012). Demographics, surgical factors, and perioperative and long-term outcomes were compared. A total of 68 patients underwent microsurgical craniofacial reconstruction: 58 conventional and 10 computer-aided design and manufacturing fibula free flaps. By demographics, patients undergoing the computer-aided design/computer-aided manufacturing method were significantly older and had a higher rate of radiotherapy exposure compared with conventional patients. Intraoperatively, the median number of osteotomies was significantly higher (2.0 versus 1.0, p=0.002) and the median ischemia time was significantly shorter (120 minutes versus 170 minutes, p=0.004) for the computer-aided design/computer-aided manufacturing technique compared with conventional techniques; operative times were shorter for patients undergoing the computer-aided design/computer-aided manufacturing technique, although this did not reach statistical significance. Perioperative and long-term outcomes were equivalent for the two groups, notably, hospital length of stay, recipient-site infection, partial and total flap loss, and rate of soft-tissue and bony tissue revisions. Microsurgical craniofacial reconstruction using a computer-assisted fibula flap technique yielded significantly shorter ischemia times amidst a higher number of osteotomies compared with conventional techniques. Therapeutic, III.

Human identification based on cranial computed tomography scan — a case report

PubMed Central

Silva, RF; Botelho, TL; Prado, FB; Kawagushi, JT; Daruge Júnior, E; Bérzin, F

2011-01-01

Today, there is increasing use of CT scanning on a clinical basis, aiding in the diagnosis of diseases or injuries. This exam also provides important information that allows identification of individuals. This paper reports the use of a CT scan on the skull, taken when the victim was alive, for the positive identification of a victim of a traffic accident in which the fingerprint analysis was impossible. The authors emphasize that the CT scan is a tool primarily used in clinical diagnosis and may contribute significantly to forensic purpose, allowing the exploration of virtual corpses before the classic autopsy. The use of CT scans might increase the quantity and quality of information involved in the death of the person examined. PMID:21493883

Machine learning based detection of age-related macular degeneration (AMD) and diabetic macular edema (DME) from optical coherence tomography (OCT) images

PubMed Central

Wang, Yu; Zhang, Yaonan; Yao, Zhaomin; Zhao, Ruixue; Zhou, Fengfeng

2016-01-01

Non-lethal macular diseases greatly impact patients’ life quality, and will cause vision loss at the late stages. Visual inspection of the optical coherence tomography (OCT) images by the experienced clinicians is the main diagnosis technique. We proposed a computer-aided diagnosis (CAD) model to discriminate age-related macular degeneration (AMD), diabetic macular edema (DME) and healthy macula. The linear configuration pattern (LCP) based features of the OCT images were screened by the Correlation-based Feature Subset (CFS) selection algorithm. And the best model based on the sequential minimal optimization (SMO) algorithm achieved 99.3% in the overall accuracy for the three classes of samples. PMID:28018716

Computer-aided design of peptide near infrared fluorescent probe for tumor diagnosis

NASA Astrophysics Data System (ADS)

Zhang, Congying; Gu, Yueqing

2014-09-01

Integrin αvβ3 receptors are expressed on activated endothelial cells during neovascularization to maintain tumor growth, so they become hot research tagets in cancer diagnosis. Peptides possess several attractive features when compared to protein and small molecule, such as small size and high structural compatibility with target proteins. Efficient design of high-affinity peptide ligands to Integrin αvβ3 receptors has been an important problem. Designed peptides in silico provide a valuable and high-selectivity peptide, meanwhile decrease the time of drug screening. In this study, we design peptide which can bind with integrin αvβ3 via computer, and then synthesis near infrared fluorescent probe. The characterization of this near infrared fluorescent probe was detected by UV. To investigate the tumor cell targeting of this probe, it was labeled with visible fluorescent dye Rhodamine B (RhB) for microscopy. To evaluate the targeting capability of this near infrared fluorescent probe, mice bearing integrin αvβ3 positive tumor xenografts were used. In vitro cellular experiments indicated that this probe have a clear binding affinity to αvβ3-positive tumor cells. In vivo experiments confirmed the receptor binding specificity of this probe. The peptide of computational design can bind with integrin αvβ3. Combined peptide near-infrared fluorescent probe with imaging technology use for clinical and tumor diagnosis have a greater development in future.

Pulmonary embolism detection using localized vessel-based features in dual energy CT

NASA Astrophysics Data System (ADS)

Dicente Cid, Yashin; Depeursinge, Adrien; Foncubierta Rodríguez, Antonio; Platon, Alexandra; Poletti, Pierre-Alexandre; Müller, Henning

2015-03-01

Pulmonary embolism (PE) affects up to 600,000 patients and contributes to at least 100,000 deaths every year in the United States alone. Diagnosis of PE can be difficult as most symptoms are unspecific and early diagnosis is essential for successful treatment. Computed Tomography (CT) images can show morphological anomalies that suggest the existence of PE. Various image-based procedures have been proposed for improving computer-aided diagnosis of PE. We propose a novel method for detecting PE based on localized vessel-based features computed in Dual Energy CT (DECT) images. DECT provides 4D data indexed by the three spatial coordinates and the energy level. The proposed features encode the variation of the Hounsfield Units across the different levels and the CT attenuation related to the amount of iodine contrast in each vessel. A local classification of the vessels is obtained through the classification of these features. Moreover, the localization of the vessel in the lung provides better comparison between patients. Results show that the simple features designed are able to classify pulmonary embolism patients with an AUC (area under the receiver operating curve) of 0.71 on a lobe basis. Prior segmentation of the lung lobes is not necessary because an automatic atlas-based segmentation obtains similar AUC levels (0.65) for the same dataset. The automatic atlas reaches 0.80 AUC in a larger dataset with more control cases.

Computer-assisted innovations in craniofacial surgery.

PubMed

Rudman, Kelli; Hoekzema, Craig; Rhee, John

2011-08-01

Reconstructive surgery for complex craniofacial defects challenges even the most experienced surgeons. Preoperative reconstructive planning requires consideration of both functional and aesthetic properties of the mandible, orbit, and midface. Technological innovations allow for computer-assisted preoperative planning, computer-aided manufacturing of patient-specific implants (PSIs), and computer-assisted intraoperative navigation. Although many case reports discuss computer-assisted preoperative planning and creation of custom implants, a general overview of computer-assisted innovations is not readily available. This article reviews innovations in computer-assisted reconstructive surgery including anatomic considerations when using PSIs, technologies available for preoperative planning, work flow and process of obtaining a PSI, and implant materials available for PSIs. A case example follows illustrating the use of this technology in the reconstruction of an orbital-frontal-temporal defect with a PSI. Computer-assisted reconstruction of complex craniofacial defects provides the reconstructive surgeon with innovative options for challenging reconstructive cases. As technology advances, applications of computer-assisted reconstruction will continue to expand. © Thieme Medical Publishers.

A New Approach to Implant-Based Midface Reconstruction Following Subtotal Maxillectomy.

PubMed

Dawood, Andrew; Kalavrezos, Nicholas; Tanner, Susan

2016-01-01

This case presentation describes the reconstruction of an extensive maxillary-orbital defect following subtotal resection of the maxilla en bloc with orbital exenteration in a young adult following the diagnosis of chondrosarcoma. A new approach to composite midface reconstruction with dental implants is described, in which computer-guided surgery (CGS) was used to obliquely position dental implants interradicularly in the residual maxilla, such that the implant tips lie in close proximity to the root apices of the remaining teeth. The implants were then used to fixate a milled-titanium bar, fabricated using computer-aided design and manufacture (CAD/CAM), and provided with attachments for the stabilization and retention of a maxillary obturator.

Simulation and visualization of face seal motion stability by means of computer generated movies

NASA Technical Reports Server (NTRS)

Etsion, I.; Auer, B. M.

1980-01-01

A computer aided design method for mechanical face seals is described. Based on computer simulation, the actual motion of the flexibly mounted element of the seal can be visualized. This is achieved by solving the equations of motion of this element, calculating the displacements in its various degrees of freedom vs. time, and displaying the transient behavior in the form of a motion picture. Incorporating such a method in the design phase allows one to detect instabilities and to correct undesirable behavior of the seal. A theoretical background is presented. Details of the motion display technique are described, and the usefulness of the method is demonstrated by an example of a noncontacting conical face seal.

Simulation and visualization of face seal motion stability by means of computer generated movies

NASA Technical Reports Server (NTRS)

Etsion, I.; Auer, B. M.

1981-01-01

A computer aided design method for mechanical face seals is described. Based on computer simulation, the actual motion of the flexibly mounted element of the seal can be visualized. This is achieved by solving the equations of motion of this element, calculating the displacements in its various degrees of freedom vs. time, and displaying the transient behavior in the form of a motion picture. Incorporating such a method in the design phase allows one to detect instabilities and to correct undesirable behavior of the seal. A theoretical background is presented. Details of the motion display technique are described, and the usefulness of the method is demonstrated by an example of a noncontacting conical face seal.

Hands-on work fine-tunes X-band PIN-diode duplexer

NASA Astrophysics Data System (ADS)

Schneider, P.

1985-06-01

Computer-aided design (CAD) programs for fabricating PIN-diode duplexers are useful in avoiding time-consuming cut-and-try techniques. Nevertheless, to attain minimum insertion loss, only experimentation yields the optimum microstrip circuitry. A PIN-diode duplexer, consisting of two SPST PIN-diode switches and a pair of 3-dB Lange microstrip couplers, designed for an X-band transmit/receive module exemplifies what is possible when computer-derived designs and experimentation are used together. Differences between the measured and computer-generated figures for insertion loss can be attributed to several factors not included in the CAD program - for example, radiation and connector losses. Mechanical tolerances of the microstrip PC board and variations in the SMA connector-to-microstrip transition contribute to the discrepancy.

Pre-trained convolutional neural networks as feature extractors toward improved malaria parasite detection in thin blood smear images.

PubMed

Rajaraman, Sivaramakrishnan; Antani, Sameer K; Poostchi, Mahdieh; Silamut, Kamolrat; Hossain, Md A; Maude, Richard J; Jaeger, Stefan; Thoma, George R

2018-01-01

Malaria is a blood disease caused by the Plasmodium parasites transmitted through the bite of female Anopheles mosquito. Microscopists commonly examine thick and thin blood smears to diagnose disease and compute parasitemia. However, their accuracy depends on smear quality and expertise in classifying and counting parasitized and uninfected cells. Such an examination could be arduous for large-scale diagnoses resulting in poor quality. State-of-the-art image-analysis based computer-aided diagnosis (CADx) methods using machine learning (ML) techniques, applied to microscopic images of the smears using hand-engineered features demand expertise in analyzing morphological, textural, and positional variations of the region of interest (ROI). In contrast, Convolutional Neural Networks (CNN), a class of deep learning (DL) models promise highly scalable and superior results with end-to-end feature extraction and classification. Automated malaria screening using DL techniques could, therefore, serve as an effective diagnostic aid. In this study, we evaluate the performance of pre-trained CNN based DL models as feature extractors toward classifying parasitized and uninfected cells to aid in improved disease screening. We experimentally determine the optimal model layers for feature extraction from the underlying data. Statistical validation of the results demonstrates the use of pre-trained CNNs as a promising tool for feature extraction for this purpose.