The Experts below are selected from a list of 318 Experts worldwide ranked by ideXlab platform
Toru Yanagisawa - One of the best experts on this subject based on the ideXlab platform.
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Computer-Aided Diagnosis in chest radiography. Preliminary experience.
Investigative Radiology, 1993Co-Authors: Katsumi Abe, Maryellen L Giger, Kunio Doi, H. Macmahon, Hong Jia, Xuan Chen, Akiko Kano, Toru YanagisawaAbstract:RATIONALE AND OBJECTIVES Computer-Aided Diagnosis (CAD) schemes for chest radiography are being developed with which to alert radiologists to possible lesions, and thus potentially improve diagnostic accuracy. However, CAD schemes have not been tested on a large number of clinical cases. The authors identify design parameters that would be required for development of an intelligent workstation. METHODS Computer-Aided Diagnosis programs were applied for the automated detection of lung nodules, cardiomegaly, and interstitial infiltrates to 310 consecutive chest radiographs, and were analyzed for potential usefulness and limitations. Computer-Aided Diagnosis output was evaluated by radiologists and physicists for accuracy and technical problems, respectively. RESULTS Approximately 70% of the results were judged to be potentially acceptable; however, the number of false-positive findings was relatively high. Technical problems included failure to detect subtle abnormalities and the occurrence of false-positive detections caused by normal anatomical structures. CONCLUSION Computer-Aided Diagnosis has the potential to be a valuable aid to radiologists in clinical practice, if certain technical problems can be overcome and if optimal operating points can be defined for clinical use.
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Computer-Aided Diagnosis in chest radiography. Preliminary experience.
Investigative radiology, 1993Co-Authors: Katsumi Abe, Maryellen L Giger, Kunio Doi, H. Macmahon, Hong Jia, Xuan Chen, Akiko Kano, Toru YanagisawaAbstract:Computer-Aided Diagnosis (CAD) schemes for chest radiography are being developed with which to alert radiologists to possible lesions, and thus potentially improve diagnostic accuracy. However, CAD schemes have not been tested on a large number of clinical cases. The authors identify design parameters that would be required for development of an intelligent workstation. Computer-Aided Diagnosis programs were applied for the automated detection of lung nodules, cardiomegaly, and interstitial infiltrates to 310 consecutive chest radiographs, and were analyzed for potential usefulness and limitations. Computer-Aided Diagnosis output was evaluated by radiologists and physicists for accuracy and technical problems, respectively. Approximately 70% of the results were judged to be potentially acceptable; however, the number of false-positive findings was relatively high. Technical problems included failure to detect subtle abnormalities and the occurrence of false-positive detections caused by normal anatomical structures. Computer-Aided Diagnosis has the potential to be a valuable aid to radiologists in clinical practice, if certain technical problems can be overcome and if optimal operating points can be defined for clinical use.
Kunio Doi - One of the best experts on this subject based on the ideXlab platform.
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Computer-Aided Diagnosis moves from breast to other systems
2007Co-Authors: Kunio DoiAbstract:Computer-Aided Diagnosis has become a part of routine clinical work for detection of breast cancer on mammograms.1-7 It is beginning to be applied in the detection and differential Diagnosis of many different kinds of abnormalities in medical images obtained with various modalities.
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Computer-Aided Diagnosis in chest radiography.
Computerized Medical Imaging and Graphics, 2007Co-Authors: Shigehiko Katsuragawa, Kunio DoiAbstract:Abstract We have developed Computer-Aided Diagnosis (CAD) schemes for the detection of lung nodules, interstitial lung diseases, interval changes, and asymmetric opacities, and also for the differential Diagnosis of lung nodules and interstitial lung diseases on chest radiographs. Observer performance studies indicate clearly that radiologists’ diagnostic accuracy was improved significantly when radiologists used a Computer output in their interpretations of chest radiographs. In addition, the automated recognition methods for the patient and the projection view by use of chest radiographs were useful for integrating the chest CAD schemes into the picture-archiving and communication system (PACS).
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Computer-Aided Diagnosis in thoracic CT.
Seminars in Ultrasound CT and MRI, 2005Co-Authors: Kunio Doi, H. Macmahon, Hiroyuki Abe, Junji Shiraishi, Roger Engelmann, Kenji Suzuki, Yongkang NieAbstract:Computer-Aided Diagnosis (CAD) provides a Computerized diagnostic result as a "second opinion" to assist radiologists in the Diagnosis of various diseases by use of medical images. CAD has become a practical clinical approach in diagnostic radiology, although, at present, primarily in the area of detection of breast cancer in mammograms. Currently, a large research effort has been devoted to the detection and classification of various lung diseases in thoracic computed tomography (CT) images. We describe in this article the current status of the development of CAD schemes in thoracic CT, including nodule detection, distinction between benign and malignant nodules, and detection, characterization, and differential Diagnosis of diffuse lung disease. Observer performance studies indicate that these CAD schemes would be useful in clinical practice by providing radiologists with Computer output as a "second opinion."
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Computer-Aided Diagnosis in chest radiology.
Seminars in Ultrasound CT and MRI, 2004Co-Authors: Hiroyuki Abe, H. Macmahon, Junji Shiraishi, Roger Engelmann, Kunio DoiAbstract:Chest radiography is still a useful examination in various situations, although CT has become a modality of choice as a diagnostic examination in many cases. Current Computer-Aided Diagnosis (CAD) schemes for chest radiographs include nodule detection, interstitial disease detection, temporal subtraction, differential Diagnosis of interstitial disease, and distinction between benign and malignant pulmonary nodules. All of these schemes are demonstrated as providing potentially useful tools for radiologists when the output of these schemes is used as a "second opinion." There are some commercially available products for these schemes and more are expected to be available in the near future. The current status of CAD for CT is also discussed briefly in this article.
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Relative gains in diagnostic accuracy between Computer-Aided Diagnosis and independent double reading
Medical Imaging 2000: Image Perception and Performance, 2000Co-Authors: Yulei Jiang, Robert M. Nishikawa, Robert A. Schmidt, Charles E. Metz, Kunio DoiAbstract:Double readings of chest radiographs and mammograms made by two radiologists have been investigated as a way to improve diagnostic accuracy. Computer-Aided Diagnosis (CAD) also has been investigated as an alternative method to improve diagnostic accuracy. Our purpose was to compare the relative gains that can be obtained from independent double readings and from Computer-Aided Diagnosis in the Diagnosis of breast lesions in mammograms (determining a known lesion as malignant or benign). We conducted an observer study from which we obtained data of radiologists' unAided single-reading performance and their single-reading performance with a Computer aid. We then derived their unAided double-reading performance according to six different methods. Our results show that Computer-Aided Diagnosis can potentially improve radiologists' diagnostic accuracy more than independent double readings by two radiologists.
Maryellen L Giger - One of the best experts on this subject based on the ideXlab platform.
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Computer-Aided Diagnosis
2008Co-Authors: Maryellen L GigerAbstract:Publisher Summary This chapter explains the role of Computer-Aided Diagnosis (CAD) for the detection and Diagnosis of diseases, with illustrations on breast cancer, lung cancer, and colon cancer. Development and implementation of Computer-Aided detection and Diagnosis involves the application of Computer technology in medical image interpretation. Radiologists can use the output from a Computerized analysis of medical images as a ‘‘second opinion’’ in detecting and characterizing lesions as well as in making diagnostic decisions. Thus, the Computer output needs to be at a sufficient performance level in terms of sensitivity and specificity, and the Computer interface should have a user-friendly format for effective and efficient use by the radiologist. Two general types of systems for CAD are being developed: CADe for Computer-Aided detection and CADx for Computer-Aided Diagnosis. CADe involves the use of Computer analyses to indicate locations of suspect regions in a medical image. CADx involves the use of Computer analyses to characterize a region or lesion. clinical usefulness of Computer-Aided detection for screening mammography is being tested by actual prospective clinical usage of commercial systems. For thoracic CT and CT colonography for the early detection of lung cancer and colon cancer, respectively, effective and efficient displays are also needed to help the radiologist incorporate the Computer output into the three-dimensional image data.
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Computer-Aided Diagnosis of breast lesions in medical images
Computing in Science & Engineering, 2000Co-Authors: Maryellen L GigerAbstract:Given current error rates, this article surveys various approaches and techniques for improved breast lesion Diagnosis in medical images, including mammography, ultrasound and magnetic resonance imaging. The author also includes studies that compare human versus Computer-Aided Diagnosis.
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Computer-Aided Diagnosis in chest radiography. Preliminary experience.
Investigative Radiology, 1993Co-Authors: Katsumi Abe, Maryellen L Giger, Kunio Doi, H. Macmahon, Hong Jia, Xuan Chen, Akiko Kano, Toru YanagisawaAbstract:RATIONALE AND OBJECTIVES Computer-Aided Diagnosis (CAD) schemes for chest radiography are being developed with which to alert radiologists to possible lesions, and thus potentially improve diagnostic accuracy. However, CAD schemes have not been tested on a large number of clinical cases. The authors identify design parameters that would be required for development of an intelligent workstation. METHODS Computer-Aided Diagnosis programs were applied for the automated detection of lung nodules, cardiomegaly, and interstitial infiltrates to 310 consecutive chest radiographs, and were analyzed for potential usefulness and limitations. Computer-Aided Diagnosis output was evaluated by radiologists and physicists for accuracy and technical problems, respectively. RESULTS Approximately 70% of the results were judged to be potentially acceptable; however, the number of false-positive findings was relatively high. Technical problems included failure to detect subtle abnormalities and the occurrence of false-positive detections caused by normal anatomical structures. CONCLUSION Computer-Aided Diagnosis has the potential to be a valuable aid to radiologists in clinical practice, if certain technical problems can be overcome and if optimal operating points can be defined for clinical use.
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Computer-Aided Diagnosis in chest radiography. Preliminary experience.
Investigative radiology, 1993Co-Authors: Katsumi Abe, Maryellen L Giger, Kunio Doi, H. Macmahon, Hong Jia, Xuan Chen, Akiko Kano, Toru YanagisawaAbstract:Computer-Aided Diagnosis (CAD) schemes for chest radiography are being developed with which to alert radiologists to possible lesions, and thus potentially improve diagnostic accuracy. However, CAD schemes have not been tested on a large number of clinical cases. The authors identify design parameters that would be required for development of an intelligent workstation. Computer-Aided Diagnosis programs were applied for the automated detection of lung nodules, cardiomegaly, and interstitial infiltrates to 310 consecutive chest radiographs, and were analyzed for potential usefulness and limitations. Computer-Aided Diagnosis output was evaluated by radiologists and physicists for accuracy and technical problems, respectively. Approximately 70% of the results were judged to be potentially acceptable; however, the number of false-positive findings was relatively high. Technical problems included failure to detect subtle abnormalities and the occurrence of false-positive detections caused by normal anatomical structures. Computer-Aided Diagnosis has the potential to be a valuable aid to radiologists in clinical practice, if certain technical problems can be overcome and if optimal operating points can be defined for clinical use.
H. Macmahon - One of the best experts on this subject based on the ideXlab platform.
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Computer-Aided Diagnosis in thoracic CT.
Seminars in Ultrasound CT and MRI, 2005Co-Authors: Kunio Doi, H. Macmahon, Hiroyuki Abe, Junji Shiraishi, Roger Engelmann, Kenji Suzuki, Yongkang NieAbstract:Computer-Aided Diagnosis (CAD) provides a Computerized diagnostic result as a "second opinion" to assist radiologists in the Diagnosis of various diseases by use of medical images. CAD has become a practical clinical approach in diagnostic radiology, although, at present, primarily in the area of detection of breast cancer in mammograms. Currently, a large research effort has been devoted to the detection and classification of various lung diseases in thoracic computed tomography (CT) images. We describe in this article the current status of the development of CAD schemes in thoracic CT, including nodule detection, distinction between benign and malignant nodules, and detection, characterization, and differential Diagnosis of diffuse lung disease. Observer performance studies indicate that these CAD schemes would be useful in clinical practice by providing radiologists with Computer output as a "second opinion."
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Computer-Aided Diagnosis in chest radiology.
Seminars in Ultrasound CT and MRI, 2004Co-Authors: Hiroyuki Abe, H. Macmahon, Junji Shiraishi, Roger Engelmann, Kunio DoiAbstract:Chest radiography is still a useful examination in various situations, although CT has become a modality of choice as a diagnostic examination in many cases. Current Computer-Aided Diagnosis (CAD) schemes for chest radiographs include nodule detection, interstitial disease detection, temporal subtraction, differential Diagnosis of interstitial disease, and distinction between benign and malignant pulmonary nodules. All of these schemes are demonstrated as providing potentially useful tools for radiologists when the output of these schemes is used as a "second opinion." There are some commercially available products for these schemes and more are expected to be available in the near future. The current status of CAD for CT is also discussed briefly in this article.
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Computer-Aided Diagnosis in chest radiography. Preliminary experience.
Investigative Radiology, 1993Co-Authors: Katsumi Abe, Maryellen L Giger, Kunio Doi, H. Macmahon, Hong Jia, Xuan Chen, Akiko Kano, Toru YanagisawaAbstract:RATIONALE AND OBJECTIVES Computer-Aided Diagnosis (CAD) schemes for chest radiography are being developed with which to alert radiologists to possible lesions, and thus potentially improve diagnostic accuracy. However, CAD schemes have not been tested on a large number of clinical cases. The authors identify design parameters that would be required for development of an intelligent workstation. METHODS Computer-Aided Diagnosis programs were applied for the automated detection of lung nodules, cardiomegaly, and interstitial infiltrates to 310 consecutive chest radiographs, and were analyzed for potential usefulness and limitations. Computer-Aided Diagnosis output was evaluated by radiologists and physicists for accuracy and technical problems, respectively. RESULTS Approximately 70% of the results were judged to be potentially acceptable; however, the number of false-positive findings was relatively high. Technical problems included failure to detect subtle abnormalities and the occurrence of false-positive detections caused by normal anatomical structures. CONCLUSION Computer-Aided Diagnosis has the potential to be a valuable aid to radiologists in clinical practice, if certain technical problems can be overcome and if optimal operating points can be defined for clinical use.
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Computer-Aided Diagnosis in chest radiography. Preliminary experience.
Investigative radiology, 1993Co-Authors: Katsumi Abe, Maryellen L Giger, Kunio Doi, H. Macmahon, Hong Jia, Xuan Chen, Akiko Kano, Toru YanagisawaAbstract:Computer-Aided Diagnosis (CAD) schemes for chest radiography are being developed with which to alert radiologists to possible lesions, and thus potentially improve diagnostic accuracy. However, CAD schemes have not been tested on a large number of clinical cases. The authors identify design parameters that would be required for development of an intelligent workstation. Computer-Aided Diagnosis programs were applied for the automated detection of lung nodules, cardiomegaly, and interstitial infiltrates to 310 consecutive chest radiographs, and were analyzed for potential usefulness and limitations. Computer-Aided Diagnosis output was evaluated by radiologists and physicists for accuracy and technical problems, respectively. Approximately 70% of the results were judged to be potentially acceptable; however, the number of false-positive findings was relatively high. Technical problems included failure to detect subtle abnormalities and the occurrence of false-positive detections caused by normal anatomical structures. Computer-Aided Diagnosis has the potential to be a valuable aid to radiologists in clinical practice, if certain technical problems can be overcome and if optimal operating points can be defined for clinical use.
Katsumi Abe - One of the best experts on this subject based on the ideXlab platform.
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Computer-Aided Diagnosis in chest radiography. Preliminary experience.
Investigative Radiology, 1993Co-Authors: Katsumi Abe, Maryellen L Giger, Kunio Doi, H. Macmahon, Hong Jia, Xuan Chen, Akiko Kano, Toru YanagisawaAbstract:RATIONALE AND OBJECTIVES Computer-Aided Diagnosis (CAD) schemes for chest radiography are being developed with which to alert radiologists to possible lesions, and thus potentially improve diagnostic accuracy. However, CAD schemes have not been tested on a large number of clinical cases. The authors identify design parameters that would be required for development of an intelligent workstation. METHODS Computer-Aided Diagnosis programs were applied for the automated detection of lung nodules, cardiomegaly, and interstitial infiltrates to 310 consecutive chest radiographs, and were analyzed for potential usefulness and limitations. Computer-Aided Diagnosis output was evaluated by radiologists and physicists for accuracy and technical problems, respectively. RESULTS Approximately 70% of the results were judged to be potentially acceptable; however, the number of false-positive findings was relatively high. Technical problems included failure to detect subtle abnormalities and the occurrence of false-positive detections caused by normal anatomical structures. CONCLUSION Computer-Aided Diagnosis has the potential to be a valuable aid to radiologists in clinical practice, if certain technical problems can be overcome and if optimal operating points can be defined for clinical use.
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Computer-Aided Diagnosis in chest radiography. Preliminary experience.
Investigative radiology, 1993Co-Authors: Katsumi Abe, Maryellen L Giger, Kunio Doi, H. Macmahon, Hong Jia, Xuan Chen, Akiko Kano, Toru YanagisawaAbstract:Computer-Aided Diagnosis (CAD) schemes for chest radiography are being developed with which to alert radiologists to possible lesions, and thus potentially improve diagnostic accuracy. However, CAD schemes have not been tested on a large number of clinical cases. The authors identify design parameters that would be required for development of an intelligent workstation. Computer-Aided Diagnosis programs were applied for the automated detection of lung nodules, cardiomegaly, and interstitial infiltrates to 310 consecutive chest radiographs, and were analyzed for potential usefulness and limitations. Computer-Aided Diagnosis output was evaluated by radiologists and physicists for accuracy and technical problems, respectively. Approximately 70% of the results were judged to be potentially acceptable; however, the number of false-positive findings was relatively high. Technical problems included failure to detect subtle abnormalities and the occurrence of false-positive detections caused by normal anatomical structures. Computer-Aided Diagnosis has the potential to be a valuable aid to radiologists in clinical practice, if certain technical problems can be overcome and if optimal operating points can be defined for clinical use.