Dr. Satoshi Kasai Profile

Dr. Satoshi Kasai

at Konica Minolta Lab USA Inc

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Publications (2)

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Proceedings Article | 30 March 2007 Paper

Computerized method for detection of vertebral fractures on lateral chest radiographs based on morphometric data

Satoshi Kasai, Feng Li, Junji Shiraishi, Qiang Li, Christopher Straus, Tamara Vokes, Heber MacMahon, Kunio Doi

Proceedings Volume 6514, 65141N (2007) https://doi.org/10.1117/12.706533

KEYWORDS: Chest imaging, Edge detection, Chest, Radiology, Radiography, Computer aided diagnosis and therapy, Lung, Medical imaging, Image enhancement, Lithium

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Vertebral fractures are the most common osteoporosis-related fractures. It is important to detect vertebral fractures, because they are associated with increased risk of subsequent fractures, and because pharmacologic therapy can reduce the risk of subsequent fractures. Although vertebral fractures are often not clinically recognized, they can be visualized on lateral chest radiographs taken for other purposes. However, only 15-60% of vertebral fractures found on lateral chest radiographs are mentioned in radiology reports. The purpose of this study was to develop a computerized method for detection of vertebral fractures on lateral chest radiographs in order to assist radiologists' image interpretation. Our computerized method is based on the automated identification of upper and lower vertebral edges. In order to develop the scheme, radiologists provided morphometric data for each identifiable vertebra, which consisted of six points for each vertebra, for 25 normals and 20 cases with severe fractures. Anatomical information was obtained from morphometric data of normal cases in terms of vertebral heights, heights of vertebral disk spaces, and vertebral centerline. Computerized detection of vertebral fractures was based on the reduction in the heights of fractured vertebrae compared to adjacent vertebrae and normal reference data. Vertebral heights from morphometric data on normal cases were used as reference. On 138 chest radiographs (20 with fractures) the sensitivity of our method for detection of fracture cases was 95% (19/20) with 0.93 (110/118) false-positives per image. In conclusion, the computerized method would be useful for detection of potentially overlooked vertebral fractures on lateral chest radiographs.

Proceedings Article | 15 March 2006 Paper

Development of computerized method for detection of vertebral fractures on lateral chest radiographs

Satoshi Kasai, Feng Li, Junji Shiraishi, Qiang Li, Yongkang Nie, Kunio Doi

Proceedings Volume 6144, 61445D (2006) https://doi.org/10.1117/12.653265

KEYWORDS: Chest imaging, Edge detection, Image enhancement, Chest, Image analysis, Clinical trials, Computer aided diagnosis and therapy, Radiology, Diagnostics, Databases

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Osteoporosis is one of the major public health concerns in the world. Several clinical trials indicated clearly that pharmacologic therapy for osteoporosis is effective for persons with vertebral fractures for preventing subsequent fractures. It is, therefore, important to diagnose vertebral fractures early. Although most vertebral fractures are asymptomatic, they can often be detected on lateral chest radiographs which may be obtained for other purposes. However, investigators have reported that vertebral fractures which were visible on lateral chest radiographs were underdiagnosed or underreported. Therefore, our purpose in this study was to develop a computerized method for detection of vertebral fractures on lateral chest radiographs and to assist radiologists' image interpretation. Our computerized scheme is based on the detection of upper and lower edges of vertebrae on lateral chest images. A curved rectangular area which included a number of visible vertebrae was identified. This area was then straightened such that the upper and lower edges of the vertebrae were oriented horizontally. For detection of vertebral edges, line components were enhanced, and a multiple thresholding technique followed by image feature analysis was applied to the line enhanced image. Finally, vertebral heights determined from the detected vertebral edges were used for characterizing the shape of the vertebrae and for distinguishing fractured from normal vertebrae. Our preliminary results indicated that all of the severely fractured vertebrae in a small database were detected correctly by our computerized method.

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