| Project/Area Number |
15591311
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Radiation science
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| Research Institution | Kumamoto University (2004)
Nippon Bunri University (2003) |
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Principal Investigator |
KATSURAGAWA Shigehiko Kumamoto Univ., School of Health Sciences, Professor, 医学部, 教授 (60021630)
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| Co-Investigator(Kenkyū-buntansha) |
ASHIZAWA Kazuto Nagasaki Univ., School of Medicine, Assistant Professor, 医学部, 講師 (90274662)
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| Project Period (FY) |
2003 – 2004
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| Project Status |
Completed (Fiscal Year 2004)
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| Budget Amount *help |
¥1,700,000 (Direct Cost: ¥1,700,000)
Fiscal Year 2004: ¥500,000 (Direct Cost: ¥500,000)
Fiscal Year 2003: ¥1,200,000 (Direct Cost: ¥1,200,000)
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| Keywords | Similar image subtraction / Similarity / Image warping / Temporal subtraction / Chest radiograph / Computer-aided diagnosis / Patient recognition / Observer study / 類似差分画像 / 経時的差分画像 / 胸部単純写真 / コンピュータ支援診断 / 画像データベース |
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| Research Abstract |
We have developed a computerized scheme of similar image subtraction method which provides subtraction images obtained from similar chest radiographs of different patients. In this study, an image to be diagnosed is called "target image".
1.A large image database was established with 8776 normal chest radiographs(5352 female images and 3424 male images) obtained from a lung cancer screening in Iwate prefecture. All images were taken from a computed radiography(CR) system.
2.Similar images of a target image were searched from a large database consist of normal chest radiographs. First, initial candidates of the similar image(10% in the database) were selected by the similarity of the lung size between the target image and normal images. Second, further similar images were chosen from the initial candidates by using their correlation values between the target image and candidates.
3.Finally, subtraction images were produced by subtracting the selected similar images of different patients from the target image. The subtraction was performed with a global matching and local matching based on a nonlinear image warping technique.
4.The quality of the subtraction images obtained from similar chest radiographs of different patients were evaluated subjectively in terms of artifacts due to misregistration between a target image and a similar image.
5.Similar images selected from the database were remarkably resembled to the target chest radiographs. Although the subtracted images obtained from different patients included some artifacts, their image qualities were acceptable for detection of abnormal lesions. Approximately, 40% of the subtraction images obtained from the similar images were considered clinically useful to enhance abnormalities in chest radiographs.
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