1988 Fiscal Year Final Research Report Summary
Basic study of computer diagnosis of high precision chest x-ray images Using digital radiography
| Project/Area Number |
62460125
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| Research Category |
Grant-in-Aid for General Scientific Research (B)
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| Allocation Type | Single-year Grants |
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| Research Field |
計算機工学
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| Research Institution | Nagoya University |
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Principal Investigator |
TORIWAKI Jun-ichiro Faculty of Engineering, Nagoya University, 工学部, 教授 (30023138)
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| Co-Investigator(Kenkyū-buntansha) |
HASEGAWA Jun-ichi Faculty of Liberal Arts, Chukyo University, 教養部, 教授 (30126891)
SUZUKI Hidetomo Faculty of Engineering, Nagoya University, 工学部, 助手 (20158976)
YOKOI Shigeki Faculty of Engineering, Nagoya University, 工学部, 助教授 (20115744)
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| Project Period (FY) |
1987 – 1988
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| Keywords | chest radiograph / computer diagnosis / digital radiograph / lung cancer / pneumoconiosis / image understanding / image recognition / 自動診断 |
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| Research Abstract |
(1) Our first aim in this project is to improve the performance of AISCR-V3(Automated Interpretation System of Chest Radiograms - Version 3) which we developed, so that it may have enough ability to treat high quality images taken by recent digital radiography (DR). We extended the picture size the system can process from 300 x 300 pixels to 600 x 600 pixels. We developed a new procedure to recognize vessel shadows using a position variant contast filter, and improved the ability to detect abnormal shfdows in the lung.
(2) Concerning computer diagnosis of pneumoconiosis. we newly developed a procedure to recognize small rounded opacities in the lung and measure the density of those opacities, by employing a difference type filtering followed by a patten classification algorithm. By combining the set of the same type of filters with different mask sizes we derived a procedure to execute both the density classification and the size classification of pneumoconiosis in a unified way. We applied the procedure to the ILO international standard film set with the promising result. Furthermore we tried the recognition of rounded opacities from x-ray CT images of pneumoconiosis and showed its feasibility.
(3) Two kinds of binary operations two pictures were applied computer diagnosis of chest x-ray images. One is detection of lung cancer from energy subtraction DR images. This revealed characteristics of energy subtraction images and the feasibility of computer interpretation of such images. The other is automated detection and measurement of the amount of changes among picture, sequences taken at different times from the same patient. We developed a procedure consisting of registration by the affine transformation and change detection by the local cross correlation. and applied it to the lung cancer diagnosis.
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