Computer-aided diagnosis of mass screenings for gastric cancer using double contrast X-ray images

In a mass screening for gastric cancer, diagnosticians read several hundred stomach X-ray pictures at a time. The existing systems of computer-aided diagnosis for the cancer mark the location of lesions appeared in X-ray images. However, the systems do not reduce the hard labor due to lack of the accuracy in the marking. Besides, to diagnose characteristics of legions, diagnosticians have to directly read X-ray pictures of abnormal cases even if the systems could show the location precisely. For the sake of decreasing the number of reading the pictures in the mass screenings, the proposed method discriminates normal cases using stomach X-ray images. In normal cases, folds on the stomach wall appear in parallel. Therefore, the proposed method measures features of parallelism extracting the folds from X-ray images. Experimental results of the discriminations for 43 images including 11 abnormal cases have shown that the proposed features are well effective for recognizing normal cases.