Development of intelligent image database system for medical x-ray images

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In this research, we tried to develope a highly intelligent image database for medical x-ray images , by integrating image understanding computer-aided diagnosis, and image retrieval.(1)Transferring the past system : We already developed a unique database for chest x-ray images which has the ability to manipulate sketches of the images stored in the database. By this system we can retrieve desired images by using pictorial keys given on a sketch and <query-by-pictorial-example> schemes. Since this system was implemented on a conventional large scale computer, we first transferred this system to the EWS(SUN-4) , and added the new function to write down diagnostic records into an original x-ray image.(2)Computer-aided diagnosis of cancer by x-ray images : We studied comuter diagnosis of lung and stomach cancer by applying image understanding techniques. Concerning stomach cancer we developed a procedure to detect small regions which are suspected to the abnormal from a double-contrast stomach x-ray image. Automated screening system for a photofluorogram was tested its performance to diagnose a 100mm films now used for mass screening and its limitations and basic policy for future improvement were made clear. For quantitative diagnosis of pneumoconiosis, we developed a procedure to automatically classify diseases into normal and nine classes according to the criteria given by ILO by detecting small rounded opacities observed in the lung field of pneumoconiosis x-ray images.(3)Supporting software tool : In order to support development of computer-aided image diagnosis system, we improved the image processing expert system IMPRESS we had previously developed , and began to study the intelligent image interface. Concerning the former, we added a goal transformation function to the system IMPRESS.