ASSERT: a physician-in-the-loop content-based retrieval system for HRCT image databases
Computer Vision and Image Understanding - Special issue on content-based access for image and video libraries
Image Segmentation of Uterine Cervix Images for Indexing in PACS
CBMS '04 Proceedings of the 17th IEEE Symposium on Computer-Based Medical Systems
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The article presents two practical ways of using the automated color image segmentation in the medical field: for content-based region query and for tracking the time evolution of the disease in patients following a certain treatment. A known technique was used for automated color medical image segmentation - the color set back-projection algorithm. Our previous work in extraction of color regions from a database of nature images using the same algorithm showed promising results. The images are transformed from RGB to HSV color space, quantized at 166 colors and processed by the color set backprojection algorithm that allows the color region detection. The algorithm is studied from two points of view: complexity and the retrieval quality. The experiments that were made on a database with color endoscopy images from digestive tract have shown satisfying results for both applications that are important in practical medical use and medical teaching.