Gastric Adenocarcinoma Aided Diagnosis System

Computer-aided medical image processing and analysis is an important application in the field of image processing using medical image characteristics. It is absolutely helpful for clinical diagnosis and medical studies that computer-aided diagnosis system of cancerous tissues is introduced, especially in the case of lack of specialists. In this paper, we focus on the studies of how to found the computer-aided diagnosis system of gastric adenocarcinoma and the knowledge base of gastric adenocarcinoma cell characteristics.We adopt the object-oriented and modular design pattern in the work. The system we proposed has seven basic parts, including image acquiring module, basic window command module, basic image processing module, medical image processing module, metadata management module of medical image, image recognition module and image retrieval module. Tests show that doctors improve their efficiency and accuracy aided by our system.In order to found the knowledge base of gastric adenocarcinoma cell characteristics, we need to segment the nuclei of every cell and extract the features at first. We present a improved adaptive thresholding algorithm based on 2D Otsu to get the accurate region of cell nuclei and a estimate algorithm of separate line based on active contour model to isolate the overlapped cells. The methods above get the contour of single cell and extract the morphometry, heterochromatic and textual features correctly, which is the base of automatic recognition of gastric adenocarcinoma cells.