Study On Recognition Techniques Of Medical Images

With the development of the visualization techniques, the information of medical images is becoming more and more important in modern medicine domain. Especially, medical images diagnosis play an important role in modern medical treatments, and it also takes a significant function in clinic diagnosis and scientific research and teaching aspects.According to the extraction of renal corpuscle tissues, recognition techniques of medical images are studied in this paper. Firstly, the complex characteristics of the kidney images caused in the process of producing and the difficulties in extracting are analyzed. To solve these problems respectively, the color space transformation and BP neural network are firstly used to realize the classification and threshold processing of images. Then the images processing including thinning, interval linking, code word chaining, seed filling, boundary fitting is performed well by some methods in Mathematical Morphology and Computer Graphics and interpolation in numerical value analysis. After the processes above, the renal corpuscles with regular shapes are extracted successfully and also the renal corpuscles with irregular shapes are located in their existing areas of the kidney images. Especially, in the process of images threshold processing firstly, the images are classified based on different coloration conditions. Then different BP neural networks are designed to deal with each classified images, which efficiently resolved the difficulty of the defining images' color characteristics and also has significance to the subsequent extracting process. By studying on renal corpuscle' s extraction, I have a deep understanding to recognition techniques of medical images.In this paper, computer techniques and images process techniques are used to detect and extract the renal corpuscles in kidney images automatically, which facilitates the subsequent analysis to the renal corpuscles and relevant data acquisition and also has a great significance in liberatingmanpower, saving time, reducing misdiagnoses ratio and researching causation of kidney diseases by using of biopsy techniques.Another application example ?gene images automatic diagnoses techniques based on medical images recognition techniques is introduced in the end of this paper.