A Review of Computer Vision Methods for Purpose on Computer-Aided Diagnosis

Medical imaging devices such as X-ray, CT and MRI provide information such as disease, abnormality and anatomic land-mark of inside of human body which cannot be seen directly. This information can be used for diagnosis or surgical planning. Since there are hundreds of slices to examine for CT and MRI data, it is time-consuming to examine all slices. Also, some noises inherent in these devices disturb the diagnosis process. For an efficient and clear Computer Aided Diagnosis, it is im-portant to process the images in order to remove the degrada-tion and to extract meaningful information from slices. This is the reason why the computer vision algorithms are essential for the Computer Aided Diagnosis.In the Computer Aided Diagnosis, extracting surgical infor-mation from image is processed through pattern recognition algorithms. In the pattern recognition procedure, image pro-cessing method is applied to eliminate possible noises from the imaging device and to enhance the image quality such as image contrast and sharpness. After that, the structural information of vessel, bone, organs is extracted via a segmentation method. Segmentation is the process which separates an image into seg -ments based on its pixel information. Each segment should rep-resent a region of human body on the image. Finally, the pattern