Segmentation method for cardiac region in CT images based on active shape model

Recently, multi detector row computed tomography (MDCT) has been introduced into medical fields. By the development of MDCT, images with high quality are provided into medical fields. So many related image processing techniques are proposed into medical image processing fields for extraction of abnormal area. In the medical image processing field, segmentation is one of the most important problems for analyzing the abnormalities and recognition of internal structures before the operation. For this reason, many approaches are proposed for detection of abnormal area on CT images. Before detection of abnormal areas, segmentation of organs in CT images is one of the most important problems for analyzing of disease. However, poor contrast, image noises and motion artifacts make this segmentation problem difficult in particular in cardiac region. Moreover, there are still no fully automatic segmentation methods for cardiac region on CT images. In this paper, we present automatic extraction technique for detection of cardiac region. Our proposed technique combines active shape model (ASM) and genetic algorithm (GA). We apply our proposed technique to five real CT images and satisfactory segmentation results are achieved.