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Extraction of multi organs by use of level set method from CT images
Masafumi Komatsu,Hyoungseop Kim,Joo Kooi Tan,Seiji Ishikawa,Akiyoshi Yamamoto 제어로봇시스템학회 2008 제어로봇시스템학회 국제학술대회 논문집 Vol.2008 No.10
Recently, various imaging equipments have been introduced into medical fields. Especially, HRCT is one of the most useful diagnosis systems because it provides a high resolution image to physicians. Accordingly, many related image processing techniques are proposed into medical 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. Many related segmentation techniques have been developed for automatic extraction of regions of interest. Especially, in order to extract multi organs and to understand the structure of them, several approaches have been developed in the past. But there are still no fully automatic segmentation methods that are generally applicable to regions of interest based on CT image set. In this paper, we propose a new technique for automatic extraction of the multi organs on the MDCT images employing the level set method. We apply the proposed technique to three CT cases and satisfactory results are achieved.
Masafumi Komatsu,Shinji Toyota,Hyoungseop Kim,Joo Kooi Tan,Seiji Ishikawa,Akiyoshi Yamamoto 대한전자공학회 2008 ITC-CSCC :International Technical Conference on Ci Vol.2008 No.7
Recently, various imaging equipment such as high resolution computed tomography (HRCT) have been intoroduced into medical fields. Accordingly, many related image processing techniques are proposed into medical fields for extraction of abnormal area. Also, segmentation is one of the most important problems for analyzing the abnormalities and some segmentation techinques have been developed for automatic extraction of region of interest (ROI) before analyzing the abnomalities in the medical image processing field. It is, however, there are still no fully automatic segmantation methods that are generally applicable to ROI based on CT image set. In this paper, we present a technique for automatic extraction of the multi organs on the multi detector row computed tomography (MDCT) images employing the ribs information which is obtained by anatomical information and a level set method. We apply our proposed technique to three image sets and satisfactory segmentation results are achieved.
Segmentation Method for Cardiac Region in CT Images Based on Active Shape Model
Hiroki Takahashi,Masafumi Komatsu,Hyoungseop Kim,Joo Kooi Tan,Seiji Ishikawa,Akiyoshi Yamamoto 제어로봇시스템학회 2010 제어로봇시스템학회 국제학술대회 논문집 Vol.2010 No.10
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.