Vania, Malinda Kim, Sunhee Lee, Deukhee 2024-01-19T11:37:14Z 2024-01-19T11:37:14Z 2022-03-01 2016-07-11 https://pubs.kist.re.kr/handle/201004/114944 The automatic multisegmentation of computed tomography (CT) data of the upper abdomen poses a challenge with regard to accuracy, automation, and strength. In this paper, we propose automatic organ segmentation to segment the kidney, vena, and liver on the basis of a gray-level analysis. Furthermore, the method has been developed by utilizing the level set with weighted global and local forces to handle the topological data of organs and tissues to improve the accuracy of multi organ segmentation. The proposed methods were tested by performing segmentation of three abdominal organs (liver, kidneys, and inferior vena cava) from several CT datasets, and good segmentation results and visualization of 3D models were obtained. English IEEE Automatic Multisegmentation of Abdominal Organs by Level Set with Weighted Global and Local Forces Conference 2 IEEE EMBS International Student Conference (ISC) IEEE EMBS International Student Conference (ISC) US Ottawa, CANADA 2016-05-29 2016 IEEE EMBS INTERNATIONAL STUDENT CONFERENCE (ISC) 000389320500029