Journal of Pure and Applied MicrobiologyVol. 7 No. Special Edition

Pancreas Segmentation using level-set Method based on Statistical Shape Model

Huiyan Jiang*, Xin Wang and Shuo Shi

Software College, Northeastern University, Shenyang, China.

Received on 03 March 2013 and accepted on 14 April 2013



As Computer Aided Diagnosis (CAD) was widely used in medical field, it was necessary to be studied deeply, especially in image segmentation. The complex anatomy structure around the pancreas made segmentation of pancreas become more difficult. In this paper a new method for medical image segmentation was proposed which used level-set method based on statistical shape model to solve above problem and improve the performance of segmentation. The level-set method was used firstly to obtain the segmentation result of the pancreas from CT images. Then some anatomical information was added into segmentation process by using a better shape of the interest object obtained by statistical shape model. Several experiments were carried out to demonstrate the validation of our proposed algorithm, and the level-set and region-grow methods were chosen as the contrast algorithm. We also gave quantitative results which showed that our method had a good robustness and better precise of segmentation than other methods.

Keywords : Computer aided diagnosis, image segmentation, pancreas, level-set, statistical shape model.