Abstract-This paper presents a new level set based solution for automatic medical image segmentation. Study shows that level set methods using image intensity or gradient information alone can not generate satisfying segmentation on some complex organic structures, such as lung bronchia or nodules. We investigate the intensity distribution of these organic structures, and propose a calibrating mechanism to automatically weight image intensity and gradient information in the level set speed function. The new method can tolerate estimation error in intensity distribution and detect object boundaries whose gradient is low. The experimental results show that the proposed method gives stable and accurate segmentation results on public lung image data.
Liu and Li REF proposed a new segmentation method based on gradient and intensity combined level set methods that generated stable and accurate segmentation results for lung bronchia and nodules.
AUTOMATIC MEDICAL IMAGE SEGMENTATION USING GRADIENT AND INTENSITY COMBINED LEVEL SET METHOD
Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference
Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference
Computer Science Medicine