Automatic liver detection and segmentation from 3D CT images: a hybrid method using statistical pose model and probabilistic atlas
黄成, Fucang Jia, 方驰华, 范应方, 胡庆茂 · 2013
Precise, robust and fully automatic segmentation of liver parenchyma from medical images is the first step and one of the major tasks in liver surgical planning. Fast and automatic liver detection is the first step to achieve good liver segmentation, due to wide variable scanning range of abdominal CT images, automatic liver detection is often unreliable which could cause total failure in the subsequent extraction of liver surface. Various kinds of approaches have been proposed to try to achieve robust liver segmentation. Here, a hybrid method is proposed that combines a novel statistical pose model (SPM) with probabilistic atlas, for fast, robust and fully automatic liver detection and segmentation.