Segmentation Method Using An Oriented Active Shape Model

摘要

An improved method of segmenting medical images includes aspects of live wire and active shape models to determine the most likely segmentation given a shape distribution that satisfies boundary location constrains on an item of interest. The method includes a supervised learning portion to train and learn new types of shape instances and a segmentation portion to use the learned model to segment new target images containing instances of the shape. The segmentation portion includes an automated search for an appropriate shape and deformation of the shape to establish a best oriented boundary for the object of interest on a medical image.