Abstract:

Aiming at the problems of high time complexity and low accuracy of traditional medical image segmentation algorithm, we proposed a segmentation algorithm based on onedimensional Otsu automatic multiple threshold. Taking into account the complexity of medical image information, we introduced a
 comprehensive information histogram based on gradient, gray scale and distance to replace the traditional gray histogram, and gave the corresponding weights of the 3 information respectively. Kdtree was used as a framework to quickly determine the number of threshold automatically, and then to realize the automatic threshold segmentation of medical images by Otsu. Compared with the maximum entropy and Otsu based on particle swarm optimization algorithm, experimental results show that the segmentation performance of the proposed algorithm is superior to other algorithms.

Key words: Otsu, kd-tree, gradient, normalized distance, gray histogram