Hierarchical segmentation of digital mammography by agents competition

A. Melouah, H. Merouani
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引用次数: 1

Abstract

A new hybrid approach for mammography segmentation is suggested in this work. The segmentations proceed by refining successively, in a way that macro regions at each step are recovered. Two segmentation techniques, thresholding and Markov field, enter in competition to segment theses regions. The technique which gives the best results according to a given criterion will take on the process. However, using the same segmentation for all macro regions is not necessary. Thus, the new obtained regions will become candidates for a novel segmentation. The process continues till verification of a stop criterion.
基于agent竞争的数字乳房x线造影分层分割
本文提出了一种新的乳房x线摄影分割混合方法。分割是通过连续的细化来进行的,每一步的宏观区域都会被恢复。阈值分割和马尔可夫域分割这两种分割技术相互竞争。根据给定的标准给出最佳结果的技术将采用该过程。但是,没有必要对所有宏观区域使用相同的分割。因此,新获得的区域将成为新分割的候选区域。该过程将继续进行,直到确认停止条件为止。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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