Multiresolutional graph cuts for brain extraction from MR images

Yong-Sheng Chen*, Li Fen Chen, Yi Ting Wang

*此作品的通信作者

研究成果: Conference contribution同行評審

摘要

This paper presents a multiresolutional brain extraction framework which utilizes graph cuts technique to classify head magnetic resonance (MR) images into brain and non-brain regions. Starting with an over-extracted brain region, we refine the segmentation result by trimming non-brain regions in a coarse-to-fine manner. The extracted brain at the coarser level will be propagated to the finer level to estimate foreground/background seeds as constraints. The short-cut problem of graph cuts is reduced by the proposed pre-determined foreground from the coarser level. In order to consider the impact of the intensity inhomogeneities, we estimate the intensity distribution locally by partitioning volume images of each resolution into different numbers of smaller cubes. The graph cuts method is individually applied for each cube. Compared with four existing methods, the proposed method performs well in terms of sensitivity and specificity in our experiments for performance evaluation.

原文English
主出版物標題Fifth International Conference on Digital Image Processing, ICDIP 2013
DOIs
出版狀態Published - 13 12月 2013
事件5th International Conference on Digital Image Processing, ICDIP 2013 - Beijing, China
持續時間: 21 4月 201322 4月 2013

出版系列

名字Proceedings of SPIE - The International Society for Optical Engineering
8878
ISSN(列印)0277-786X
ISSN(電子)1996-756X

Conference

Conference5th International Conference on Digital Image Processing, ICDIP 2013
國家/地區China
城市Beijing
期間21/04/1322/04/13

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