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Improved watershed transform for medical image segmentation using prior information.

Abstract：

:The watershed transform has interesting properties that make it useful for many different image segmentation applications: it is simple and intuitive, can be parallelized, and always produces a complete division of the image. However, when applied to medical image analysis, it has important drawbacks (oversegmentation, sensitivity to noise, poor detection of thin or low signal to noise ratio structures). We present an improvement to the watershed transform that enables the introduction of prior information in its calculation. We propose to introduce this information via the use of a previous probability calculation. Furthermore, we introduce a method to combine the watershed transform and atlas registration, through the use of markers. We have applied our new algorithm to two challenging applications: knee cartilage and gray matter/white matter segmentation in MR images. Numerical validation of the results is provided, demonstrating the strength of the algorithm for medical image segmentation.

journal_name

IEEE Trans Med Imaging

journal_title

IEEE transactions on medical imaging

authors

Grau V,Mewes AU,Alcañiz M,Kikinis R,Warfield SK

doi

10.1109/TMI.2004.824224

subject

Has Abstract

pub_date

2004-04-01 00:00:00

pages

447-58

issue

4

eissn

0278-0062

issn

1558-254X

journal_volume

23

pub_type

杂志文章

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