An Efficient Segmentation Method for Ultrasound Images based on a Semi-supervised Approach and Patch-based Features

Segmenting ultrasound images is a challenging problem where standard unsupervised segmentation methods such as the well-known Chan-Vese method fail. We propose in this paper an efficient segmentation method for this class of images. Our proposed algorithm is based on a semi-supervised approach (user labels) and the use of image patches as data features. We also consider the Pearson distance between patches, which has been shown to be robust w.r.t speckle noise present in ultrasound images. Our results on phantom and clinical data show a very high similarity agreement with the ground truth provided by a medical expert.


Published in:
Proceedings of the 8th IEEE International Symposium on Biomedical Imaging
Presented at:
8th IEEE International Symposium on Biomedical Imaging, Chicago, Illinois, USA, March 30th - April 2nd, 2011
Year:
2011
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Oral Presentation
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 Record created 2011-03-18, last modified 2018-03-17

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