Inproceedings: an article in a conference proceedings.
An Efficient Segmentation Method for Ultrasound Images based on a Semi-supervised Approach and Patch-based Features
Title of the conference
Proceedings of the 8th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2011
Chicago, Illinois, USA, March 30 - April 2, 2011
Segmenting ultrasound images is a challenging problemwhere standard unsupervised segmentation methods such asthe well-known Chan-Vese method fail. We propose in thispaper an efficient segmentation method for this class ofimages. Our proposed algorithm is based on asemi-supervised approach (user labels) and the use ofimage patches as data features. We also consider thePearson distance between patches, which has been shown tobe robust w.r.t speckle noise present in ultrasoundimages. Our results on phantom and clinical data show avery high similarity agreement with the ground truthprovided by a medical expert.
Semi-supervised segmentation, Ultrasonography, Patch features, Min-cut algorithms, Bipartite graph, LTS5, CIBM-SPC
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