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

Details

Serval ID
serval:BIB_8C933F116BF4
Type
Inproceedings: an article in a conference proceedings.
Collection
Publications
Institution
Title
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
Author(s)
Ciurte A.R., Houhou N., Nedevschi S., Pica A., Munier F., Thiran J.P., Bresson X., Bach Cuadra M.
Address
Chicago, Illinois, USA, March 30 - April 2, 2011
ISBN
1945-7928
Publication state
Published
Issued date
2011
Volume
2011
Series
Biomedical Imaging
Pages
969-972
Language
english
Abstract
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.
Keywords
Semi-supervised segmentation, Ultrasonography, Patch features, Min-cut algorithms, Bipartite graph, LTS5, CIBM-SPC
Create date
29/11/2011 16:40
Last modification date
20/08/2019 14:50
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