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...

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Bibliographic Details
Published in2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro pp. 969 - 972
Main Authors Ciurte, A, Houhou, N, Nedevschi, S, Pica, A, Munier, F L, Thiran, J-Ph, Bresson, X, Cuadra, M Bach
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.03.2011
Subjects
active shape model
Biomedical imaging
bipartite graph
Image segmentation
Mathematical model
Noise
retinopathy
Speckle
Tumors
Ultrasonic imaging
Ultrasonography
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Summary: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.
ISBN:1424441277
9781424441273
ISSN:1945-7928
1945-8452
DOI:10.1109/ISBI.2011.5872564