학술논문

An efficient segmentation method for ultrasound images based on a semi-supervised approach and patch-based features
Document Type
Conference
Source
2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro Biomedical Imaging: From Nano to Macro, 2011 IEEE International Symposium on. :969-972 Mar, 2011
Subject
Bioengineering
Communication, Networking and Broadcast Technologies
Computing and Processing
Signal Processing and Analysis
Robotics and Control Systems
Image segmentation
Ultrasonic imaging
Speckle
Noise
Mathematical model
Tumors
Biomedical imaging
Ultrasonography
retinopathy
image segmentation
active shape model
bipartite graph
Language
ISSN
1945-7928
1945-8452
Abstract
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.