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A Label-Free Segmentation Approach for Intravital Imaging of Mammary Tumor Microenvironment
Published on: May 24, 2022
A robust graph-based segmentation method for breast tumors in ultrasound images
Qing-Hua Huang1, Su-Ying Lee, Long-Zhong Liu
1School of Electronic and Information Engineering, South China University of Technology, Guangzhou, China.
Objectives:
This paper introduces a new graph-based method for segmenting breast tumors in US images.
Background And Motivation:
Segmentation for breast tumors in ultrasound (US) images is crucial for computer-aided diagnosis system, but it has always been a difficult task due to the defects inherent in the US images, such as speckles and low contrast.
Methods:
The proposed segmentation algorithm constructed a graph using improved neighborhood models. In addition, taking advantages of local statistics, a new pair-wise region comparison predicate that was insensitive to noises was proposed to determine the mergence of any two of adjacent subregions.
Results And Conclusion:
Experimental results have shown that the proposed method could improve the segmentation accuracy by 1.5-5.6% in comparison with three often used segmentation methods, and should be capable of segmenting breast tumors in US images.
