Journal article

An image segmentation framework for extracting tumors from breast magnetic resonance images

Le Sun, Jinyuan He, Xiaoxia Yin, Yanchun Zhang, Jeon-Hor Chen, Tomas Kron, Min-Ying Su

JOURNAL OF INNOVATIVE OPTICAL HEALTH SCIENCES | WORLD SCIENTIFIC PUBL CO PTE LTD | Published : 2018

Abstract

Magnetic resonance imaging (MRI) has been a prevalence technique for breast cancer diagnosis. Computer-aided detection and segmentation of lesions from MRIs plays a vital role for the MRI-based disease analysis. There are two main issues of the existing breast lesion segmentation techniques: requiring manual delineation of Regions of Interests (ROIs) as a step of initialization; and requiring a large amount of labeled images for model construction or parameter learning, while in real clinical or experimental settings, it is highly challenging to get sufficient labeled MRIs. To resolve these issues, this work proposes a semi-supervised method for breast tumor segmentation based on super voxel..

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Grants

Awarded by National Natural Science Foundation of China


Awarded by Natural Science Foundation of Jiangsu Province


Funding Acknowledgements

This paper is supported by the National Natural Science Foundation of China (Grants No 61702274) and the Natural Science Foundation of Jiangsu Province (Grants No BK20170958).