Oct 24, 2017 · We propose a novel end-to-end network for mammographic mass segmentation which employs a fully convolutional network (FCN) to model a potential function.
Mass segmentation provides effective morphological features which are important for mass diagnosis. In this work, we propose a novel end-to-end network for ...
Sep 10, 2024 · Mass segmentation provides effective morphological features which are important for mass diagnosis. In this work, we propose a novel ...
In this work, we propose a novel end-to-end network for mammographic mass segmentation which employs a fully convolutional network (FCN) to model a potential ...
A novel end-to-end network for mammographic mass segmentation is proposed which employs a fully convolutional network (FCN) to model a potential function, ...
This is the first work formulating the adversarial example to improve segmentation. Three aspects to understand adversarial deep structure model 1) optimal ...
Jun 6, 2018 · Mass segmentation is an important task in mammogram analysis, providing effective morphological features and regions of interest (ROI) for mass ...
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Adversarial deep structured nets for mass segmentation from mammograms. Zhu, W., Xiang, X., Tran, T. D, Hager, G. D, & Xie, X. In 2018 IEEE 15th ...
Dec 18, 2016 · Mass segmentation is an important task in mammogram analysis, providing effective morphological features and re-.
Adversarial Deep Structured Nets for Mass Segmentation from Mammograms ... Mass segmentation provides effective morphological features which are important for ...