14.3k citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Columbia UniversityUS16 papers
- Harvard UniversityUS13 papers
- Stanford UniversityUS12 papers
- Cornell UniversityUS11 papers
- National Institutes of HealthUS7 papers
- New York UniversityUS7 papers
- University of California, San FranciscoUS7 papers
- Emory UniversityUS6 papers
- Georgia Institute of TechnologyUS6 papers
- Hebrew University of JerusalemIL6 papers
- Imperial College LondonGB6 papers
- Mayo ClinicUS6 papers
4 papers · 2 filters
End-to-end Training for Whole Image Breast Cancer Diagnosis using An All Convolutional Design
Li Shen
We develop an end-to-end training algorithm for whole-image breast cancer diagnosis based on mammograms. It requires lesion annotations only at the first stage of training. After t…
Improving Dermoscopic Image Segmentation with Enhanced Convolutional-Deconvolutional Networks
Yading Yuan, Yeh-Chi Lo
Automatic skin lesion segmentation on dermoscopic images is an essential step in computer-aided diagnosis of melanoma. However, this task is challenging due to significant variatio…
Deep Learning to Improve Breast Cancer Early Detection on Screening Mammography
Li Shen, Laurie R. Margolies, Joseph H. Rothstein +3
The rapid development of deep learning, a family of machine learning techniques, has spurred much interest in its application to medical imaging problems. Here, we develop a deep l…
Automatic skin lesion segmentation with fully convolutional-deconvolutional networks
Yading Yuan
This paper summarizes our method and validation results for the ISBI Challenge 2017 - Skin Lesion Analysis Towards Melanoma Detection - Part I: Lesion Segmentation