1k citations · 1.4k across the 2 of their papers we have counts for
4 papers
A Patient-Centric Dataset of Images and Metadata for Identifying Melanomas Using Clinical Context
Veronica Rotemberg, Nicholas Kurtansky, Brigid Betz-Stablein +21
Prior skin image datasets have not addressed patient-level information obtained from multiple skin lesions from the same patient. Though artificial intelligence classification algo…
Skin Lesion Analysis Toward Melanoma Detection 2018: A Challenge Hosted by the International Skin Imaging Collaboration (ISIC)
Noel Codella, Veronica Rotemberg, Philipp Tschandl +9
This work summarizes the results of the largest skin image analysis challenge in the world, hosted by the International Skin Imaging Collaboration (ISIC), a global partnership that…
Deep Learning Ensembles for Melanoma Recognition in Dermoscopy Images
Noel Codella, Quoc-Bao Nguyen, Sharath Pankanti +4
Melanoma is the deadliest form of skin cancer. While curable with early detection, only highly trained specialists are capable of accurately recognizing the disease. As expertise i…
Skin Lesion Analysis toward Melanoma Detection: A Challenge at the International Symposium on Biomedical Imaging (ISBI) 2016, hosted by the International Skin Imaging Collaboration (ISIC)
David Gutman, Noel C. F. Codella, Emre Celebi +4
In this article, we describe the design and implementation of a publicly accessible dermatology image analysis benchmark challenge. The goal of the challenge is to sup- port resear…