publication . Report . Part of book or chapter of book . 2020

Applications of generative adversarial networks to dermatologic imaging

Fabian Furger; Ludovic Amruthalingam; Alexander A. Navarini; Marc Pouly;
Open Access
  • Published: 10 Jun 2020
  • Publisher: Zenodo
  • Country: Switzerland
Abstract
Even though standard dermatological images are relatively easy to take, the availability and public release of such dataset for machine learning is notoriously limited due to medical data legal constraints, availability of field experts for annotation, numerous and sometimes rare diseases, large variance of skin pigmentation or the presence of identifying factors such as fingerprints or tattoos. With these generic issues in mind, we explore the application of Generative Adversarial Networks (GANs) to three different types of images showing full hands, skin lesions, and varying degrees of eczema. A first model generates realistic images of all three types with a ...
Subjects
free text keywords: Adversarial system, Segmentation, Artificial intelligence, business.industry, business, Supervised learning, Source code, media_common.quotation_subject, media_common, Generative grammar, Data set, Ground truth, Annotation, Machine learning, computer.software_genre, computer, Computer science
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Open Access
Zenodo
Report . 2020
Provider: Datacite
Open Access
ZENODO
Report . 2020
Provider: ZENODO
Open Access
Zenodo
Report . 2020
Provider: Datacite
Open Access
https://zenodo.org/record/3873...
Part of book or chapter of book
Provider: UnpayWall
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