Aim
Submit automated predictions of lesion segmentation boundaries within dermoscopic images.
Background
Skin cancer is the most common cancer globally, with melanoma being the most deadly form. Dermoscopy is a skin imaging modality that has demonstrated improvement for diagnosis of skin cancer compared to unaided visual inspection. However, clinicians should receive adequate training for those improvements to be realized. In order to make expertise more widely available, the International Skin Imaging Collaboration (ISIC) has developed the ISIC Archive, an international repository of dermoscopic images, for both the purposes of clinical training, and for supporting technical research toward automated algorithmic analysis by hosting the ISIC Challenges.
Results
Challenge
Ivo Matteo Baltruschat
Co-Founder / Research Scientist
Ivo Matteo Baltruschat studied Information and Electrical Engineering at the University of Applied Sciences, Hamburg between 2010 and 2014. In 2016, he finished his Master of Science in medical engineering science at the Universität zu Lübeck with his thesis on Deep Learning for Advanced Medical Applications. During DAISYlabs, he was a PhD student in the group of Tobias Knopp at the Institute for Biomedical Imaging, Hamburg University of Technology. His research covered the automatic analysis of medical x-ray images using machine learning methods, with a focus on applying deep learning to high-resolution medical x-ray images for computer-aided diagnosis.
Thilo Sentker
Research Scientist
Frederic Madesta
PhD Student
Rüdiger Schmitz
PhD Student
Helge Kniep
PhD Student
Nils Gessert
Research Scientist
René Werner
Co-Founder / Head of scientific working group
René Werner co-founded DAISYlabs and led the scientific working group at the University Medical Center Hamburg-Eppendorf, coordinating deep learning research for biomedical image processing across UKE and TUHH.