Public International Image Database
Engaging Stakeholder Communities
2024 Challenge
ISIC Machine Learning Challenge
In this competition, you'll develop image-based algorithms to identify histologically confirmed skin cancer cases with single-lesion crops from 3D total body photos (TBP). The image quality resembles close-up smartphone photos, which are regularly submitted for telehealth purposes. Your binary classification algorithm could be used in settings without access to specialized care and improve triage for early skin cancer detection.
The ISIC Archive
A large and expanding open-source public-access archive of skin images serves as a public resource for teaching, research, and the development and testing of diagnostic artificial intelligence algorithms
Browse tens of thousands of public images
Define an image collection and collect annotations
Access data through the command line
Contribute data from your own clinic
Serving the Clinical and Computer Vision Communities
The International Skin Imaging Collaboration (ISIC) is an academia and industry partnership designed to use digital skin imaging to help reduce skin cancer mortality.
ISIC works to achieve its goals through the development and promotion of standards for digital skin imaging, and through engaging the dermatology and computer vision communities toward improved diagnostics.
Creating and Disseminating Skin Imaging Standards
Upcoming Workshop
The Alignment Problem in Medicine
In this special session, we will explore the alignment of AI systems with human values within image-based diagnostic medicine. To integrate complex ethical principles and embed human values into AI algorithm, it is required to understand ethical frames in healthcare and apply it in AI development. Transparency and biases in AI systems will also be important discussion topics in this session.
Latest Announcements
Developing standards to ensure quality, privacy, and interoperability of dermatologic images.
Organizing workshops and ML challenges to engage with computer vision researchers.
Disseminating resources for educating the next generation of skin cancer experts.
Hosting competitions to engage the computer vision community to improve dermatologic diagnostic accuracy with the aid of AI.
The following tasks are open for live-submission scoring:
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2020: SIIM-ISIC Melanoma Classification with patient-clustered images (2 classes)
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An overview of the ISIC Archive, voiceover by Veronica Rotemberg (AI Working Group Leader)
ISIC Working Groups have published dozens of seminal papers in high-impact journals.
Our Partners
9,389 Registered Users
503,955 Public Images
1,157,577 Total Images
22 Core Publications
1000+ Citations
Generously funded by The Shore Family Fund
The International Skin Imaging Collaboration
Improving Skin Cancer Diagnosis by
● Promoting Standards in Skin Imaging
● Gathering and Sharing Dermatologic Images
● Engaging Clinicians & Computer Vision Researchers
