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Found 5 papers, 2 papers with code
The iToBoS dataset: skin region images extracted from 3D total body photographs for lesion detection
This dataset aims to facilitate training and benchmarking of algorithms, with the goal of enabling early detection of skin cancer and deployment of this technology in non-clinical environments.
A Multimodal Vision Foundation Model for Clinical Dermatology
Diagnosing and treating skin diseases require advanced visual skills across domains and the ability to synthesize information from multiple imaging modalities.
Ugly Ducklings or Swans: A Tiered Quadruplet Network with Patient-Specific Mining for Improved Skin Lesion Classification
An ugly duckling is an obviously different skin lesion from surrounding lesions of an individual, and the ugly duckling sign is a criterion used to aid in the diagnosis of cutaneous melanoma by differentiating between highly suspicious and benign lesions.
Application of Machine Learning in Melanoma Detection and the Identification of 'Ugly Duckling' and Suspicious Naevi: A Review
As lesions within the same individual typically share similarities and follow a predictable pattern, an ugly duckling naevus stands out as unusual and may indicate the presence of a cancerous melanoma.
A Patient-Centric Dataset of Images and Metadata for Identifying Melanomas Using Clinical Context
Prior skin image datasets have not addressed patient-level information obtained from multiple skin lesions from the same patient.
