Skin Image Analysis Datasets for Lesion Classification and Segmentation

A collection of datasets for skin image analysis, focusing on tasks like skin lesion classification and segmentation. The datasets are curated by the sfu-mial organization and are available under an MIT license. Specific row counts, column details, and dataset sizes are not provided.

Use Cases

• Train deep learning models for skin lesion classification using labeled medical images.
• Develop segmentation algorithms to delineate lesion boundaries in skin images.
• Conduct medical image analysis research on melanoma and other skin conditions.

Strengths

• Curated by a research organization (sfu-mial) specializing in medical image analysis.
• Includes data for multiple analytical tasks: classification and segmentation.
• Available under a permissive MIT license for broad use.

Limitations

• No specific dataset size, row count, or column information is available for evaluation.
• The collection's composition, including image resolution and label quality, is unspecified.
• Potential for class imbalance or geographic bias in the constituent datasets is unknown.

Provenance

Source

github repository by sfu-mial

Collection Method

Collection and curation of existing skin image datasets.

Freshness

Last updated on 2025-03-19.