mahmoodlab/HIPT
Hierarchical Image Pyramid Transformer - CVPR 2022 (Oral)
This tool helps medical researchers and pathologists analyze extremely large, high-resolution whole-slide images (WSIs), common in cancer pathology. It takes gigapixel WSI files and processes them to generate a single, meaningful representation of the entire slide. Researchers can then use this representation for tasks like classifying cancer types or predicting patient outcomes, ultimately aiding in disease understanding and diagnosis.
615 stars. No commits in the last 6 months.
Use this if you need to extract meaningful, high-level features from very large, detailed medical images like whole-slide pathology scans for machine learning applications.
Not ideal if your images are small, standard-resolution photographs or if you primarily work with tabular data rather than images.
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Mar 19, 2024
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