https://github.com/DIAGNijmegen/pathology-whole-slide-data

A package for working with whole-slide data including a fast batch iterator that can be used to train deep learning models.
https://github.com/DIAGNijmegen/pathology-whole-slide-data

computational-pathology deep-learning histopathology iterator pathology python whole-slide-annotation whole-slide-data whole-slide-dataset whole-slide-image whole-slide-imaging whole-slide-mask wsa wsd wsi wsm

Last synced: about 2 months ago
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A package for working with whole-slide data including a fast batch iterator that can be used to train deep learning models.

• Host: GitHub
• URL: https://github.com/DIAGNijmegen/pathology-whole-slide-data
• Owner: DIAGNijmegen
• License: apache-2.0
• Created: 2021-09-07T05:23:50.000Z (over 3 years ago)
• Default Branch: main
• Last Pushed: 2024-11-07T12:43:30.000Z (about 2 months ago)
• Last Synced: 2024-11-07T13:44:02.477Z (about 2 months ago)
• Topics: computational-pathology, deep-learning, histopathology, iterator, pathology, python, whole-slide-annotation, whole-slide-data, whole-slide-dataset, whole-slide-image, whole-slide-imaging, whole-slide-mask, wsa, wsd, wsi, wsm
• Language: Python
• Homepage: https://diagnijmegen.github.io/pathology-whole-slide-data/
• Size: 93.7 MB
• Stars: 93
• Watchers: 6
• Forks: 27
• Open Issues: 4
• Metadata Files:
  • Readme: README.md
  • Changelog: CHANGELOG.md
  • License: LICENSE
  • Citation: CITATION.cff

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• awesome-pathology - WholeSlideData - Batch iterator that enables fast, efficient and easy patch sampling. (Software / Image IO)