DigitalSlideArchive/HistomicsTK
A Python library providing machine learning algorithms for analyzing whole-slide digital pathology images.
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HistomicsTK is a Python package for computational analysis of digital pathology images, functioning either as a standalone library or as a plugin for the Digital Slide Archive platform. It offers image analysis algorithms that leverage machine learning to characterize tissue contents in high-resolution whole-slide images. The toolkit enables users to apply computational methods to understand relationships between histology, clinical outcomes, and molecular data.
Frequently asked
- What is DigitalSlideArchive/HistomicsTK?
- A Python library providing machine learning algorithms for analyzing whole-slide digital pathology images.
- Is HistomicsTK open source?
- Yes — DigitalSlideArchive/HistomicsTK is open source, released under the Apache-2.0 license.
- What language is HistomicsTK written in?
- DigitalSlideArchive/HistomicsTK is primarily written in Python.
- How popular is HistomicsTK?
- DigitalSlideArchive/HistomicsTK has 476 stars on GitHub.
- Where can I find HistomicsTK?
- DigitalSlideArchive/HistomicsTK is on GitHub at https://github.com/DigitalSlideArchive/HistomicsTK.