pathml

Tools for computational pathology (by Dana-Farber-AIOS)
Add to my DEV experience Machine Learning digital-pathology computational-pathology biomedical-image-processing pathology histopathology spatial-transcriptomics image-analysis microscopy fluorescence-microscopy-imaging Deep Learning Python Pytorch Research pathml
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pathml.org
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pathml reviews and mentions

Posts with mentions or reviews of pathml. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-11-17.
  • Hilo Semanal de Consultas IT - Asesoría Técnica, Desarrollo Profesional y Aprendizaje
    1 project | /r/chileIT | 28 Jun 2023
  • Dask – a flexible library for parallel computing in Python
    8 projects | news.ycombinator.com | 17 Nov 2021
    We have been using dask to support our computational pathology workflows [1], where the images are so big that they cannot be loaded in memory, let alone analyzed (standard pathology whole slide images are ~1GB; some microscopy techniques generate images >1TB). We divide each image into a bunch of smaller tiles and process each tile independently. The dask.distributed scheduler lets us scale up by distributing the tile processing across a cluster.

    Benefits of dask.distributed: easy to get up and running, and has support for spinning up clusters on lots of different computing platforms (local machines, HPC cluster, k8s, etc.)

    One difficulty is optimizing performance - there are so many configuration details (job size, number of workers, worker resources, etc. etc.) that it's been hard to know what is best.

    [1] https://github.com/Dana-Farber-AIOS/pathml

Stats

Basic pathml repo stats
2
362
8.0
21 days ago

Dana-Farber-AIOS/pathml is an open source project licensed under GNU General Public License v3.0 only which is an OSI approved license.

The primary programming language of pathml is Python.

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