Phantom VS mammography_metarepository

Compare Phantom vs mammography_metarepository and see what are their differences.

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Phantom mammography_metarepository
2 2
3 63
- -
10.0 0.0
over 1 year ago almost 2 years ago
Python Python
- BSD 2-clause "Simplified" License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

Phantom

Posts with mentions or reviews of Phantom. We have used some of these posts to build our list of alternatives and similar projects.

mammography_metarepository

Posts with mentions or reviews of mammography_metarepository. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-08-11.

What are some alternatives?

When comparing Phantom and mammography_metarepository you can also consider the following projects:

rt-utils - A minimal Python library to facilitate the creation and manipulation of DICOM RTStructs.

huggingface_hub - The official Python client for the Huggingface Hub.

Viewers - OHIF zero-footprint DICOM viewer and oncology specific Lesion Tracker, plus shared extension packages

medicaldetectiontoolkit - The Medical Detection Toolkit contains 2D + 3D implementations of prevalent object detectors such as Mask R-CNN, Retina Net, Retina U-Net, as well as a training and inference framework focused on dealing with medical images.

torchio - Medical imaging toolkit for deep learning

MONAILabel - MONAI Label is an intelligent open source image labeling and learning tool.

raiven - A framework for the translation of AI tools to the radiology environment

jina - ☁️ Build multimodal AI applications with cloud-native stack