Brain-Tumor-Segmentation-And-Classification VS MONAILabel

Compare Brain-Tumor-Segmentation-And-Classification vs MONAILabel and see what are their differences.

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Brain-Tumor-Segmentation-And-Classification MONAILabel
3 1
18 541
- 2.6%
3.0 7.8
9 months ago 8 days ago
Python Python
MIT License Apache License 2.0
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.

Brain-Tumor-Segmentation-And-Classification

Posts with mentions or reviews of Brain-Tumor-Segmentation-And-Classification. We have used some of these posts to build our list of alternatives and similar projects.

MONAILabel

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

What are some alternatives?

When comparing Brain-Tumor-Segmentation-And-Classification and MONAILabel you can also consider the following projects:

dipy - DIPY is the paragon 3D/4D+ imaging library in Python. Contains generic methods for spatial normalization, signal processing, machine learning, statistical analysis and visualization of medical images. Additionally, it contains specialized methods for computational anatomy including diffusion, perfusion and structural imaging.

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.

caer - High-performance Vision library in Python. Scale your research, not boilerplate.

pytorch-toolbelt - PyTorch extensions for fast R&D prototyping and Kaggle farming

SlicerTomoSAM - An extension of 3D Slicer using the Segment Anything Model (SAM) to aid the segmentation of 3D data from tomography or other imaging techniques.

albumentations - Fast image augmentation library and an easy-to-use wrapper around other libraries. Documentation: https://albumentations.ai/docs/ Paper about the library: https://www.mdpi.com/2078-2489/11/2/125

mammography_metarepository - Meta-repository of screening mammography classifiers

FedCV - FedCV: An Industrial-grade Federated Learning Framework for Diverse Computer Vision Tasks

Active-Learning-as-a-Service - A scalable & efficient active learning/data selection system for everyone.

small-text - Active Learning for Text Classification in Python