Active-Learning-as-a-Service
MONAILabel
Active-Learning-as-a-Service | MONAILabel | |
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1 | 1 | |
210 | 552 | |
0.0% | 4.5% | |
4.8 | 7.9 | |
6 months ago | 4 days ago | |
Python | Python | |
Apache License 2.0 | Apache License 2.0 |
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Active-Learning-as-a-Service
MONAILabel
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[D] Need to find a good self-hosted medical image annotation tool.
I've also found MONAILabel(https://github.com/Project-MONAI/MONAILabel), but it apparently requires GPU which makes it really expensive. I'd rather find a cpu based solution because our task is not that complex. We only get some Dicom files (each have studies in them), and want to label them.
What are some alternatives?
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.
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.
mammography_metarepository - Meta-repository of screening mammography classifiers
Brain-Tumor-Segmentation-And-Classification - Brain Tumor Segmentation And Classification using artificial intelligence
small-text - Active Learning for Text Classification in Python
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.