medicaldetectiontoolkit
MONAILabel
| medicaldetectiontoolkit | MONAILabel | |
|---|---|---|
| 2 | 1 | |
| 1,269 | 541 | |
| 0.3% | 2.6% | |
| 0.0 | 7.8 | |
| 29 days ago | 8 days ago | |
| Python | Python | |
| Apache License 2.0 | Apache License 2.0 |
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medicaldetectiontoolkit
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3D rcnn
Checkout https://github.com/MIC-DKFZ/medicaldetectiontoolkit, they have a recent 3d rcnn implementation. Their paper is a good start on the topic. Also have a look at nnDetection from the same group, it might provide some more leads. Hth
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3D Faster R-CNN for microscopy image analysis
I'm doing research in the area of biomedical image processing using deep learning. At the moment, I'm focused in the detection of biological structures in 3D microscopy images. For this task I trained a Faster R-CNN architecture, however I noticed that while the training loss is decreasing the validation loss is high, doesn't decrease and sometimes oscillates. When I looked at the results, the bounding boxes in the training and validation sets were too small but located at random spots. At first I thought that I should adjust the size of the anchors, however, even after trying different anchor sizes the results didn't improve. I would like to know if anyone has experience in working with 3D Faster R-CNN that could help me with suggestions for this project. (btw, I'm using the code available in this repo). Thanks in advance.
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?
nnUNet
pytorch-toolbelt - PyTorch extensions for fast R&D prototyping and Kaggle farming
mmdetection3d - OpenMMLab's next-generation platform for general 3D object detection.
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.
Mask-RCNN-TF2 - Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow 2.0
mammography_metarepository - Meta-repository of screening mammography classifiers
BlenderProc - A procedural Blender pipeline for photorealistic training image generation
Active-Learning-as-a-Service - A scalable & efficient active learning/data selection system for everyone.
PaddleDetection - Object Detection toolkit based on PaddlePaddle. It supports object detection, instance segmentation, multiple object tracking and real-time multi-person keypoint detection.
Brain-Tumor-Segmentation-And-Classification - Brain Tumor Segmentation And Classification using artificial intelligence
BCNet - Deep Occlusion-Aware Instance Segmentation with Overlapping BiLayers [CVPR 2021]
small-text - Active Learning for Text Classification in Python