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3D Medical Imaging Segmentation

3D medical imaging segmentation is the task of segmenting medical objects of interest from 3D medical imaging.

( Image credit: Elastic Boundary Projection for 3D Medical Image Segmentation )

Papers

Showing 110 of 41 papers

TitleStatusHype
xLSTM-UNet can be an Effective 2D & 3D Medical Image Segmentation Backbone with Vision-LSTM (ViL) better than its Mamba CounterpartCode3
UNETR: Transformers for 3D Medical Image SegmentationCode3
MIST: A Simple and Scalable End-To-End 3D Medical Imaging Segmentation FrameworkCode2
nnMamba: 3D Biomedical Image Segmentation, Classification and Landmark Detection with State Space ModelCode2
LoRKD: Low-Rank Knowledge Decomposition for Medical Foundation ModelsCode1
FastSAM3D: An Efficient Segment Anything Model for 3D Volumetric Medical ImagesCode1
SegReg: Segmenting OARs by Registering MR Images and CT AnnotationsCode1
Reliable brain morphometry from contrast‐enhanced T1w‐MRI in patients with multiple sclerosisCode1
An Embarrassingly Simple Consistency Regularization Method for Semi-Supervised Medical Image SegmentationCode1
Direct cortical thickness estimation using deep learning‐based anatomy segmentation and cortex parcellationCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Holistic-nested CNNDice Score81.3Unverified
2Multi-class 3D FCNDice Score76.8Unverified