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Volumetric Medical Image Segmentation

Papers

Showing 125 of 58 papers

TitleStatusHype
MedNeXt: Transformer-driven Scaling of ConvNets for Medical Image SegmentationCode2
LHU-Net: A Light Hybrid U-Net for Cost-Efficient, High-Performance Volumetric Medical Image SegmentationCode2
SAM-Med3D: Towards General-purpose Segmentation Models for Volumetric Medical ImagesCode2
SegVol: Universal and Interactive Volumetric Medical Image SegmentationCode2
CSAM: A 2.5D Cross-Slice Attention Module for Anisotropic Volumetric Medical Image SegmentationCode1
Discrepancy Matters: Learning from Inconsistent Decoder Features for Consistent Semi-supervised Medical Image SegmentationCode1
MAPSeg: Unified Unsupervised Domain Adaptation for Heterogeneous Medical Image Segmentation Based on 3D Masked Autoencoding and Pseudo-LabelingCode1
Frequency Domain Adversarial Training for Robust Volumetric Medical SegmentationCode1
Towards Generic Semi-Supervised Framework for Volumetric Medical Image SegmentationCode1
TextBraTS: Text-Guided Volumetric Brain Tumor Segmentation with Innovative Dataset Development and Fusion Module ExplorationCode1
nnFormer: Interleaved Transformer for Volumetric SegmentationCode1
D-Net: Dynamic Large Kernel with Dynamic Feature Fusion for Volumetric Medical Image SegmentationCode1
Learnable Weight Initialization for Volumetric Medical Image SegmentationCode1
Positional Contrastive Learning for Volumetric Medical Image SegmentationCode1
Rethinking Bayesian Deep Learning Methods for Semi-Supervised Volumetric Medical Image SegmentationCode1
A Robust Volumetric Transformer for Accurate 3D Tumor SegmentationCode1
KiU-Net: Overcomplete Convolutional Architectures for Biomedical Image and Volumetric SegmentationCode1
FastSAM-3DSlicer: A 3D-Slicer Extension for 3D Volumetric Segment Anything Model with Uncertainty QuantificationCode1
Towards Foundation Models and Few-Shot Parameter-Efficient Fine-Tuning for Volumetric Organ SegmentationCode1
Boosting Convolution with Efficient MLP-Permutation for Volumetric Medical Image SegmentationCode0
Conditional Random Fields as Recurrent Neural Networks for 3D Medical Imaging SegmentationCode0
On the Compactness, Efficiency, and Representation of 3D Convolutional Networks: Brain Parcellation as a Pretext TaskCode0
Rethinking Barely-Supervised Volumetric Medical Image Segmentation from an Unsupervised Domain Adaptation PerspectiveCode0
Improving 3D Medical Image Segmentation at Boundary Regions using Local Self-attention and Global Volume MixingCode0
Memorizing SAM: 3D Medical Segment Anything Model with Memorizing TransformerCode0
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