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Organ Segmentation

Papers

Showing 125 of 305 papers

TitleStatusHype
Universal and Extensible Language-Vision Models for Organ Segmentation and Tumor Detection from Abdominal Computed TomographyCode4
3D TransUNet: Advancing Medical Image Segmentation through Vision TransformersCode4
UNETR: Transformers for 3D Medical Image SegmentationCode3
Rethinking Abdominal Organ Segmentation (RAOS) in the clinical scenario: A robustness evaluation benchmark with challenging casesCode2
TotalVibeSegmentator: Full Body MRI Segmentation for the NAKO and UK BiobankCode2
MRSegmentator: Multi-Modality Segmentation of 40 Classes in MRI and CTCode2
Test-Time Adaptation with SaLIP: A Cascade of SAM and CLIP for Zero shot Medical Image SegmentationCode2
Unleashing the Potential of SAM for Medical Adaptation via Hierarchical DecodingCode2
U-Mamba: Enhancing Long-range Dependency for Biomedical Image SegmentationCode2
BRAU-Net++: U-Shaped Hybrid CNN-Transformer Network for Medical Image SegmentationCode2
MCANet: Medical Image Segmentation with Multi-Scale Cross-Axis AttentionCode2
A-Eval: A Benchmark for Cross-Dataset Evaluation of Abdominal Multi-Organ SegmentationCode2
Disruptive Autoencoders: Leveraging Low-level features for 3D Medical Image Pre-trainingCode2
AbdomenAtlas-8K: Annotating 8,000 CT Volumes for Multi-Organ Segmentation in Three WeeksCode2
Customized Segment Anything Model for Medical Image SegmentationCode2
CLIP-Driven Universal Model for Organ Segmentation and Tumor DetectionCode2
TransUNet: Transformers Make Strong Encoders for Medical Image SegmentationCode2
CRISP-SAM2: SAM2 with Cross-Modal Interaction and Semantic Prompting for Multi-Organ SegmentationCode1
CENet: Context Enhancement Network for Medical Image SegmentationCode1
PG-SAM: Prior-Guided SAM with Medical for Multi-organ SegmentationCode1
Leveraging Textual Anatomical Knowledge for Class-Imbalanced Semi-Supervised Multi-Organ SegmentationCode1
STA-Unet: Rethink the semantic redundant for Medical Imaging SegmentationCode1
TTT-Unet: Enhancing U-Net with Test-Time Training Layers for Biomedical Image SegmentationCode1
GuidedNet: Semi-Supervised Multi-Organ Segmentation via Labeled Data Guide Unlabeled DataCode1
LUCF-Net: Lightweight U-shaped Cascade Fusion Network for Medical Image SegmentationCode1
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