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Organ Segmentation

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Showing 76–100 of 305 papers

TitleStatusHype
D-Net: Dynamic Large Kernel with Dynamic Feature Fusion for Volumetric Medical Image SegmentationCode1
Dynamic U-Net: Adaptively Calibrate Features for Abdominal Multi-organ SegmentationCode0
Dcl-Net: Dual Contrastive Learning Network for Semi-Supervised Multi-Organ Segmentation—0
AnatoMix: Anatomy-aware Data Augmentation for Multi-organ Segmentation—0
Efficient 3D affinely equivariant CNNs with adaptive fusion of augmented spherical Fourier-Bessel basesCode0
Label-efficient Multi-organ Segmentation Method with Diffusion Model—0
3D Vascular Segmentation Supervised by 2D Annotation of Maximum Intensity ProjectionCode1
Application analysis of ai technology combined with spiral CT scanning in early lung cancer screening—0
Two-View Topogram-Based Anatomy-Guided CT Reconstruction for Prospective Risk Minimization—0
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
ZePT: Zero-Shot Pan-Tumor Segmentation via Query-Disentangling and Self-PromptingCode1
Evaluating General Purpose Vision Foundation Models for Medical Image Analysis: An Experimental Study of DINOv2 on Radiology BenchmarksCode1
Adaptive Smooth Activation for Improved Disease Diagnosis and Organ Segmentation from Radiology Scans—0
Leveraging Unlabeled Data for 3D Medical Image Segmentation through Self-Supervised Contrastive LearningCode0
UniMOS: A Universal Framework For Multi-Organ Segmentation Over Label-Constrained DatasetsCode0
Versatile Medical Image Segmentation Learned from Multi-Source Datasets via Model Self-DisambiguationCode1
Transfer learning from a sparsely annotated dataset of 3D medical imagesCode1
Leveraging point annotations in segmentation learning with boundary loss—0
Pelvic floor MRI segmentation based on semi-supervised deep learning—0
LLM-driven Multimodal Target Volume Contouring in Radiation OncologyCode1
SynergyNet: Bridging the Gap between Discrete and Continuous Representations for Precise Medical Image Segmentation—0
3D TransUNet: Advancing Medical Image Segmentation through Vision TransformersCode4
AG-CRC: Anatomy-Guided Colorectal Cancer Segmentation in CT with Imperfect Anatomical KnowledgeCode0
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