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Liver Segmentation

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Showing 1–50 of 86 papers

TitleStatusHype
Attention GhostUNet++: Enhanced Segmentation of Adipose Tissue and Liver in CT ImagesCode1
Cross Modality Medical Image Synthesis for Improving Liver Segmentation—0
A Reverse Mamba Attention Network for Pathological Liver SegmentationCode1
Registration of Longitudinal Liver Examinations for Tumor Progress Assessment—0
ProKAN: Progressive Stacking of Kolmogorov-Arnold Networks for Efficient Liver Segmentation—0
SmoothSegNet: A Global-Local Framework for Liver Tumor Segmentation with Clinical KnowledgeInformed Label SmoothingCode0
Towards Synergistic Deep Learning Models for Volumetric Cirrhotic Liver Segmentation in MRIs—0
Research on Tumors Segmentation based on Image Enhancement Method—0
A Classification-Based Adaptive Segmentation Pipeline: Feasibility Study Using Polycystic Liver Disease and Metastases from Colorectal Cancer CT Images—0
CT Liver Segmentation via PVT-based Encoding and Refined DecodingCode1
From Denoising Training to Test-Time Adaptation: Enhancing Domain Generalization for Medical Image SegmentationCode1
FourierLoss: Shape-Aware Loss Function with Fourier Descriptors—0
SAM^Med: A medical image annotation framework based on large vision model—0
Mci-net: multi-scale context integrated network for liver ct image segmentationCode0
Liver Segmentation in Time-resolved C-arm CT Volumes Reconstructed from Dynamic Perfusion Scans using Time Separation Technique—0
Encoding feature supervised UNet++: Redesigning Supervision for liver and tumor segmentation—0
Fully Automated Deep Learning-enabled Detection for Hepatic Steatosis on Computed Tomography: A Multicenter International Validation Study—0
What can we learn about a generated image corrupting its latent representation?—0
Efficient liver segmentation with 3D CNN using computed tomography scans—0
Liver Segmentation using Turbolift Learning for CT and Cone-beam C-arm Perfusion ImagingCode0
Learning to segment with limited annotations: Self-supervised pretraining with regression and contrastive loss in MRI—0
Decoupled Pyramid Correlation Network for Liver Tumor Segmentation from CT images—0
FedNorm: Modality-Based Normalization in Federated Learning for Multi-Modal Liver Segmentation—0
Transformer based Generative Adversarial Network for Liver SegmentationCode0
Scheduling Techniques for Liver Segmentation: ReduceLRonPlateau Vs OneCycleLR—0
Deep Learning-based Assessment of Hepatic Steatosis on chest CT—0
Cross-Modality Multi-Atlas Segmentation via Deep Registration and Label FusionCode1
RA V-Net: Deep learning network for automated liver segmentation—0
Robust End-to-End Focal Liver Lesion Detection using Unregistered Multiphase Computed Tomography ImagesCode1
OSS-Net: Memory Efficient High Resolution Semantic Segmentation of 3D Medical DataCode1
EAR-U-Net: EfficientNet and attention-based residual U-Net for automatic liver segmentation in CT—0
Robust Segmentation Models using an Uncertainty Slice Sampling Based Annotation Workflow—0
Training on Polar Image Transformations Improves Biomedical Image SegmentationCode1
Unsupervised domain adaptation for cross-modality liver segmentation via joint adversarial learning and self-learningCode1
Box-Adapt: Domain-Adaptive Medical Image Segmentation using Bounding BoxSupervision—0
Context-aware PolyUNet for Liver and Lesion Segmentation from Abdominal CT Images—0
Anatomy-guided Multimodal Registration by Learning Segmentation without Ground Truth: Application to Intraprocedural CBCT/MR Liver Segmentation and RegistrationCode1
Deep Implicit Statistical Shape Models for 3D Medical Image DelineationCode1
Evaluation of Preprocessing Techniques for U-Net Based Automated Liver Segmentation—0
Spatially Dependent U-Nets: Highly Accurate Architectures for Medical Imaging Segmentation—0
SAR-U-Net: squeeze-and-excitation block and atrous spatial pyramid pooling based residual U-Net for automatic liver segmentation in Computed Tomography—0
Multi-Slice Low-Rank Tensor Decomposition Based Multi-Atlas Segmentation: Application to Automatic Pathological Liver CT Segmentation—0
Automatic Liver Segmentation from CT Images Using Deep Learning Algorithms: A Comparative StudyCode0
Comparing Deep Learning strategies for paired but unregistered multimodal segmentation of the liver in T1 and T2-weighted MRI—0
Upgraded W-Net with Attention Gates and its Application in Unsupervised 3D Liver SegmentationCode0
KiU-Net: Overcomplete Convolutional Architectures for Biomedical Image and Volumetric SegmentationCode1
Unsupervised Wasserstein Distance Guided Domain Adaptation for 3D Multi-Domain Liver Segmentation—0
User-Guided Domain Adaptation for Rapid Annotation from User Interactions: A Study on Pathological Liver Segmentation—0
E^2Net: An Edge Enhanced Network for Accurate Liver and Tumor Segmentation on CT Scans—0
Learning Semantics-enriched Representation via Self-discovery, Self-classification, and Self-restorationCode1
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