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Liver Segmentation

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Showing 26–50 of 86 papers

TitleStatusHype
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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