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Liver Segmentation

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Showing 26–50 of 86 papers

TitleStatusHype
Transformer based Generative Adversarial Network for Liver SegmentationCode0
Liver Lesion Segmentation with slice-wise 2D Tiramisu and Tversky loss functionCode0
Upgraded W-Net with Attention Gates and its Application in Unsupervised 3D Liver SegmentationCode0
Fully Automatic Liver Attenuation Estimation Combing CNN Segmentation and Morphological OperationsCode0
FourierLoss: Shape-Aware Loss Function with Fourier Descriptors—0
Hierarchical Convolutional-Deconvolutional Neural Networks for Automatic Liver and Tumor Segmentation—0
Holographic Visualisation of Radiology Data and Automated Machine Learning-based Medical Image Segmentation—0
Inter-slice image augmentation based on frame interpolation for boosting medical image segmentation accuracy—0
Learning to segment with limited annotations: Self-supervised pretraining with regression and contrastive loss in MRI—0
Liver lesion segmentation informed by joint liver segmentation—0
Liver Segmentation from Multimodal Images using HED-Mask R-CNN—0
Liver Segmentation in Abdominal CT Images by Adaptive 3D Region Growing—0
Liver segmentation in CT images using three dimensional to two dimensional fully convolutional network—0
Liver Segmentation in Time-resolved C-arm CT Volumes Reconstructed from Dynamic Perfusion Scans using Time Separation Technique—0
SAM^Med: A medical image annotation framework based on large vision model—0
Multimodal Self-Supervised Learning for Medical Image Analysis—0
Multi-Slice Low-Rank Tensor Decomposition Based Multi-Atlas Segmentation: Application to Automatic Pathological Liver CT Segmentation—0
Neural Network-Based Automatic Liver Tumor Segmentation With Random Forest-Based Candidate Filtering—0
ProKAN: Progressive Stacking of Kolmogorov-Arnold Networks for Efficient Liver Segmentation—0
RA V-Net: Deep learning network for automated liver segmentation—0
Registration of Longitudinal Liver Examinations for Tumor Progress Assessment—0
Research on Tumors Segmentation based on Image Enhancement Method—0
Robust Segmentation Models using an Uncertainty Slice Sampling Based Annotation Workflow—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
Scheduling Techniques for Liver Segmentation: ReduceLRonPlateau Vs OneCycleLR—0
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