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Liver Segmentation
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논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Evaluation of Preprocessing Techniques for U-Net Based Automated Liver Segmentation
Spatially Dependent U-Nets: Highly Accurate Architectures for Medical Imaging Segmentation
SAR-U-Net: squeeze-and-excitation block and atrous spatial pyramid pooling based residual U-Net for automatic liver segmentation in Computed Tomography
Multi-Slice Low-Rank Tensor Decomposition Based Multi-Atlas Segmentation: Application to Automatic Pathological Liver CT Segmentation
Automatic Liver Segmentation from CT Images Using Deep Learning Algorithms: A Comparative Study
Comparing Deep Learning strategies for paired but unregistered multimodal segmentation of the liver in T1 and T2-weighted MRI
Upgraded W-Net with Attention Gates and its Application in Unsupervised 3D Liver Segmentation
KiU-Net: Overcomplete Convolutional Architectures for Biomedical Image and Volumetric Segmentation
Unsupervised Wasserstein Distance Guided Domain Adaptation for 3D Multi-Domain Liver Segmentation
User-Guided Domain Adaptation for Rapid Annotation from User Interactions: A Study on Pathological Liver Segmentation
E$^2$Net: An Edge Enhanced Network for Accurate Liver and Tumor Segmentation on CT Scans
Learning Semantics-enriched Representation via Self-discovery, Self-classification, and Self-restoration
A Comparison of Deep Learning Convolution Neural Networks for Liver Segmentation in Radial Turbo Spin Echo Images
3D medical image segmentation with labeled and unlabeled data using autoencoders at the example of liver segmentation in CT images
Liver Segmentation in Abdominal CT Images via Auto-Context Neural Network and Self-Supervised Contour Attention
Inter-slice image augmentation based on frame interpolation for boosting medical image segmentation accuracy
Automatic segmentation and determining radiodensity of the liver in a large-scale CT database
Multimodal Self-Supervised Learning for Medical Image Analysis
Liver Segmentation from Multimodal Images using HED-Mask R-CNN
Liver segmentation and metastases detection in MR images using convolutional neural networks
Domain-Agnostic Learning with Anatomy-Consistent Embedding for Cross-Modality Liver Segmentation
Optimal input configuration of dynamic contrast enhanced MRI in convolutional neural networks for liver segmentation
Models Genesis: Generic Autodidactic Models for 3D Medical Image Analysis
Unsupervised Domain Adaptation via Disentangled Representations: Application to Cross-Modality Liver Segmentation
Generating large labeled data sets for laparoscopic image processing tasks using unpaired image-to-image translation
Fully Automatic Liver Attenuation Estimation Combing CNN Segmentation and Morphological Operations
Liver Lesion Segmentation with slice-wise 2D Tiramisu and Tversky loss function
Med3D: Transfer Learning for 3D Medical Image Analysis
Transformation Consistent Self-ensembling Model for Semi-supervised Medical Image Segmentation
The Liver Tumor Segmentation Benchmark (LiTS)
Automatic Liver Segmentation with Adversarial Loss and Convolutional Neural Network
Comparison of U-net-based Convolutional Neural Networks for Liver Segmentation in CT
A Time Series Graph Cut Image Segmentation Scheme for Liver Tumors
Holographic Visualisation of Radiology Data and Automated Machine Learning-based Medical Image Segmentation
Deeply Self-Supervised Contour Embedded Neural Network Applied to Liver Segmentation
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