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3D Medical Imaging Segmentation
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3D medical imaging segmentation is the task of segmenting medical objects of interest from 3D medical imaging.
<span style="color:grey; opacity: 0.6">( Image credit: Elastic Boundary Projection for 3D Medical Image Segmentation )</span>
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
UNet-3D with Adaptive TverskyCE Loss for Pancreas Medical Image Segmentation
A Dual-Task Synergy-Driven Generalization Framework for Pancreatic Cancer Segmentation in CT Scans
Leveraging Anatomical Priors for Automated Pancreas Segmentation on Abdominal CT
3D Medical Imaging Segmentation on Non-Contrast CT
A Novel Convolutional-Free Method for 3D Medical Imaging Segmentation
Leveraging Multiphase CT for Quality Enhancement of Portal Venous CT: Utility for Pancreas Segmentation
DMC-Net: Lightweight Dynamic Multi-Scale and Multi-Resolution Convolution Network for Pancreas Segmentation in CT Images
LoRKD: Low-Rank Knowledge Decomposition for Medical Foundation Models
Influence of Early through Late Fusion on Pancreas Segmentation from Imperfectly Registered Multimodal MRI
MIST: A Simple and Scalable End-To-End 3D Medical Imaging Segmentation Framework
Deep Learning for Pancreas Segmentation: a Systematic Review
xLSTM-UNet can be an Effective 2D & 3D Medical Image Segmentation Backbone with Vision-LSTM (ViL) better than its Mamba Counterpart
Large-Scale Multi-Center CT and MRI Segmentation of Pancreas with Deep Learning
Detection of Peri-Pancreatic Edema using Deep Learning and Radiomics Techniques
Diffusion Probabilistic Multi-cue Level Set for Reducing Edge Uncertainty in Pancreas Segmentation
FastSAM3D: An Efficient Segment Anything Model for 3D Volumetric Medical Images
nnMamba: 3D Biomedical Image Segmentation, Classification and Landmark Detection with State Space Model
M3BUNet: Mobile Mean Max UNet for Pancreas Segmentation on CT-Scans
SCPMan: Shape Context and Prior Constrained Multi-scale Attention Network for Pancreatic Segmentation
SegReg: Segmenting OARs by Registering MR Images and CT Annotations
Curriculum Knowledge Switching for Pancreas Segmentation
Compete to Win: Enhancing Pseudo Labels for Barely-supervised Medical Image Segmentation
Detection and Segmentation of Pancreas using Morphological Snakes and Deep Convolutional Neural Networks
Cats: Complementary CNN and Transformer Encoders for Segmentation
An Open-Source Tool for Longitudinal Whole-Brain and White Matter Lesion Segmentation
Unsupervised Domain Adaptation through Shape Modeling for Medical Image Segmentation
Dynamic Linear Transformer for 3D Biomedical Image Segmentation
Multi-organ Segmentation Network with Adversarial Performance Validator
Auto-FedRL: Federated Hyperparameter Optimization for Multi-institutional Medical Image Segmentation
An Embarrassingly Simple Consistency Regularization Method for Semi-Supervised Medical Image Segmentation
Transformer-Unet: Raw Image Processing with Unet
Hierarchical 3D Feature Learning for Pancreas Segmentation
Multi-task Federated Learning for Heterogeneous Pancreas Segmentation
Uncertainty-Based Dynamic Graph Neighborhoods For Medical Segmentation
Auto-FedAvg: Learnable Federated Averaging for Multi-Institutional Medical Image Segmentation
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