Papers with Code 아카이브
Brain Segmentation
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<span style="color:grey; opacity: 0.6">( Image credit: 3D fully convolutional networks for subcortical segmentation in MRI: A large-scale study )</span>
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
FLAIRBrainSeg: Fine-grained brain segmentation using FLAIR MRI only
Exploring Robustness of Cortical Morphometry in the presence of white matter lesions, using Diffusion Models for Lesion Filling
Transfer Risk Map: Mitigating Pixel-level Negative Transfer in Medical Segmentation
Full-Head Segmentation of MRI with Abnormal Brain Anatomy: Model and Data Release
Unified 3D MRI Representations via Sequence-Invariant Contrastive Learning
VPBSD:Vessel-Pattern-Based Semi-Supervised Distillation for Efficient 3D Microscopic Cerebrovascular Segmentation
SegQC: a segmentation network-based framework for multi-metric segmentation quality control and segmentation error detection in volumetric medical images
Comparative Study of Probabilistic Atlas and Deep Learning Approaches for Automatic Brain Tissue Segmentation from MRI Using N4 Bias Field Correction and Anisotropic Diffusion Pre-processing Techniques
Bilateral Hippocampi Segmentation in Low Field MRIs Using Mutual Feature Learning via Dual-Views
MedSegMamba: 3D CNN-Mamba Hybrid Architecture for Brain Segmentation
Label-Efficient 3D Brain Segmentation via Complementary 2D Diffusion Models with Orthogonal Views
Deep learning-based brain segmentation model performance validation with clinical radiotherapy CT
Investigation of Energy-efficient AI Model Architectures and Compression Techniques for "Green" Fetal Brain Segmentation
Region-based U-net for accelerated training and enhanced precision in deep brain segmentation
Transferring Ultrahigh-Field Representations for Intensity-Guided Brain Segmentation of Low-Field Magnetic Resonance Imaging
Expert-Adaptive Medical Image Segmentation
Multi-Center Fetal Brain Tissue Annotation (FeTA) Challenge 2022 Results
Segment anything model (SAM) for brain extraction in fMRI studies
Brain-ID: Learning Contrast-agnostic Anatomical Representations for Brain Imaging
Artificial Intelligence in Fetal Resting-State Functional MRI Brain Segmentation: A Comparative Analysis of 3D UNet, VNet, and HighRes-Net Models
All Sizes Matter: Improving Volumetric Brain Segmentation on Small Lesions
UPL-SFDA: Uncertainty-aware Pseudo Label Guided Source-Free Domain Adaptation for Medical Image Segmentation
Comprehensive analysis of synthetic learning applied to neonatal brain MRI segmentation
Enhancing Hierarchical Transformers for Whole Brain Segmentation with Intracranial Measurements Integration
Brain MRI Segmentation using Template-Based Training and Visual Perception Augmentation
Numerical Uncertainty of Convolutional Neural Networks Inference for Structural Brain MRI Analysis
Direct segmentation of brain white matter tracts in diffusion MRI
UM-CAM: Uncertainty-weighted Multi-resolution Class Activation Maps for Weakly-supervised Fetal Brain Segmentation
Two Independent Teachers are Better Role Model
Mixup-Privacy: A simple yet effective approach for privacy-preserving segmentation
Model-based inexact graph matching on top of CNNs for semantic scene understanding
Joint Self-Supervised Image-Volume Representation Learning with Intra-Inter Contrastive Clustering
Semi-supervised Learning with Robust Loss in Brain Segmentation
UNesT: Local Spatial Representation Learning with Hierarchical Transformer for Efficient Medical Segmentation
Contour Dice loss for structures with Fuzzy and Complex Boundaries in Fetal MRI
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.