Anatomy
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Benchmarks
BIG-bench
Most implemented
Automatic lung segmentation in routine imaging is primarily a data diversity problem, not a methodology problem
Transferable Visual Words: Exploiting the Semantics of Anatomical Patterns for Self-supervised Learning
Disentangled Representation Learning in Cardiac Image Analysis
Guided Reconstruction with Conditioned Diffusion Models for Unsupervised Anomaly Detection in Brain MRIs
Towards Robust Cardiac Segmentation using Graph Convolutional Networks
Papers
Are Vision Foundation Models Ready for Out-of-the-Box Medical Image Registration?
Foundation models, pre-trained on large image datasets and capable of capturing rich feature representations, have recently shown potential for zero-shot image registration. However, their performance has mostly been tes…
AnatomyImage RegistrationMedical Image RegistrationPSAT: Pediatric Segmentation Approaches via Adult Augmentations and Transfer Learning
Pediatric medical imaging presents unique challenges due to significant anatomical and developmental differences compared to adults. Direct application of segmentation models trained on adult data often yields suboptimal…
AnatomyContinual LearningData AugmentationSegmentation+1SV-DRR: High-Fidelity Novel View X-Ray Synthesis Using Diffusion Model
X-ray imaging is a rapid and cost-effective tool for visualizing internal human anatomy. While multi-view X-ray imaging provides complementary information that enhances diagnosis, intervention, and education, acquiring i…
AnatomyImage GenerationCausal-SAM-LLM: Large Language Models as Causal Reasoners for Robust Medical Segmentation
The clinical utility of deep learning models for medical image segmentation is severely constrained by their inability to generalize to unseen domains. This failure is often rooted in the models learning spurious correla…
AnatomyDisentanglementImage SegmentationMedical Image Segmentation+1Pose-Star: Anatomy-Aware Editing for Open-World Fashion Images
To advance real-world fashion image editing, we analyze existing two-stage pipelines(mask generation followed by diffusion-based editing)which overly prioritize generator optimization while neglecting mask controllabilit…
AnatomyX-SiT: Inherently Interpretable Surface Vision Transformers for Dementia Diagnosis
Interpretable models are crucial for supporting clinical decision-making, driving advances in their development and application for medical images. However, the nature of 3D volumetric data makes it inherently challengin…
AnatomyDecision MakingDecoder