Unsupervised Anatomical Feature Learning via Diffusion Models: Enhanced Medical Image Segmentation with Denoising Diffusion Probabilistic Models
cs.CV, cs.AI, cs.LG
Submitted: 2026-08-26
Updated: 2026-08-26
Comments: 15 pages, 5 figures. Submitted for peer review
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Terminology
Sources
- How inter-rater variability relates to aleatoric and epistemic uncertainty: a case study with deep learning-based paraspinal muscle segmentation
- A Simple Framework for Contrastive Learning of Visual Representations
- Momentum Contrast for Unsupervised Visual Representation Learning
- Self-supervised Visual Feature Learning with Deep Neural Networks: A Survey
- Masked Autoencoders Are Scalable Vision Learners
- Improved Baselines with Momentum Contrastive Learning
- Label-Efficient Semantic Segmentation with Diffusion Models
- SegDiff: Image Segmentation with Diffusion Probabilistic Models
- MedSegDiff-V2: Diffusion based Medical Image Segmentation with Transformer
- Adam: A Method for Stochastic Optimization
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