ArticleBioengineering (Basel, Switzerland)2023
Med-cDiff: Conditional Medical Image Generation with Diffusion Models.
Article in Bioengineering (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.
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Who cites it
15 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A systematic literature review: deep learning techniques for synthetic medical image generation and their applications in radiotherapy.Frontiers in radiology · 2024Pooled it
- A Systematic Review on Synthetic Medical Images Generation-Recent Trends and Future Opportunities.Diagnostics (Basel, Switzerland) · 2026Review
- From Structure to Function and Back Again: A GAN-Guided Diffusion Framework for Generating Clinically Meaningful Multimodal Neuroimaging Data.Research square · 2026Article
- A Systematic Review of Diffusion Models for Medical Image-Based Diagnosis: Methods, Taxonomies, Clinical Integration, Explainability, and Future Directions.Diagnostics (Basel, Switzerland) · 2026Review
- Deep Convolutional Generative Adversarial Network for Improved Cardiac Image Classification in Heart Disease Diagnosis.Journal of imaging informatics in medicine · 2025Article
- Implementation of a Conditional Latent Diffusion-Based Generative Model to Synthetically Create Unlabeled Histopathological Images.Bioengineering (Basel, Switzerland) · 2025Article
- Evaluation of Perceptual Realism and Clinical Plausibility of AI-Generated Colon Polyp Images.Biomedicines · 2025Article
- Combining diffusion and transformer models for enhanced promoter synthesis and strength prediction in deep learning.mSystems · 2025Article
- MPR-DIFF: A SELF-SUPERVISED DIFFUSION MODEL FOR MULTI-PLANAR REFORMATION IN PROSTATE MICRO-ULTRASOUND IMAGING.Proceedings. IEEE International Symposium on Biomedical Imaging · 2025Article
- MRI Super-Resolution With Partial Diffusion Models.IEEE transactions on medical imaging · 2025Article
- Dual-Stream Attention-Based Classification Network for Tibial Plateau Fractures via Diffusion Model Augmentation and Segmentation Map Integration.Current medical science · 2025Article
- Feasibility of generating sagittal radiographs from coronal views using GAN-based deep learning framework in adolescent idiopathic scoliosis.European radiology experimental · 2025Article
- NExpR: Neural Explicit Representation for fast arbitrary-scale medical image super-resolution.Computers in biology and medicine · 2025Article
- Article
- Research on improved black widow algorithm for medical image denoising.Scientific reports · 2024Article
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Authors and funding
7 authors.
Funding
Abstract
Conditional image generation plays a vital role in medical image analysis as it is effective in tasks such as super-resolution, denoising, and inpainting, among others. Diffusion models have been shown to perform at a state-of-the-art level in natural image generation, but they have not been thoroughly studied in medical image generation with specific conditions. Moreover, current medical image generation models have their own problems, limiting their usage in various medical image generation tasks. In this paper, we introduce the use of conditional Denoising Diffusion Probabilistic Models (cDDPMs) for medical image generation, which achieve state-of-the-art performance on several medical image generation tasks.
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Registered trials
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