{"total":27,"rows":[{"id":"2312.07330","title":"Learned representation-guided diffusion models for large-image generation","created":"2023-12-12","cited_by_count":40,"area":"diffusion"},{"id":"2405.18087","title":"FlowSDF: Flow Matching for Medical Image Segmentation Using Distance Transforms","created":"2024-05-28","cited_by_count":25,"area":"diffusion"},{"id":"2406.12120","title":"Adding Conditional Control to Diffusion Models with Reinforcement Learning","created":"2024-06-17","cited_by_count":16,"area":"diffusion"},{"id":"2411.16969","title":"ZoomLDM: Latent Diffusion Model for multi-scale image generation","created":"2024-11-25","cited_by_count":16,"area":"diffusion"},{"id":"2412.06011","title":"TopoCellGen: Generating Histopathology Cell Topology with a Diffusion Model","created":"2024-12-08","cited_by_count":16,"area":"diffusion"},{"id":"2506.23440","title":"PathDiff: Histopathology Image Synthesis with Unpaired Text and Mask Conditions","created":"2025-06-30","cited_by_count":9,"area":"diffusion"},{"id":"2407.14426","title":"Controllable and Efficient Multi-Class Pathology Nuclei Data Augmentation using Text-Conditioned Diffusion Models","created":"2024-07-19","cited_by_count":8,"area":"diffusion"},{"id":"2407.14434","title":"Co-synthesis of Histopathology Nuclei Image-Label Pairs using a Context-Conditioned Joint Diffusion Model","created":"2024-07-19","cited_by_count":8,"area":"diffusion"},{"id":"2410.20073","title":"Pixel super-resolved virtual staining of label-free tissue using diffusion models","created":"2024-10-26","cited_by_count":8,"area":"diffusion"},{"id":"2412.01672","title":"Gen-SIS: Generative Self-augmentation Improves Self-supervised Learning","created":"2024-12-02","cited_by_count":5,"area":"diffusion"},{"id":"2502.09242","title":"From large language models to multimodal AI: A scoping review on the potential of generative AI in medicine","created":"2025-02-13","cited_by_count":5,"area":"diffusion"},{"id":"2507.23001","title":"LesionGen: A Concept-Guided Diffusion Model for Dermatology Image Synthesis","created":"2025-07-30","cited_by_count":4,"area":"diffusion"},{"id":"2509.17847","title":"Semantic and Visual Crop-Guided Diffusion Models for Heterogeneous Tissue Synthesis in Histopathology","created":"2025-09-22","cited_by_count":4,"area":"diffusion"},{"id":"2312.09792","title":"Latent Diffusion Models with Image-Derived Annotations for Enhanced AI-Assisted Cancer Diagnosis in Histopathology","created":"2023-12-15","cited_by_count":3,"area":"diffusion"},{"id":"2504.06950","title":"PathSegDiff: Pathology Segmentation using Diffusion model representations","created":"2025-04-09","cited_by_count":3,"area":"diffusion"},{"id":"2407.11664","title":"Mask-guided cross-image attention for zero-shot in-silico histopathologic image generation with a diffusion model","created":"2024-07-16","cited_by_count":2,"area":"diffusion"},{"id":"2504.12351","title":"Prototype-Guided Diffusion for Digital Pathology: Achieving Foundation Model Performance with Minimal Clinical Data","created":"2025-04-15","cited_by_count":2,"area":"diffusion"},{"id":"2411.15719","title":"Comparative Analysis of Diffusion Generative Models in Computational Pathology","created":"2024-11-24","cited_by_count":1,"area":"diffusion"},{"id":"2503.08346","title":"Pathology-Aware Adaptive Watermarking for Text-Driven Medical Image Synthesis","created":"2025-03-11","cited_by_count":1,"area":"diffusion"},{"id":"2505.07866","title":"Computationally Efficient Diffusion Models in Medical Imaging: A Comprehensive Review","created":"2025-05-09","cited_by_count":1,"area":"diffusion"},{"id":"2506.10230","title":"Leveraging Clinical Text and Class Conditioning for 3D Prostate MRI Generation","created":"2025-06-11","cited_by_count":1,"area":"diffusion"},{"id":"2601.10917","title":"Self-learned representation-guided latent diffusion model for breast cancer classification in deep ultraviolet whole surface images","created":"2026-01-16","cited_by_count":1,"area":"diffusion"},{"id":"2510.09121","title":"MSDM: Generating Task-Specific Pathology Images with a Multimodal Conditioned Diffusion Model for Cell and Nuclei Segmentation","created":"2025-10-10","cited_by_count":0,"area":"diffusion"},{"id":"2601.17228","title":"Semi-Supervised Domain Adaptation with Latent Diffusion for Pathology Image Classification","created":"2026-01-23","cited_by_count":0,"area":"diffusion"},{"id":"2603.13386","title":"Layout-Guided Controllable Pathology Image Generation with In-Context Diffusion Transformers","created":"2026-03-11","cited_by_count":0,"area":"diffusion"},{"id":"2606.07036","title":"STREAM: Stochastic Riemannian Flow Matching with Anisotropic Decoder for Digital Histopathology Image Generation","created":"2026-06-05","cited_by_count":0,"area":"diffusion"},{"id":"2609.24691","title":"What Makes a Good Medical Image Tokenizer? Rethinking Reconstruction and Generation in Medical Image Tokenization","created":"2026-09-21","cited_by_count":0,"area":"diffusion"}],"next_cursor":null}