Deep Generative Models : 4th MICCAI Workshop, DGM4MICCAI 2024, held in conjunction with MICCAI 2024, Marrakesh, Morocco, October 10, 2024, Proceedings / Anirban Mukhopadhyay, Ilkay Oksuz, Sandy Engelhardt, Dorit Mehrof, Yixuan Yuan, editors.

This book constitutes the proceedings of the 4th workshop on Deep Generative Models for Medical Image Computing and Computer Assisted Intervention, DGM4MICCAI 2024, held in conjunction with the 27th International conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2024, in Marrakesh, Morocco in October 2024. The 21 papers presented here were carefully reviewed and selected from 40 submissions. These papers deal with a broad range of topics, ranging from methodology (such as Causal inference, Latent interpretation, Generative factor analysis) to Applications (such as Mammography, Vessel imaging, Surgical videos and more).

Includes author index.

Online resource; title from PDF title page (SpringerLink, viewed October 16, 2024).

References -- Energy-Based Prior Latent Space Diffusion Model for Reconstruction of Lumbar Vertebrae from Thick Slice MRI -- 1 Introduction -- 2 Previous Work -- 3 Method -- 4 Results -- 4.1 Datasets and Metrics -- 4.2 Lumbar Vertebrae Reconstruction -- 4.3 Convergence in the Latent Space -- 5 Conclusions -- References -- Anatomically-Guided Inpainting for Local Synthesis of Normal Chest Radiographs -- 1 Introduction -- 2 Methods -- 2.1 Datasets -- 2.2 Chest Radiography Inpainting -- 2.3 Anatomically-Guided Chest Radiography Inpainting -- 3 Experiments -- 4 Results and Discussion -- 5 Conclusion

References -- Enhancing Cross-Modal Medical Image Segmentation Through Compositionality -- 1 Introduction -- 2 Methodology -- 3 Experiments -- 4 Conclusions -- References -- Unpaired Modality Translation for Pseudo Labeling of Histology Images -- 1 Introduction -- 2 Methods -- 2.1 Data -- 2.2 Models -- 2.3 Experiments -- 3 Results and Discussion -- 4 Conclusion -- References -- SNAFusion: Distilling 2D Axial Plane Diffusion Priors for Sparse-View 3D Cone-Beam CT Imaging -- 1 Introduction -- 2 Background -- 3 Method -- 3.1 Main Idea -- 3.2 Density Initialization -- 3.3 Density Refinement

Intro -- Preface -- Organization -- Contents -- DeReStainer: H&E to IHC Pathological Image Translation via Decoupled Staining Channels -- 1 Introduction -- 2 Methods -- 2.1 DeStainer -- 2.2 Feature Fusion Module -- 2.3 ReStainer -- 2.4 Loss Functions -- 3 Experiment -- 3.1 Dataset and Implementation Details -- 3.2 Results -- 3.3 Ablation Study -- 4 Conclusion -- References -- WDM: 3D Wavelet Diffusion Models for High-Resolution Medical Image Synthesis -- 1 Introduction -- 2 Background -- 3 Method -- 4 Experiments -- 4.1 Experimental Settings -- 4.2 Experimental Results -- 5 Conclusion

4 Experiments -- 4.1 Experimential Settings -- 4.2 Results and Discussion -- 5 Conclusion -- References -- SynthBrainGrow: Synthetic Diffusion Brain Aging for Longitudinal MRI Data Generation in Young People -- 1 Introduction -- 2 Method -- 3 Experiments and Results -- 3.1 Experimental Setup and Dataset -- 3.2 Quantitative Image Quality -- 3.3 Uncertainty Maps as an Explainability Surrogate -- 3.4 Limitations and Future Directions -- 4 Conclusion -- Appendix -- References -- Denoising Diffusion Models for 3D Healthy Brain Tissue Inpainting -- 1 Introduction -- 1.1 Related Work -- 1.2 Contribution

2 Methods -- 2.1 Denoising Diffusion Probabilistic Models -- 2.2 Modifying Diffusion Models for Inpainting -- 3 Experiments -- 4 Results -- 5 Discussion -- 6 Conclusion -- References -- Panoptic Segmentation of Mammograms with Text-to-Image Diffusion Model -- 1 Introduction -- 2 Materials and Methods -- 2.1 Segmentation Framework -- 2.2 Datasets -- 2.3 Implementation Details -- 2.4 Evaluation Metrics -- 3 Results -- 4 Discussion -- References -- Interactive Generation of Laparoscopic Videos with Diffusion Models -- 1 Introduction -- 2 Related Work -- 3 Video Generation Pipeline