Titlebook: Deep Generative Models; 4th MICCAI Workshop, Anirban Mukhopadhyay,Ilkay Oksuz,Yixuan Yuan Conference proceedings 2025 The Editor(s) (if app

人充满活力

Ligneous

,Multi-parametric MRI to FMISO PET Synthesis for Hypoxia Prediction in Brain Tumors,ypoxia, a condition characterized by low oxygen levels, is a common feature of malignant brain tumors associated with poor prognosis. Fluoromisonidazole Positron Emission Tomography (FMISO PET) is a well-established method for detecting hypoxia in vivo, but it is expensive and not widely available..

Kinetic

,qMRI Diffuser: Quantitative T1 Mapping of the Brain Using a Denoising Diffusion Probabilistic Modelng-based methods have demonstrated effectiveness in estimating quantitative maps from series of weighted images. In this study, we present qMRI Diffuser, a novel approach to qMRI utilising deep generative models. Specifically, we implemented denoising diffusion probabilistic models (DDPM) for T1 qua

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epidermis

,Five Pitfalls When Assessing Synthetic Medical Images with Reference Metrics,compressed images, these metrics have shown very useful. Extensive tests of such metrics on benchmarks of artificially distorted natural images have revealed which metric best correlate with human perception of quality. Direct transfer of these metrics to the evaluation of generative models in medic

事物的方面

,Augmenting Prostate MRI Dataset with Synthetic Volumetric Images from Zone-Conditioned Diffusion Gecal imaging. However, collecting the necessary amount of data is often impractical due to patient privacy concerns or restricted time for medical annotation. Recent advances in generative models in medical imaging with a focus on diffusion-based techniques could provide realistic-looking synthetic s

母猪

,TiBiX: Leveraging Temporal Information for Bidirectional X-Ray and Report Generation,ort generation from Chest X-rays (CXR), and (2) synthetic scan generation from text or reports. Despite some research incorporating multi-view CXRs into the generative process, prior patient scans and reports have been generally disregarded. This can inadvertently lead to the leaving out of importan

avarice

破译

,Non-reference Quality Assessment for Medical Imaging: Application to Synthetic Brain MRIs,concerns. Existing image quality metrics often rely on reference images, are tailored for group comparisons, or are intended for 2D natural images, limiting their efficacy in complex domains like medical imaging. This study introduces a novel deep learning-based non-reference approach to assess brai

Minatory

Conference proceedings 2025GM4MICCAI 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