Report on the AAPM grand challenge on deep generative modeling for learning medical image statistics

R Deshpande, VA Kelkar, D Gotsis, P Kc… - Medical …, 2025‏ - Wiley Online Library
Background The findings of the 2023 AAPM Grand Challenge on Deep Generative
Modeling for Learning Medical Image Statistics are reported in this Special Report. Purpose …

[HTML][HTML] Evaluating synthetic neuroimaging data augmentation for automatic brain tumour segmentation with a deep fully-convolutional network

F Asadi, T Angsuwatanakul, JA O'Reilly - IBRO Neuroscience Reports, 2024‏ - Elsevier
Gliomas observed in medical images require expert neuro-radiologist evaluation for
treatment planning and monitoring, motivating development of intelligent systems capable of …

[HTML][HTML] Interpretation of latent codes in InfoGAN with SAR images

Z Feng, M Daković, H Ji, X Zhou, M Zhu, X Cui… - Remote Sensing, 2023‏ - mdpi.com
Generative adversarial networks (GANs) can synthesize abundant photo-realistic synthetic
aperture radar (SAR) images. Some modified GANs (eg, InfoGAN) are even able to edit …

Towards improved evaluation of generative neural networks: The Fréchet Coefficient

A Kucharski, A Fabijańska - Neurocomputing, 2025‏ - Elsevier
Generative adversarial networks (GANs) have shown remarkable capabilities for
synthesizing realistic images and movies. However, evaluating the performance of GANs …

Diffusion models for realistic CT image generation

MS Txurio, KLL Román, A Marcos-Carrión… - … KES Conference on …, 2023‏ - Springer
Generative networks, such as GANs, have been applied to the medical image domain,
where they have demonstrated their ability to synthesize realistic-looking images. However …

Tooth development prediction using a generative machine learning approach

K Kokomoto, R Okawa, K Nakano, K Nozaki - IEEE Access, 2024‏ - ieeexplore.ieee.org
This study pioneers the use of generative deep learning in pediatric dentistry to predict
dental growth using panoramic radiography, going beyond numerical analysis and …

Identifying Obviously Artificial Medical Images Produced by a Generative Adversarial Network

JA O'Reilly, F Asadi - … Conference of the IEEE Engineering in …, 2022‏ - ieeexplore.ieee.org
Synthetic medical images have an important role to play in develo** data-driven medical
image processing systems. Using a relatively small amount of patient data to train …

Cross-modality profiling of high-content microscopy images with deep learning

J Cross-Zamirski - 2023‏ - repository.cam.ac.uk
In this thesis we investigate the use of deep learning for cross-modality and multi-modal
image-based profiling applications. In particular, we explore the utility of the brightfield …

Generating Synthetic CT Images Using Diffusion Models

S Saleh - 2023‏ - diva-portal.org
Magnetic resonance (MR) images together with computed tomography (CT) images are
used in many medical practices, such as radiation therapy. To capture those images …