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Report on the AAPM grand challenge on deep generative modeling for learning medical image statistics
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 …
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
Gliomas observed in medical images require expert neuro-radiologist evaluation for
treatment planning and monitoring, motivating development of intelligent systems capable of …
treatment planning and monitoring, motivating development of intelligent systems capable of …
[HTML][HTML] Interpretation of latent codes in InfoGAN with SAR images
Generative adversarial networks (GANs) can synthesize abundant photo-realistic synthetic
aperture radar (SAR) images. Some modified GANs (eg, InfoGAN) are even able to edit …
aperture radar (SAR) images. Some modified GANs (eg, InfoGAN) are even able to edit …
Towards improved evaluation of generative neural networks: The Fréchet Coefficient
Generative adversarial networks (GANs) have shown remarkable capabilities for
synthesizing realistic images and movies. However, evaluating the performance of GANs …
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 …
where they have demonstrated their ability to synthesize realistic-looking images. However …
Tooth development prediction using a generative machine learning approach
This study pioneers the use of generative deep learning in pediatric dentistry to predict
dental growth using panoramic radiography, going beyond numerical analysis and …
dental growth using panoramic radiography, going beyond numerical analysis and …
Identifying Obviously Artificial Medical Images Produced by a Generative Adversarial Network
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 …
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 …
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 …
used in many medical practices, such as radiation therapy. To capture those images …