The role of generative adversarial networks in brain MRI: a scoping review
The performance of artificial intelligence (AI) for brain MRI can improve if enough data are
made available. Generative adversarial networks (GANs) showed a lot of potential to …
made available. Generative adversarial networks (GANs) showed a lot of potential to …
[HTML][HTML] Data synthesis and adversarial networks: A review and meta-analysis in cancer imaging
Despite technological and medical advances, the detection, interpretation, and treatment of
cancer based on imaging data continue to pose significant challenges. These include inter …
cancer based on imaging data continue to pose significant challenges. These include inter …
Lesion segmentation in lung CT scans using unsupervised adversarial learning
Lesion segmentation in medical images is difficult yet crucial for proper diagnosis and
treatment. Identifying lesions in medical images is costly and time-consuming and requires …
treatment. Identifying lesions in medical images is costly and time-consuming and requires …
[PDF][PDF] A review of generative adversarial networks in cancer imaging: New applications, new solutions
Despite technological and medical advances, the detection, interpretation, and treatment of
cancer based on imaging data continue to pose significant challenges. These include high …
cancer based on imaging data continue to pose significant challenges. These include high …
ResNet-based image inpainting method for enhancing the imaging speed of single molecule localization microscopy
Single molecule localization microscopy (SMLM) is a mainstream method in the field of
super-resolution fluorescence microscopy that can achieve a spatial resolution of 20∼ 30 …
super-resolution fluorescence microscopy that can achieve a spatial resolution of 20∼ 30 …
[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 …
treatment planning and monitoring, motivating development of intelligent systems capable of …
Deep learning using a residual deconvolutional network enables real-time high-density single-molecule localization microscopy
High-density localization based on deep learning is a very effective method to accelerate
single molecule localization microscopy (SMLM). Compared with traditional high-density …
single molecule localization microscopy (SMLM). Compared with traditional high-density …
2D/3D-MGR: A 2D/3D Medical Image Registration Framework Based on DRR
Z Li, X Ji, C Wang, W Liu, F Zhu, J Zhai - IEEE Access, 2024 - ieeexplore.ieee.org
Medical image registration is a crucial process in medical image analysis. However,
traditional 2D and 3D medical image registration methods often struggle to accommodate …
traditional 2D and 3D medical image registration methods often struggle to accommodate …
Artificial Intelligence in Health Services Management
H Arslan, F Kucuk - The Impact of Artificial Intelligence on Healthcare … - taylorfrancis.com
Various types of diseases and epidemics have been emerging day by day and there have
been great demand on using health information technologies in disease prediction and …
been great demand on using health information technologies in disease prediction and …
[PDF][PDF] Deep Generative Models in Brain MRI Synthesis for Alzheimer's Disease Research
R Zhao - lup.lub.lu.se
Alzheimer's Disease (AD) is a prevalent neurodegenerative disorder characterized by
progressive cognitive decline. Early and precise diagnosis is crucial for effective prophylaxis …
progressive cognitive decline. Early and precise diagnosis is crucial for effective prophylaxis …