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Deep learning for accelerated and robust MRI reconstruction
Deep learning (DL) has recently emerged as a pivotal technology for enhancing magnetic
resonance imaging (MRI), a critical tool in diagnostic radiology. This review paper provides …
resonance imaging (MRI), a critical tool in diagnostic radiology. This review paper provides …
Deep learning for accelerated and robust MRI reconstruction: a review
Deep learning (DL) has recently emerged as a pivotal technology for enhancing magnetic
resonance imaging (MRI), a critical tool in diagnostic radiology. This review paper provides …
resonance imaging (MRI), a critical tool in diagnostic radiology. This review paper provides …
Bias in artificial intelligence for medical imaging: fundamentals, detection, avoidance, mitigation, challenges, ethics, and prospects
Although artificial intelligence (AI) methods hold promise for medical imaging-based
prediction tasks, their integration into medical practice may present a double-edged sword …
prediction tasks, their integration into medical practice may present a double-edged sword …
K-band: self-supervised MRI reconstruction via stochastic gradient descent over k-space subsets
Although deep learning (DL) methods are powerful for solving inverse problems, their
reliance on high-quality training data is a major hurdle. This is significant in high …
reliance on high-quality training data is a major hurdle. This is significant in high …
fastMRI Breast: A publicly available radial k-space dataset of breast dynamic contrast-enhanced MRI
The fastMRI breast dataset is the first large-scale dataset of radial k-space and Digital
Imaging and Communications in Medicine data for breast dynamic contrast-enhanced MRI …
Imaging and Communications in Medicine data for breast dynamic contrast-enhanced MRI …
Advancing medical imaging research through standardization: The path to rapid development, rigorous validation, and robust reproducibility
Artificial intelligence (AI) has made significant advances in radiology. Nonetheless,
challenges in AI development, validation, and reproducibility persist, primarily due to the …
challenges in AI development, validation, and reproducibility persist, primarily due to the …
Data resources: Milestones and building blocks
CE Kahn Jr - Radiology: Artificial Intelligence, 2023 - pubs.rsna.org
research in medical imaging AI through transparent and collaborative sharing of resources
such as software, data, methodology, and education. Open science presents an opportunity …
such as software, data, methodology, and education. Open science presents an opportunity …
The Multicentre Acute ischemic stroke imaGIng and Clinical data (MAGIC) repository: rationale and blueprint
Purpose The Multicentre Acute ischemic stroke imaGIng and Clinical data (MAGIC)
repository is a collaboration established in 2024 by seven stroke centres in Europe. MAGIC …
repository is a collaboration established in 2024 by seven stroke centres in Europe. MAGIC …
Artificial Intelligence in Gastrointestinal Imaging: Advances and Applications
JJR Chong, A Kirpalani, R Moreland… - Radiologic …, 2025 - radiologic.theclinics.com
The potential benefits of artificial intelligence (AI) in medical imaging include enhanced
diagnostic accuracy, increased interpretive efficiency, greater consistency among …
diagnostic accuracy, increased interpretive efficiency, greater consistency among …
Navigating the Future of Prostate Cancer Care: AI-Driven Imaging and Theranostics Through the Lens of RELAINCE
Centre of Excellence Preceptorship of 2024 held in Melbourne, Australia, a presentation on
artificial intelligence (AI) in prostate cancer imaging was delivered in which the …
artificial intelligence (AI) in prostate cancer imaging was delivered in which the …