[HTML][HTML] Deep learning based synthesis of MRI, CT and PET: Review and analysis
Medical image synthesis represents a critical area of research in clinical decision-making,
aiming to overcome the challenges associated with acquiring multiple image modalities for …
aiming to overcome the challenges associated with acquiring multiple image modalities for …
Deep learning for tomographic image reconstruction
Deep-learning-based tomographic imaging is an important application of artificial
intelligence and a new frontier of machine learning. Deep learning has been widely used in …
intelligence and a new frontier of machine learning. Deep learning has been widely used in …
A review of deep learning in medical imaging: Imaging traits, technology trends, case studies with progress highlights, and future promises
Since its renaissance, deep learning has been widely used in various medical imaging tasks
and has achieved remarkable success in many medical imaging applications, thereby …
and has achieved remarkable success in many medical imaging applications, thereby …
A review on medical imaging synthesis using deep learning and its clinical applications
This paper reviewed the deep learning‐based studies for medical imaging synthesis and its
clinical application. Specifically, we summarized the recent developments of deep learning …
clinical application. Specifically, we summarized the recent developments of deep learning …
[HTML][HTML] The promise of artificial intelligence and deep learning in PET and SPECT imaging
This review sets out to discuss the foremost applications of artificial intelligence (AI),
particularly deep learning (DL) algorithms, in single-photon emission computed tomography …
particularly deep learning (DL) algorithms, in single-photon emission computed tomography …
State of the art in total body PET
The idea of a very sensitive positron emission tomography (PET) system covering a large
portion of the body of a patient already dates back to the early 1990s. In the period 2000 …
portion of the body of a patient already dates back to the early 1990s. In the period 2000 …
Deep learning for Alzheimer's disease diagnosis: A survey
Alzheimer's Disease (AD) is an irreversible neurodegenerative disease that results in a
progressive decline in cognitive abilities. Since AD starts several years before the onset of …
progressive decline in cognitive abilities. Since AD starts several years before the onset of …
A roadmap for foundational research on artificial intelligence in medical imaging: from the 2018 NIH/RSNA/ACR/The Academy Workshop
Imaging research laboratories are rapidly creating machine learning systems that achieve
expert human performance using open-source methods and tools. These artificial …
expert human performance using open-source methods and tools. These artificial …
PET image denoising using unsupervised deep learning
Purpose Image quality of positron emission tomography (PET) is limited by various physical
degradation factors. Our study aims to perform PET image denoising by utilizing prior …
degradation factors. Our study aims to perform PET image denoising by utilizing prior …
Supervised learning with cyclegan for low-dose FDG PET image denoising
PET imaging involves radiotracer injections, raising concerns about the risk of radiation
exposure. To minimize the potential risk, one way is to reduce the injected tracer. However …
exposure. To minimize the potential risk, one way is to reduce the injected tracer. However …