Transforming medical imaging with Transformers? A comparative review of key properties, current progresses, and future perspectives
Transformer, one of the latest technological advances of deep learning, has gained
prevalence in natural language processing or computer vision. Since medical imaging bear …
prevalence in natural language processing or computer vision. Since medical imaging bear …
Deep learning for PET image reconstruction
This article reviews the use of a subdiscipline of artificial intelligence (AI), deep learning, for
the reconstruction of images in positron emission tomography (PET). Deep learning can be …
the reconstruction of images in positron emission tomography (PET). Deep learning can be …
Image reconstruction is a new frontier of machine learning
Over past several years, machine learning, or more generally artificial intelligence, has
generated overwhelming research interest and attracted unprecedented public attention. As …
generated overwhelming research interest and attracted unprecedented public attention. As …
Content-noise complementary learning for medical image denoising
Medical imaging denoising faces great challenges, yet is in great demand. With its
distinctive characteristics, medical imaging denoising in the image domain requires …
distinctive characteristics, medical imaging denoising in the image domain requires …
Using deep learning techniques in medical imaging: a systematic review of applications on CT and PET
I Domingues, G Pereira, P Martins, H Duarte… - Artificial Intelligence …, 2020 - Springer
Medical imaging is a rich source of invaluable information necessary for clinical judgements.
However, the analysis of those exams is not a trivial assignment. In recent times, the use of …
However, the analysis of those exams is not a trivial assignment. In recent times, the use of …
Adaptive rectification based adversarial network with spectrum constraint for high-quality PET image synthesis
Positron emission tomography (PET) is a typical nuclear imaging technique, which can
provide crucial functional information for early brain disease diagnosis. Generally, clinically …
provide crucial functional information for early brain disease diagnosis. Generally, clinically …
A survey on deep learning in medical image reconstruction
E Ahishakiye, M Bastiaan Van Gijzen… - Intelligent …, 2021 - mednexus.org
Medical image reconstruction aims to acquire high-quality medical images for clinical usage
at minimal cost and risk to the patients. Deep learning and its applications in medical …
at minimal cost and risk to the patients. Deep learning and its applications in medical …
Artificial intelligence, machine (deep) learning and radio (geno) mics: definitions and nuclear medicine imaging applications
D Visvikis, C Cheze Le Rest, V Jaouen… - European journal of …, 2019 - Springer
Techniques from the field of artificial intelligence, and more specifically machine (deep)
learning methods, have been core components of most recent developments in the field of …
learning methods, have been core components of most recent developments in the field of …
Artificial intelligence in nuclear medicine
F Nensa, A Demircioglu… - Journal of Nuclear …, 2019 - Soc Nuclear Med
Despite the great media attention for artificial intelligence (AI), for many health care
professionals the term and the functioning of AI remain a “black box,” leading to exaggerated …
professionals the term and the functioning of AI remain a “black box,” leading to exaggerated …
Deep learning‐based image reconstruction for different medical imaging modalities
Image reconstruction in magnetic resonance imaging (MRI) and computed tomography (CT)
is a mathematical process that generates images at many different angles around the …
is a mathematical process that generates images at many different angles around the …