Positron emission tomography: current challenges and opportunities for technological advances in clinical and preclinical imaging systems
JJ Vaquero, P Kinahan - Annual review of biomedical …, 2015 - annualreviews.org
Positron emission tomography (PET) imaging is based on detecting two time-coincident high-
energy photons from the emission of a positron-emitting radioisotope. The physics of the …
energy photons from the emission of a positron-emitting radioisotope. The physics of the …
MRI-only treatment planning: benefits and challenges
AM Owrangi, PB Greer… - Physics in Medicine & …, 2018 - iopscience.iop.org
Over the past decade, the application of magnetic resonance imaging (MRI) has increased,
and there is growing evidence to suggest that improvements in the accuracy of target …
and there is growing evidence to suggest that improvements in the accuracy of target …
ResViT: residual vision transformers for multimodal medical image synthesis
Generative adversarial models with convolutional neural network (CNN) backbones have
recently been established as state-of-the-art in numerous medical image synthesis tasks …
recently been established as state-of-the-art in numerous medical image synthesis tasks …
Medical image synthesis with deep convolutional adversarial networks
Medical imaging plays a critical role in various clinical applications. However, due to
multiple considerations such as cost and radiation dose, the acquisition of certain image …
multiple considerations such as cost and radiation dose, the acquisition of certain image …
MR‐based synthetic CT generation using a deep convolutional neural network method
X Han - Medical physics, 2017 - Wiley Online Library
Purpose Interests have been rapidly growing in the field of radiotherapy to replace CT with
magnetic resonance imaging (MRI), due to superior soft tissue contrast offered by MRI and …
magnetic resonance imaging (MRI), due to superior soft tissue contrast offered by MRI and …
Medical image synthesis with context-aware generative adversarial networks
Computed tomography (CT) is critical for various clinical applications, eg, radiation treatment
planning and also PET attenuation correction in MRI/PET scanner. However, CT exposes …
planning and also PET attenuation correction in MRI/PET scanner. However, CT exposes …
Deep learning MR imaging–based attenuation correction for PET/MR imaging
Purpose To develop and evaluate the feasibility of deep learning approaches for magnetic
resonance (MR) imaging–based attenuation correction (AC)(termed deep MRAC) in brain …
resonance (MR) imaging–based attenuation correction (AC)(termed deep MRAC) in brain …
Bidirectional mapping generative adversarial networks for brain MR to PET synthesis
Fusing multi-modality medical images, such as magnetic resonance (MR) imaging and
positron emission tomography (PET), can provide various anatomical and functional …
positron emission tomography (PET), can provide various anatomical and functional …
Estimating CT image from MRI data using 3D fully convolutional networks
Computed tomography (CT) is critical for various clinical applications, eg, radiotherapy
treatment planning and also PET attenuation correction. However, CT exposes radiation …
treatment planning and also PET attenuation correction. However, CT exposes radiation …
Deep learning-based attenuation correction in the absence of structural information for whole-body positron emission tomography imaging
Deriving accurate structural maps for attenuation correction (AC) of whole-body positron
emission tomography (PET) remains challenging. Common problems include truncation …
emission tomography (PET) remains challenging. Common problems include truncation …