Latest AI and machine learning research in nuclear medicine for healthcare professionals.
BACKGROUND: Low-dose (LD) myocardial perfusion (MP) SPECT suffers from high noise level, leading to ...
PURPOSE: Recently, deep learning-based methods have been established to denoise the low-count positr...
PURPOSE: To investigate whether the iodine density of liver parenchyma in the equilibrium phase and ...
PURPOSE: To develop an automated lung tumor segmentation method for radiation therapy planning based...
BACKGROUND: Studies have shown that the conventional parameters characterizing left ventricular mech...
Potential radioactive hazards in full-dose positron emission tomography (PET) imaging remain a conce...
Perception can influence individuals' behaviour and attitude affecting responses and compliance to p...
PURPOSE: Attenuation correction is a critically important step in data correction in positron emissi...
Though artificial intelligence (AI) has been used in nuclear medicine for more than 50 years, more p...
The segmentation of magnetic resonance (MR) images is a crucial task for creating pseudo computed to...
. Deep learning denoising networks are typically trained with images that are representative of the ...
In this work, a dedicated end-to-end deep convolutional neural network, named as Triple-CBCT, is pro...
PURPOSE: To compare the performances of machine learning (ML) and deep learning (DL) in improving th...
Positron Emission Tomography (PET) has become a preferred imaging modality for cancer diagnosis, rad...
OBJECTIVE: The exploration and the implementation of a deep learning method using a state-of-the-art...
PURPOSE: Positron Emission Tomography (PET) can support a diagnosis of neurodegenerative disorder by...
Clinical PET/CT examinations rely on CT modality for anatomical localization and attenuation correct...
: Cervical cancer is one of the two biggest killers of women and early detection of cervical precanc...
. Monolithic scintillator crystals coupled to silicon photomultiplier (SiPM) arrays are promising de...
PURPOSE: Deep-layer learning processing may improve contrast imaging with greater precision in low-c...
We investigate the use of 3D convolutional neural networks for gamma arrival time estimation in mono...