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 …

Inhibitory synapses dampen neuronal activity through postsynaptic hyperpolarization. The
composition of the inhibitory postsynapse and the mechanistic basis of its regulation, however…

Numerous methods to segment tumors using 18 F-fluorodeoxyglucose positron emission
tomography (FDG PET) have been introduced. Metabolic tumor volume (MTV) refers to the …

An important need exists for strategies to perform rigorous objective clinical-task-based
evaluation of artificial intelligence (AI) algorithms for nuclear medicine. To address this need, we …

The nuclear medicine field has seen a rapid expansion of academic and commercial interest
in developing artificial intelligence (AI) algorithms. Users and developers can avoid some …

Background To develop and evaluate the feasibility of a data-driven deep learning approach
(deepAC) for positron-emission tomography (PET) image attenuation correction without …

Artificial intelligence (AI) is being increasingly used to automate and improve technologies
within the field of medical imaging. A critical step in the development of an AI algorithm is …

Analysis of endogenous protein localization, function, and dynamics is fundamental to the
study of all cells, including the diversity of cell types in the brain. However, current approaches …

18 F-NaF, a PET radiotracer of bone turnover, has shown potential as an imaging biomarker
for assessing the response of bone metastases to therapy. This study aimed to evaluate the …

Purpose To automatically detect lymph nodes involved in lymphoma on fluorine 18 ( 18 F)
fluorodeoxyglucose (FDG) PET/CT images using convolutional neural networks (CNNs). …