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 …

This review sets out to discuss the foremost applications of artificial intelligence (AI),
particularly deep learning (DL) algorithms, in single-photon emission computed tomography …

A tumor is carried on by rapid and uncontrolled cell growth in the brain. If it is not treated in
the initial phases, it could prove fatal. Despite numerous significant efforts and encouraging …

Abstract Recently, deep learning (DL)‐based methods for the generation of synthetic
computed tomography (sCT) have received significant research attention as an alternative to …

Deep Learning (DL) algorithms enabled computational models consist of multiple
processing layers that represent data with multiple levels of abstraction. In recent years …

The rapid expansion of machine learning is offering a new wave of opportunities for nuclear
medicine. This paper reviews applications of machine learning for the study of attenuation …

Attenuation correction (AC) is essential for the generation of artifact-free and quantitatively
accurate positron emission tomography (PET) images. PET AC based on computed …

Machine learning has found unique applications in nuclear medicine from photon detection
to quantitative image reconstruction. Although there have been impressive strides in …

Objective Artificial intelligence (AI) has facilitated the analysis of medical imaging given
increased computational capacity and medical data availability in recent years. Although …

Abstract Introduction Artificial Intelligence-based Medical Devices (AI-based MDs) are
experiencing exponential growth in healthcare. This study aimed to investigate whether …