The use of deep learning in medical imaging has increased rapidly over the past few years,
finding applications throughout the entire radiology pipeline, from improved scanner …

Segmentation of the Left ventricle (LV) is a crucial step for quantitative measurements such
as area, volume, and ejection fraction. However, the automatic LV segmentation in 2D …

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

Introduction The purpose of this work was to assess the feasibility of acquisition time
reduction in MPI-SPECT imaging using deep leering techniques through two main …

Lowering the dose in single-photon emission computed tomography (SPECT) imaging to
reduce the radiation damage to patients has become very significant. In SPECT imaging …

PET scanners with partial-ring geometry have been proposed for various imaging purposes.
The incomplete projection data obtained from this design cause undesirable artifacts in the …

Nowadays PET imaging is routinely coupled with anatomical imaging in the form of PET/CT
and PET/MRI. CT or MR images are commonly used to correct for attenuation and scatter …

In order to generate high-quality single-photon emission computed tomography (SPECT)
images under low-dose acquisition mode, a sinogram denoising method was studied for …

Accurate delineation of the gross tumor volume (GTV) is critical for treatment planning in
radiation oncology. This task is very challenging owing to the irregular and diverse shapes …

Purpose This review aims to investigate the available evidence of PET image reconstruction
using conventional and AI-based approaches. Materials and methods The electronic …