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

Artificial intelligence and machine learning based approaches are increasingly finding their
way into various areas of nuclear medicine imaging. With the technical development of new …

The present procedural guidelines summarize the current views of the EANM Neuro-
Imaging Committee (NIC). The purpose of these guidelines is to assist nuclear medicine …

Recently, the application of artificial intelligence (AI) in medical imaging (including nuclear
medicine imaging) has rapidly developed. Most AI applications in nuclear medicine imaging …

Despite being thirteen years since the installation of the first PET-MR system, the scanners
constitute a very small proportion of the total hybrid PET systems installed. This is in stark …

The segmentation of MR (magnetic resonance) images is a simple approach to create
Pseudo CT images which are useful for many medical imaging analysis applications. One of …

Among the most critical health issues, brain illnesses, such as neurodegenerative conditions
and tumors, lower quality of life and have a significant economic impact. Implantable …

Positron emission tomography (PET) and magnetic resonance imaging (MRI) are advanced
clinical imaging modalities that in combination can provide structural, morphologic …

Precise segmentation of the hippocampus is essential for various human brain activity and
neurological disorder studies. To overcome the small size of the hippocampus and the low …

The recent emergence of imaging mass cytometry technology has led to the generation of
an increasing amount of high-dimensional data and, with it, the need for suitable performant …