AI-Based Noise-Reduction Filter for Whole-Body Planar Bone Scintigraphy Reliably Improves Low-Count Images.

: Artificial intelligence (AI) is a promising tool for the enhancement of physician workflow and serves to further improve the efficiency of their diagnostic evaluations. This study aimed to assess the performance of an AI-based bone scan noise-reduction filter on noisy, low-count images in a routine clinical environment. : The performance of the AI bone-scan filter (BS-AI filter) in question was retrospectively evaluated on 47 different patients' Tc-MDP bone scintigraphy image pairs (anterior- and posterior-view images), which were obtained in such a manner as to represent the diverse characteristics of the general patient population.

Q-Bot: automatic DICOM metadata monitoring for the next level of quality management in nuclear medicine.

Background: Regular and precise inspection of the realization of the local nuclear medicine standard operation procedures (SOPs) is very complex and time-consuming, especially when large amount of patient data is obtained from a wide scale of different scan procedures on a daily basis. DICOM metadata comprise a complete set of data related to the patient and the imaging procedure, and consequently all information necessary to evaluate the compliance with the actual SOP.

Methods: Q-Bot, an automatic DICOM metadata monitoring tool which is capable to verify SOP conformities, was tested for 11 months at two nuclear medicine departments.