Impact of patient size on image quality of OSEM3D and BSREM reconstructions in [68Ga]Ga-DOTA-TATE PET/MR

The image quality predictor body weight is a weaker predictor for BSREM than for OSEM3D image quality in [<sup>68</sup>Ga]Ga-DOTA-TATE PET/MR. Therefore, a linear dosage regimen based on body weight is preferable for BSREM, whereas a quadratic dosage regimen based on body weight is optimal for OSEM3D.

Authors

Institutions

Publication Details

Journal
EJNMMI Physics
Published
2025-07-01
DOI
https://doi.org/10.1186/s40658-025-00777-w
Primary Topic
Medical Imaging Techniques and Applications
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Impact of patient size on image quality of OSEM3D and BSREM reconstructions in [68Ga]Ga-DOTA-TATE PET/MR

Tessa Brabander, Frederik A. Verburg, Marcel Segbers, Christina P. W. Cox
EJNMMI Physics
Medical Imaging Techniques and Applications
article

Impact of patient size on image quality of OSEM3D and BSREM reconstructions in [68Ga]Ga-DOTA-TATE PET/MR

Tessa Brabander, Frederik A. Verburg, Marcel Segbers, Christina P. W. Cox
article en

Abstract

The image quality predictor body weight is a weaker predictor for BSREM than for OSEM3D image quality in [<sup>68</sup>Ga]Ga-DOTA-TATE PET/MR. Therefore, a linear dosage regimen based on body weight is preferable for BSREM, whereas a quadratic dosage regimen based on body weight is optimal for OSEM3D.

EJNMMI PhysicsVol. 12(1)
Erasmus MC (NL), Erasmus University Rotterdam (NL)
Openalex Percentile: Top 77%
Medical Imaging Techniques and Applications
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.