Fully automated computational measurement of noise in positron emission tomography

ConclusionAn algorithm provides an accurate and meaningful estimation of the global noise level encountered in clinical PET imaging datasets.Clinical relevance statementAn automated computational approach that measures the global noise level of PET imaging datasets may facilitate quality standardization and benchmarking of clinical PET imaging within and across institutions.Key Points•Noise is an important quantitative marker that strongly impacts image quality of PET images.•An automated computational noise measurement algorithm provides an accurate and meaningful estimation of the global noise level encountered in clinical PET imaging datasets.•An automated computational approach that measures the global noise level of PET imaging datasets may facilitate quality standardization and benchmarking as well as protocol harmonization.
Source: European Radiology - Category: Radiology Source Type: research