Comparison of Automatic Segmentation and Preprocessing Approaches for Dynamic Total-Body 3D Pet Images with Different Pet Tracers.

ABSTRACT: Segmentation is a routine step in PET image analysis, and few automatic tools have been developed for it. However, excluding supervised methods with their own limitations, they are typically designed for older, small images and the implementations are no longer publicly available. Here, we test if different commonly used building blocks of the automatic methods work with large modern total-body PET images. Dynamic total-body images from five different datasets are used for evaluation purposes, and the tested algorithms cover wide range of different preprocessing approaches and unsupervised segmentation methods. The validation is done by comparing the obtained segments to manually drawn ones using Jaccard index, Dice score, precision, and recall as measures of match. Out of the 17 considere

SUBMITTER: Jaakkola MK 

PROVIDER: S-EPMC12920958 | biostudies-literature | 2026 Feb

REPOSITORIES: biostudies-literature