# Comparison of multi-organ CT image segmentation tools for whole-body [18F]FDG-PET/CT clinical imaging

## TL;DR

This study compares two automated tools for segmenting organs in CT scans and finds that while they perform well technically, they differ from manual methods in clinically important metrics.

## Contribution

The study introduces a comprehensive evaluation of multi-organ segmentation tools using both technical and clinical metrics.

## Key findings

- MOOSE and TotalSegmentator show comparable performance in technical segmentation metrics like DSC.
- Both tools produce significantly different organ volumes and SUVs compared to manual delineation for key organs.
- The study emphasizes the need for multi-pronged evaluation beyond traditional segmentation scores.

## Abstract

Automated multi-organ segmentation looks to assist clinicians and researchers working with Positron Emission Tomography/Computed Tomography (PET/CT) imaging in streamlining the time-consuming, operator-dependent task of manual delineation. This study aimed to compare two state-of-the-art automated multi-organ CT segmentation tools with typically perceived “gold-standard” manual delineation.

We compare Multiple-Organ Objective Segmentation (MOOSE) and TotalSegmentator against manual labels of six tissues on a dataset of 24 patients of lung cancer. We evaluated CT segmentation performance using the Dice–Sørensen Coefficient (DSC), Hausdorff Distance (HD), Average Symmetric Surface Distance (ASSD) and pixel-based metrics Precision and Recall. Alongside technical analysis, we perform evaluation using clinically relevant metrics including organ volume, mean standardised uptake value (SUVmean), maximum standardised uptake value (SUVmax), and Hounsfield units.

Both MOOSE and TotalSegmentator produce overall comparable DSC results. Conversely, MOOSE and TotalSegmentator segmentation results in significantly different volumes and SUVs compared with manual delineation for the lungs, brain, and kidneys.

Data presented here highlights the need to assess multi-organ segmentation tools performance using multi-pronged metrics beyond Dice-Sørensen scores.

The online version contains supplementary material available at 10.1007/s00259-025-07666-5.