Improving Vertebra Segmentation through Joint Vertebra-Rib Atlases

TL;DR

This paper introduces a joint vertebra-rib atlas approach to improve the accuracy of vertebra segmentation in CT images, reducing errors caused by leakage into ribs and enhancing segmentation metrics.

Contribution

The study presents a novel joint vertebra-rib atlas method that significantly improves vertebra segmentation accuracy over traditional methods.

Findings

Increased Dice coefficient from 92.5% to 93.8%.

Reduced surface distance errors from 0.75mm to 0.30mm.

Statistically significant improvements in segmentation accuracy.

Abstract

Accurate spine segmentation allows for improved identification and quantitative characterization of abnormalities of the vertebra, such as vertebral fractures. However, in existing automated vertebra segmentation methods on computed tomography (CT) images, leakage into nearby bones such as ribs occurs due to the close proximity of these visibly intense structures in a 3D CT volume. To reduce this error, we propose the use of joint vertebra-rib atlases to improve the segmentation of vertebrae via multi-atlas joint label fusion. Segmentation was performed and evaluated on CTs containing 106 thoracic and lumbar vertebrae from 10 pathological and traumatic spine patients on an individual vertebra level basis. Vertebra atlases produced errors where the segmentation leaked into the ribs. The use of joint vertebra-rib atlases produced a statistically significant increase in the Dice coefficient from 92.5 $\pm$ 3.1% to 93.8 $\pm$ 2.1% for the left and right transverse processes and a decrease in the mean and max surface distance from 0.75 $\pm$ 0.60mm and 8.63 $\pm$ 4.44mm to 0.30 $\pm$ 0.27mm and 3.65 $\pm$ 2.87mm, respectively.