Vertebral morphometry is a common clinically-used method for vertebral fracture detection and classification, based on height measurements of vertebral bodies in radiographic images. This method is quantitative and does not require specific operator skills, but its actual accuracy is affected by errors made during the timeconsuming manual or semi-automatic measurements. In this paper, we propose an innovative fully automatic approach to vertebral morphometry. A novel algorithm, based on a local phase symmetry measure and an "Active Shape Model", was implemented and tested on lateral X-ray radiographs of 50 patients. Thoracic and lumbar vertebral bodies in each image were independently segmented and measured by both the automatic algorithm and an experienced radiologist, whose manually-obtained results were assumed as the ground truth. The algorithm showed reasonably low error rates regarding both vertebral localization and morphometric measurements with a sensitivity of 86.5% and a perfect specificity of 100%, because no false positive were present. Furthermore, its performance did not appreciably worsen on poor quality images, emphasizing a significant potential for a prompt translation into clinical routine.
A novel fully automatic algorithm for accurate vertebral morphometry
F Conversano;E Casciaro;S Casciaro
2014
Abstract
Vertebral morphometry is a common clinically-used method for vertebral fracture detection and classification, based on height measurements of vertebral bodies in radiographic images. This method is quantitative and does not require specific operator skills, but its actual accuracy is affected by errors made during the timeconsuming manual or semi-automatic measurements. In this paper, we propose an innovative fully automatic approach to vertebral morphometry. A novel algorithm, based on a local phase symmetry measure and an "Active Shape Model", was implemented and tested on lateral X-ray radiographs of 50 patients. Thoracic and lumbar vertebral bodies in each image were independently segmented and measured by both the automatic algorithm and an experienced radiologist, whose manually-obtained results were assumed as the ground truth. The algorithm showed reasonably low error rates regarding both vertebral localization and morphometric measurements with a sensitivity of 86.5% and a perfect specificity of 100%, because no false positive were present. Furthermore, its performance did not appreciably worsen on poor quality images, emphasizing a significant potential for a prompt translation into clinical routine.File | Dimensione | Formato | |
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