Vertebral fracture classification

Marleen De Bruijne*, Paola C. Pettersen, László B. Tankó, Mads Nielsen

*Corresponding author for this work

Research output: Chapter/Conference proceedingConference proceedingAcademicpeer-review

6 Citations (Scopus)

Abstract

A novel method for classification and quantification of vertebral fractures from X-ray images is presented. Using pairwise conditional shape models trained on a set of healthy spines, the most likely unfractured shape is estimated for each of the vertebrae in the image. The difference between the true shape and the reconstructed normal shape is an indicator for the shape abnormality. A statistical classification scheme with the two shapes as features is applied to detect, classify, and grade various types of deformities. In contrast with the current (semi-)quantitative grading strategies this method takes the full shape into account, it uses a patient-specific reference by combining population-based information on biological variation in vertebra shape and vertebra interrelations, and it provides a continuous measure of deformity. Good agreement with manual classification and grading is demonstrated on 204 lateral spine radiographs with in total 89 fractures.

Original languageEnglish
Title of host publicationMedical Imaging 2007
Subtitle of host publicationImage Processing
EditionPART 1
DOIs
Publication statusPublished - 2007
Externally publishedYes
EventMedical Imaging 2007: Image Processing - San Diego, CA, United States
Duration: 18 Feb 200720 Feb 2007

Publication series

SeriesProgress in Biomedical Optics and Imaging - Proceedings of SPIE
NumberPART 1
Volume6512
ISSN1605-7422

Conference

ConferenceMedical Imaging 2007: Image Processing
Country/TerritoryUnited States
CitySan Diego, CA
Period18/02/0720/02/07

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