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Lumbar spine posterior corner detection in X-rays using Haar-based features

Type
Communications avec actes
Author
EBRAHIMI, Shahin
ANGELINI, Elsa
300362 Télécom ParisTech
GAJNY, Laurent
466360 Institut de Biomecanique Humaine Georges Charpak
SKALLI, Wafa
466360 Institut de Biomecanique Humaine Georges Charpak
99538 Laboratoire de biomécanique [LBM]
164351 Institut de Mécanique et d'Ingénierie de Bordeaux [I2M]

URI
http://hdl.handle.net/10985/15787
DOI
10.1109/ISBI.2016.7493239
Date
2016

Abstract

3D reconstruction of the spine using biplanar X-rays remains approximate and requires human-machine interactions to adjust the position of important features such as vertebral corners and endplates. The purpose of this study is to develop a method to extract automatically the accurate position of lumbar vertebrae posterior corners. In the proposed method we select corner point candidates from an initial edge map. A dedicated pipeline is designed to discard unwanted candidates, involving polyline simplification, curvature thresholding and multiscale Haar filtering. Ultimately, we use a priori knowledge derived from an initial 3D spine model to define search areas and select the final corner points. The framework was tested on 21 biplanar X-rays from scoliotic children. Corner positions are compared with manual selections by two experts. The results report a localization accuracy between 0.7 and 1.6 mm, comparable to manual expert variability.

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