Lumbar spine posterior corner detection in X-rays using Haar-based features
Communication avec acte
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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Quasi-automatic 3D reconstruction of the full spine from low-dose biplanar X-rays based on statistical inferences and image analysis Article dans une revue avec comité de lectureGAJNY, Laurent; EBRAHIMI, Shahin; VERGARI, Claudio; ANGELINI, Elsa; SKALLI, Wafa (Springer Verlag, 2018)Purpose: To design a quasi-automated three-dimensional reconstruction method of the spine from biplanar X-rays as the daily used method in clinical routine is based on manual adjustments of a trained operator and the ...
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Article dans une revue avec comité de lectureGIRINON, François; GAJNY, Laurent; EBRAHIMI, Shahin; DAGNEAUX, Louis; ROUCH, Philippe; SKALLI, Wafa (Taylor & Francis, 2020)3D reconstruction from low-dose Bi-Planar X-Rays (BPXR) is a rising practice in clinical routine. However, this process is time consuming and highly depends on the user. This study aims to partially automate the process ...