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Authors: Rémy Vandaele ; François Lallemand ; Philippe Martinive ; Akos Gulyban ; Sébastien Jodogne ; Philippe Coucke ; Pierre Geurts and Raphaël Marée

Affiliation: University of Liège, Belgium

Keyword(s): Registration, Machine Learning, Oncology Applications, Radiation Therapy, Urology and Pelvic Organs, Computed Tomography.

Related Ontology Subjects/Areas/Topics: Applications and Services ; Computer Vision, Visualization and Computer Graphics ; Image and Video Analysis ; Image Registration ; Medical Image Applications ; Shape Representation and Matching

Abstract: We propose a new method for automatic 3D multimodal registration based on anatomical landmark detection. Landmark detectors are learned independantly in the two imaging modalities using Extremely Randomized Trees and multi-resolution voxel windows. A least-squares fitting algorithm is then used for rigid registration based on the landmark positions as predicted by these detectors in the two imaging modalities. Experiments are carried out with this method on a dataset of pelvis CT and CBCT scans related to 45 patients. On this dataset, our fully automatic approach yields results very competitive with respect to a manually assisted state-of-the-art rigid registration algorithm.

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Paper citation in several formats:
Vandaele, R. ; Lallemand, F. ; Martinive, P. ; Gulyban, A. ; Jodogne, S. ; Coucke, P. ; Geurts, P. and Marée, R. (2017). Automated Multimodal Volume Registration based on Supervised 3D Anatomical Landmark Detection. In Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2017) - Volume 5: VISAPP; ISBN 978-989-758-226-4; ISSN 2184-4321, SciTePress, pages 333-340. DOI: 10.5220/0006153803330340

@conference{visapp17,
author={Rémy Vandaele and Fran\c{c}ois Lallemand and Philippe Martinive and Akos Gulyban and Sébastien Jodogne and Philippe Coucke and Pierre Geurts and Raphaël Marée},
title={Automated Multimodal Volume Registration based on Supervised 3D Anatomical Landmark Detection},
booktitle={Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2017) - Volume 5: VISAPP},
year={2017},
pages={333-340},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006153803330340},
isbn={978-989-758-226-4},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2017) - Volume 5: VISAPP
TI - Automated Multimodal Volume Registration based on Supervised 3D Anatomical Landmark Detection
SN - 978-989-758-226-4
IS - 2184-4321
AU - Vandaele, R.
AU - Lallemand, F.
AU - Martinive, P.
AU - Gulyban, A.
AU - Jodogne, S.
AU - Coucke, P.
AU - Geurts, P.
AU - Marée, R.
PY - 2017
SP - 333
EP - 340
DO - 10.5220/0006153803330340
PB - SciTePress

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