loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

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.

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 18.118.154.237

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

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

- Science and Technology Publications, Lda.
RESOURCES

Proceedings

Papers

Authors

Ontology

CONTACTS

Science and Technology Publications, Lda
Avenida de S. Francisco Xavier, Lote 7 Cv. C,
2900-616 Setúbal, Portugal.

Phone: +351 265 520 185 (National fixed network call)
Fax: +351 265 520 186
Email: info@scitepress.org

EXTERNAL LINKS

PRIMORIS

INSTICC

SCITEVENTS

CROSSREF

PROCEEDINGS SUBMITTED FOR INDEXATION BY:

dblp

Ei Compendex

SCOPUS

Semantic Scholar

Google Scholar

Microsoft Academic