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Authors: Marco Carletti 1 ; Diego Dall'Alba 1 ; Marco Cristani 2 and Paolo Fiorini 1

Affiliations: 1 University of Verona, Italy ; 2 University of Verona and Consiglio Nazionale delle Ricerche (CNR), Italy

ISBN: 978-989-758-175-5

Keyword(s): Medical Image Applications, Ultrasound Tracking, Particle Filtering, Template Selection, Motion Flow.

Related Ontology Subjects/Areas/Topics: Applications and Services ; Computer Vision, Visualization and Computer Graphics ; Medical Image Applications ; Motion, Tracking and Stereo Vision ; Tracking and Visual Navigation

Abstract: Tracking moving organs captured by ultrasound imaging techniques is of fundamental importance in many applications, from image-guided radiotherapy to minimally invasive surgery. Due to operative constraints, tracking has to be carried out on-line, facing classic computer vision problems that are still unsolved in the community. One of them is the update of the template, which is necessary to avoid drifting phenomena in the case of template-based tracking. In this paper, we offer an innovative and robust solution to this problem, exploiting a simple yet important aspect which often holds in biomedical scenarios: in many cases, the target (a blood vessel, cyst or localized lesion) exists in a semi-static operative field, where the unique motion is due to organs that are subjected to quasi-periodic movements. This leads the target to occupy certain areas of the scene at some times, exhibiting particular visual layouts. Our solution exploits this scenario, and consists into a template-bas ed particle filtering strategy equipped with a spatially-localized vocabulary, which in practice suggests the tracker the most suitable template to be used among a set of available ones, depending on the proposal distribution. Experiments have been performed on the MICCAI CLUST 2015 benchmark, reaching an accuracy (i.e. mean tracking error) of 1.11 mm and a precision of 1.53 mm. These results widely satisfy the clinical requirements imposed by image guided surgical procedure and show fostering future developments. (More)

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Paper citation in several formats:
Carletti, M.; Carletti, M.; Dall'Alba, D.; Cristani, M. and Fiorini, P. (2016). A Robust Particle Filtering Approach with Spatially-dependent Template Selection for Medical Ultrasound Tracking Applications.In Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2016) ISBN 978-989-758-175-5, pages 522-531. DOI: 10.5220/0005725505220531

@conference{visapp16,
author={Marco Carletti. and Marco Carletti. and Diego Dall'Alba. and Marco Cristani. and Paolo Fiorini.},
title={A Robust Particle Filtering Approach with Spatially-dependent Template Selection for Medical Ultrasound Tracking Applications},
booktitle={Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2016)},
year={2016},
pages={522-531},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005725505220531},
isbn={978-989-758-175-5},
}

TY - CONF

JO - Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2016)
TI - A Robust Particle Filtering Approach with Spatially-dependent Template Selection for Medical Ultrasound Tracking Applications
SN - 978-989-758-175-5
AU - Carletti, M.
AU - Carletti, M.
AU - Dall'Alba, D.
AU - Cristani, M.
AU - Fiorini, P.
PY - 2016
SP - 522
EP - 531
DO - 10.5220/0005725505220531

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