Using Geometric Graph Matching in Image Registration

Giomar Olivera, Aura Conci, Leandro Fernandes

Abstract

Image registration is a fundamental task in many medical applications, allowing interpreting and analyzing images acquired using different technologies, from different viewpoints, or at different times. The image registration task is particularly challenging when the images have little high-frequency information and when average brightness changes over time, as is the case with infrared breast exams acquired using a dynamic protocol. This paper presents a new method for registering these images, where each one is represented in a compact form by a geometric graph, and the registration is done by comparing graphs. The application of the proposed technique consists of five stages: (i) pre-process the infrared breast image; (ii) extract the internal linear structures that characterize arteries, vascular structures, and other hot regions; (iii) create a geometric graph to represent such structures; (iv) perform structure registration by comparing graphs; and (v) estimate the transformation function. The Dice coefficient, Jaccard index, and total overlap agreement measure are considered to evaluate the results’ quality. The output obtained on a public database of infrared breast images is compared against SURF interest points for image registration and a state of the art approach for infrared breast image registration from the literature. The analyzes show that the proposed method outperforms others.

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Paper Citation


in Harvard Style

Olivera G., Conci A. and Fernandes L. (2021). Using Geometric Graph Matching in Image Registration.In Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP, ISBN 978-989-758-488-6, pages 87-98. DOI: 10.5220/0010239200870098


in Bibtex Style

@conference{visapp21,
author={Giomar Olivera and Aura Conci and Leandro Fernandes},
title={Using Geometric Graph Matching in Image Registration},
booktitle={Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP,},
year={2021},
pages={87-98},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010239200870098},
isbn={978-989-758-488-6},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP,
TI - Using Geometric Graph Matching in Image Registration
SN - 978-989-758-488-6
AU - Olivera G.
AU - Conci A.
AU - Fernandes L.
PY - 2021
SP - 87
EP - 98
DO - 10.5220/0010239200870098