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Deformable registration of 3D ultrasound volumes using automatic landmark generation

US image registration is an important task e.g. in Computer Aided Surgery. Due to tissue deformation occurring between pre-operative and interventional images often deformable registration is necessary. We present a registration method focused on surface structures (i.e. saliencies) of soft tissues...

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Autores principales: Figl, Michael, Hoffmann, Rainer, Kaar, Marcus, Hummel, Johann
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6420033/
https://www.ncbi.nlm.nih.gov/pubmed/30875379
http://dx.doi.org/10.1371/journal.pone.0213004
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author Figl, Michael
Hoffmann, Rainer
Kaar, Marcus
Hummel, Johann
author_facet Figl, Michael
Hoffmann, Rainer
Kaar, Marcus
Hummel, Johann
author_sort Figl, Michael
collection PubMed
description US image registration is an important task e.g. in Computer Aided Surgery. Due to tissue deformation occurring between pre-operative and interventional images often deformable registration is necessary. We present a registration method focused on surface structures (i.e. saliencies) of soft tissues like organ capsules or vessels. The main concept follows the idea of representative landmarks (so called leading points). These landmarks represent saliencies in each image in a certain region of interest. The determination of deformation was based on a geometric model assuming that saliencies could locally be described by planes. These planes were calculated from the landmarks using two dimensional linear regression. Once corresponding regions in both images were found, a displacement vector field representing the local deformation was computed. Finally, the deformed image was warped to match the pre-operative image. For error calculation we used a phantom representing the urinary bladder and the prostate. The phantom could be deformed to mimic tissue deformation. Error calculation was done using corresponding landmarks in both images. The resulting target registration error of this procedure amounted to 1.63 mm. With respect to patient data a full deformable registration was performed on two 3D-US images of the abdomen. The resulting mean distance error was 2.10 ± 0.66 mm compared to an error of 2.75 ± 0.57 mm from a simple rigid registration. A two-sided paired t-test showed a p-value < 0.001. We conclude that the method improves the results of the rigid registration considerably. Provided an appropriate choice of the filter there are many possible fields of applications.
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spelling pubmed-64200332019-04-02 Deformable registration of 3D ultrasound volumes using automatic landmark generation Figl, Michael Hoffmann, Rainer Kaar, Marcus Hummel, Johann PLoS One Research Article US image registration is an important task e.g. in Computer Aided Surgery. Due to tissue deformation occurring between pre-operative and interventional images often deformable registration is necessary. We present a registration method focused on surface structures (i.e. saliencies) of soft tissues like organ capsules or vessels. The main concept follows the idea of representative landmarks (so called leading points). These landmarks represent saliencies in each image in a certain region of interest. The determination of deformation was based on a geometric model assuming that saliencies could locally be described by planes. These planes were calculated from the landmarks using two dimensional linear regression. Once corresponding regions in both images were found, a displacement vector field representing the local deformation was computed. Finally, the deformed image was warped to match the pre-operative image. For error calculation we used a phantom representing the urinary bladder and the prostate. The phantom could be deformed to mimic tissue deformation. Error calculation was done using corresponding landmarks in both images. The resulting target registration error of this procedure amounted to 1.63 mm. With respect to patient data a full deformable registration was performed on two 3D-US images of the abdomen. The resulting mean distance error was 2.10 ± 0.66 mm compared to an error of 2.75 ± 0.57 mm from a simple rigid registration. A two-sided paired t-test showed a p-value < 0.001. We conclude that the method improves the results of the rigid registration considerably. Provided an appropriate choice of the filter there are many possible fields of applications. Public Library of Science 2019-03-15 /pmc/articles/PMC6420033/ /pubmed/30875379 http://dx.doi.org/10.1371/journal.pone.0213004 Text en © 2019 Figl et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Figl, Michael
Hoffmann, Rainer
Kaar, Marcus
Hummel, Johann
Deformable registration of 3D ultrasound volumes using automatic landmark generation
title Deformable registration of 3D ultrasound volumes using automatic landmark generation
title_full Deformable registration of 3D ultrasound volumes using automatic landmark generation
title_fullStr Deformable registration of 3D ultrasound volumes using automatic landmark generation
title_full_unstemmed Deformable registration of 3D ultrasound volumes using automatic landmark generation
title_short Deformable registration of 3D ultrasound volumes using automatic landmark generation
title_sort deformable registration of 3d ultrasound volumes using automatic landmark generation
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6420033/
https://www.ncbi.nlm.nih.gov/pubmed/30875379
http://dx.doi.org/10.1371/journal.pone.0213004
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