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Real-Time Dynamic Data Driven Deformable Registration for Image-Guided Neurosurgery: Computational Aspects
Current neurosurgical procedures utilize medical images of various modalities to enable the precise location of tumors and critical brain structures to plan accurate brain tumor resection. The difficulty of using preoperative images during the surgery is caused by the intra-operative deformation of...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cornell University
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10508827/ https://www.ncbi.nlm.nih.gov/pubmed/37731651 |
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author | Chrisochoides, Nikos Fedorov, Andrey Liu, Yixun Kot, Andriy Foteinos, Panos Drakopoulos, Fotis Tsolakis, Christos Billias, Emmanuel Clatz, Olivier Ayache, Nicholas Golby, Alex Black, Peter Kikinis, Ron |
author_facet | Chrisochoides, Nikos Fedorov, Andrey Liu, Yixun Kot, Andriy Foteinos, Panos Drakopoulos, Fotis Tsolakis, Christos Billias, Emmanuel Clatz, Olivier Ayache, Nicholas Golby, Alex Black, Peter Kikinis, Ron |
author_sort | Chrisochoides, Nikos |
collection | PubMed |
description | Current neurosurgical procedures utilize medical images of various modalities to enable the precise location of tumors and critical brain structures to plan accurate brain tumor resection. The difficulty of using preoperative images during the surgery is caused by the intra-operative deformation of the brain tissue (brain shift), which introduces discrepancies concerning the preoperative configuration. Intra-operative imaging allows tracking such deformations but cannot fully substitute for the quality of the pre-operative data. Dynamic Data Driven Deformable Non-Rigid Registration (D(4)NRR) is a complex and time-consuming image processing operation that allows the dynamic adjustment of the pre-operative image data to account for intra-operative brain shift during the surgery. This paper summarizes the computational aspects of a specific adaptive numerical approximation method and its variations for registering brain MRIs. It outlines its evolution over the last 15 years and identifies new directions for the computational aspects of the technique. |
format | Online Article Text |
id | pubmed-10508827 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Cornell University |
record_format | MEDLINE/PubMed |
spelling | pubmed-105088272023-09-20 Real-Time Dynamic Data Driven Deformable Registration for Image-Guided Neurosurgery: Computational Aspects Chrisochoides, Nikos Fedorov, Andrey Liu, Yixun Kot, Andriy Foteinos, Panos Drakopoulos, Fotis Tsolakis, Christos Billias, Emmanuel Clatz, Olivier Ayache, Nicholas Golby, Alex Black, Peter Kikinis, Ron ArXiv Article Current neurosurgical procedures utilize medical images of various modalities to enable the precise location of tumors and critical brain structures to plan accurate brain tumor resection. The difficulty of using preoperative images during the surgery is caused by the intra-operative deformation of the brain tissue (brain shift), which introduces discrepancies concerning the preoperative configuration. Intra-operative imaging allows tracking such deformations but cannot fully substitute for the quality of the pre-operative data. Dynamic Data Driven Deformable Non-Rigid Registration (D(4)NRR) is a complex and time-consuming image processing operation that allows the dynamic adjustment of the pre-operative image data to account for intra-operative brain shift during the surgery. This paper summarizes the computational aspects of a specific adaptive numerical approximation method and its variations for registering brain MRIs. It outlines its evolution over the last 15 years and identifies new directions for the computational aspects of the technique. Cornell University 2023-09-06 /pmc/articles/PMC10508827/ /pubmed/37731651 Text en https://creativecommons.org/licenses/by-sa/4.0/This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License (https://creativecommons.org/licenses/by-sa/4.0/) , which allows reusers to distribute, remix, adapt, and build upon the material in any medium or format, so long as attribution is given to the creator. The license allows for commercial use. If you remix, adapt, or build upon the material, you must license the modified material under identical terms. |
spellingShingle | Article Chrisochoides, Nikos Fedorov, Andrey Liu, Yixun Kot, Andriy Foteinos, Panos Drakopoulos, Fotis Tsolakis, Christos Billias, Emmanuel Clatz, Olivier Ayache, Nicholas Golby, Alex Black, Peter Kikinis, Ron Real-Time Dynamic Data Driven Deformable Registration for Image-Guided Neurosurgery: Computational Aspects |
title | Real-Time Dynamic Data Driven Deformable Registration for Image-Guided Neurosurgery: Computational Aspects |
title_full | Real-Time Dynamic Data Driven Deformable Registration for Image-Guided Neurosurgery: Computational Aspects |
title_fullStr | Real-Time Dynamic Data Driven Deformable Registration for Image-Guided Neurosurgery: Computational Aspects |
title_full_unstemmed | Real-Time Dynamic Data Driven Deformable Registration for Image-Guided Neurosurgery: Computational Aspects |
title_short | Real-Time Dynamic Data Driven Deformable Registration for Image-Guided Neurosurgery: Computational Aspects |
title_sort | real-time dynamic data driven deformable registration for image-guided neurosurgery: computational aspects |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10508827/ https://www.ncbi.nlm.nih.gov/pubmed/37731651 |
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