The Creation of a Brain Atlas for Image Guided Neurosurgery Using Serial Histological Data
Identifieur interne : 000D17 ( Istex/Curation ); précédent : 000D16; suivant : 000D18The Creation of a Brain Atlas for Image Guided Neurosurgery Using Serial Histological Data
Auteurs : M. Mallar Chakravarty [Canada] ; Gilles Bertrand [Canada] ; Maxime Descouteaux [Canada] ; Abbas F. Sadikot [Canada] ; D. Louis Collins [Canada]Source :
- Lecture Notes in Computer Science [ 0302-9743 ] ; 2003.
Abstract
Abstract: Digital atlases of the human brain can help in the specific localization of structures of surgical relevance and interest in Image Guided Neurosurgery (IGNS). This paper outlines one of the steps in the creation of a digital atlas intended for IGNS, using histological data. The acquisition of histological data can include artefacts such as tearing, shearing, stretching, shrinking, as well as inhomogeneous staining leading to structural inhomogeneities. These inconsistencies are reduced using a non-linear intensity based registration procedure where deformations are defined using a maximized correlation coefficient estimate. The intensity artefacts brought about by inhomogeneous staining are reduced by applying a slice to slice intensity inhomogeneity correction by modelling the intensity mapping between slices as a third order polynomial that is estimated with a Least Trimmed Squared fit. The lateral ventricle was then segmented and to demonstrate increased smoothing along its surface.
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DOI: 10.1007/978-3-540-39899-8_43
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Mallar Chakravarty</name><affiliation wicri:level="1"><mods:affiliation>Montreal Neurological Institute (MNI), McGill University, Montreal, Canada</mods:affiliation><country xml:lang="fr">Canada</country><wicri:regionArea>Montreal Neurological Institute (MNI), McGill University, Montreal</wicri:regionArea></affiliation></author><author><name sortKey="Bertrand, Gilles" sort="Bertrand, Gilles" uniqKey="Bertrand G" first="Gilles" last="Bertrand">Gilles Bertrand</name><affiliation wicri:level="1"><mods:affiliation>Montreal Neurological Institute (MNI), McGill University, Montreal, Canada</mods:affiliation><country xml:lang="fr">Canada</country><wicri:regionArea>Montreal Neurological Institute (MNI), McGill University, Montreal</wicri:regionArea></affiliation><affiliation wicri:level="1"><mods:affiliation>Division of Neurosurgery, McGill University, Montreal, Canada</mods:affiliation><country xml:lang="fr">Canada</country><wicri:regionArea>Division of Neurosurgery, McGill University, Montreal</wicri:regionArea></affiliation></author><author><name sortKey="Descouteaux, Maxime" sort="Descouteaux, Maxime" uniqKey="Descouteaux M" first="Maxime" last="Descouteaux">Maxime Descouteaux</name><affiliation wicri:level="1"><mods:affiliation>Center for Intelligent Machines (CIM), McGill University, Montreal, Canada</mods:affiliation><country xml:lang="fr">Canada</country><wicri:regionArea>Center for Intelligent Machines (CIM), McGill University, Montreal</wicri:regionArea></affiliation></author><author><name sortKey="Sadikot, Abbas F" sort="Sadikot, Abbas F" uniqKey="Sadikot A" first="Abbas F." last="Sadikot">Abbas F. 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Louis Collins</name><affiliation wicri:level="1"><mods:affiliation>Montreal Neurological Institute (MNI), McGill University, Montreal, Canada</mods:affiliation><country xml:lang="fr">Canada</country><wicri:regionArea>Montreal Neurological Institute (MNI), McGill University, Montreal</wicri:regionArea></affiliation></author></analytic><monogr></monogr><series><title level="s">Lecture Notes in Computer Science</title><imprint><date>2003</date></imprint><idno type="ISSN">0302-9743</idno><idno type="eISSN">1611-3349</idno><idno type="ISSN">0302-9743</idno></series></biblStruct></sourceDesc><seriesStmt><idno type="ISSN">0302-9743</idno></seriesStmt></fileDesc><profileDesc><textClass></textClass><langUsage><language ident="en">en</language></langUsage></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Abstract: Digital atlases of the human brain can help in the specific localization of structures of surgical relevance and interest in Image Guided Neurosurgery (IGNS). This paper outlines one of the steps in the creation of a digital atlas intended for IGNS, using histological data. The acquisition of histological data can include artefacts such as tearing, shearing, stretching, shrinking, as well as inhomogeneous staining leading to structural inhomogeneities. These inconsistencies are reduced using a non-linear intensity based registration procedure where deformations are defined using a maximized correlation coefficient estimate. The intensity artefacts brought about by inhomogeneous staining are reduced by applying a slice to slice intensity inhomogeneity correction by modelling the intensity mapping between slices as a third order polynomial that is estimated with a Least Trimmed Squared fit. The lateral ventricle was then segmented and to demonstrate increased smoothing along its surface.</div></front></TEI></record>Pour manipuler ce document sous Unix (Dilib)
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