A tracking approach to parcellation of the cerebral cortex

Chris Adamson; Leigh Johnston; Terrie Inder; Sandra Rees; Iven Mareels; Gary Egan

doi:10.1007/11566465_37

A tracking approach to parcellation of the cerebral cortex

Chris Adamson, Leigh Johnston, Terrie Inder, Sandra Rees, Iven Mareels, Gary Egan

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review

3 Citations (Scopus)

Abstract

The cerebral cortex is composed of regions with distinct laminar structure. Functional neuroimaging results are often reported with respect to these regions, usually by means of a brain "atlas". Motivated by the need for more precise atlases, and the lack of model-based approaches in prior work in the field, this paper introduces a novel approach to parcellating the cortex into regions of distinct laminar structure, based on the theory of target tracking. The cortical layers are modelled by hidden Markov models and are tracked to determine the Bayesian evidence of layer hypotheses. This model-based parcellation method, evaluated here on a set of histological images of the cortex, is extensible to 3-D images.

Original language	English
Title of host publication	Medical Image Computing and Computer-Assisted Intervention - MICCAI 2005 - 8th International Conference, Proceedings
Pages	294-301
Number of pages	8
DOIs	https://doi.org/10.1007/11566465_37
Publication status	Published - 1 Dec 2005
Externally published	Yes
Event	Medical Image Computing and Computer-Assisted Intervention 2005 - Palm Springs, United States of America Duration: 26 Oct 2005 → 29 Oct 2005 Conference number: 8th https://link.springer.com/book/10.1007/11566465 (Proceedings)

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	3749 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	Medical Image Computing and Computer-Assisted Intervention 2005
Abbreviated title	MICCAI 2005
Country/Territory	United States of America
City	Palm Springs
Period	26/10/05 → 29/10/05
Internet address	https://link.springer.com/book/10.1007/11566465 (Proceedings)

Access to Document

10.1007/11566465_37

Cite this

Adamson, C., Johnston, L., Inder, T., Rees, S., Mareels, I., & Egan, G. (2005). A tracking approach to parcellation of the cerebral cortex. In Medical Image Computing and Computer-Assisted Intervention - MICCAI 2005 - 8th International Conference, Proceedings (pp. 294-301). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3749 LNCS). https://doi.org/10.1007/11566465_37

Adamson, Chris ; Johnston, Leigh ; Inder, Terrie et al. / A tracking approach to parcellation of the cerebral cortex. Medical Image Computing and Computer-Assisted Intervention - MICCAI 2005 - 8th International Conference, Proceedings. 2005. pp. 294-301 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{2998a987eaf64aaea962cc4680a7deab,

title = "A tracking approach to parcellation of the cerebral cortex",

abstract = "The cerebral cortex is composed of regions with distinct laminar structure. Functional neuroimaging results are often reported with respect to these regions, usually by means of a brain {"}atlas{"}. Motivated by the need for more precise atlases, and the lack of model-based approaches in prior work in the field, this paper introduces a novel approach to parcellating the cortex into regions of distinct laminar structure, based on the theory of target tracking. The cortical layers are modelled by hidden Markov models and are tracked to determine the Bayesian evidence of layer hypotheses. This model-based parcellation method, evaluated here on a set of histological images of the cortex, is extensible to 3-D images.",

author = "Chris Adamson and Leigh Johnston and Terrie Inder and Sandra Rees and Iven Mareels and Gary Egan",

year = "2005",

month = dec,

day = "1",

doi = "10.1007/11566465_37",

language = "English",

isbn = "3540293272",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

pages = "294--301",

booktitle = "Medical Image Computing and Computer-Assisted Intervention - MICCAI 2005 - 8th International Conference, Proceedings",

note = "Medical Image Computing and Computer-Assisted Intervention 2005, MICCAI 2005 ; Conference date: 26-10-2005 Through 29-10-2005",

url = "https://link.springer.com/book/10.1007/11566465",

}

Adamson, C, Johnston, L, Inder, T, Rees, S, Mareels, I & Egan, G 2005, A tracking approach to parcellation of the cerebral cortex. in Medical Image Computing and Computer-Assisted Intervention - MICCAI 2005 - 8th International Conference, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 3749 LNCS, pp. 294-301, Medical Image Computing and Computer-Assisted Intervention 2005, Palm Springs, California, United States of America, 26/10/05. https://doi.org/10.1007/11566465_37

A tracking approach to parcellation of the cerebral cortex. / Adamson, Chris; Johnston, Leigh; Inder, Terrie et al.
Medical Image Computing and Computer-Assisted Intervention - MICCAI 2005 - 8th International Conference, Proceedings. 2005. p. 294-301 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3749 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review

TY - GEN

T1 - A tracking approach to parcellation of the cerebral cortex

AU - Adamson, Chris

AU - Johnston, Leigh

AU - Inder, Terrie

AU - Rees, Sandra

AU - Mareels, Iven

AU - Egan, Gary

N1 - Conference code: 8th

PY - 2005/12/1

Y1 - 2005/12/1

N2 - The cerebral cortex is composed of regions with distinct laminar structure. Functional neuroimaging results are often reported with respect to these regions, usually by means of a brain "atlas". Motivated by the need for more precise atlases, and the lack of model-based approaches in prior work in the field, this paper introduces a novel approach to parcellating the cortex into regions of distinct laminar structure, based on the theory of target tracking. The cortical layers are modelled by hidden Markov models and are tracked to determine the Bayesian evidence of layer hypotheses. This model-based parcellation method, evaluated here on a set of histological images of the cortex, is extensible to 3-D images.

AB - The cerebral cortex is composed of regions with distinct laminar structure. Functional neuroimaging results are often reported with respect to these regions, usually by means of a brain "atlas". Motivated by the need for more precise atlases, and the lack of model-based approaches in prior work in the field, this paper introduces a novel approach to parcellating the cortex into regions of distinct laminar structure, based on the theory of target tracking. The cortical layers are modelled by hidden Markov models and are tracked to determine the Bayesian evidence of layer hypotheses. This model-based parcellation method, evaluated here on a set of histological images of the cortex, is extensible to 3-D images.

UR - http://www.scopus.com/inward/record.url?scp=33744812469&partnerID=8YFLogxK

U2 - 10.1007/11566465_37

DO - 10.1007/11566465_37

M3 - Conference Paper

AN - SCOPUS:33744812469

SN - 3540293272

SN - 9783540293279

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 294

EP - 301

BT - Medical Image Computing and Computer-Assisted Intervention - MICCAI 2005 - 8th International Conference, Proceedings

T2 - Medical Image Computing and Computer-Assisted Intervention 2005

Y2 - 26 October 2005 through 29 October 2005

ER -

Adamson C, Johnston L, Inder T, Rees S, Mareels I, Egan G. A tracking approach to parcellation of the cerebral cortex. In Medical Image Computing and Computer-Assisted Intervention - MICCAI 2005 - 8th International Conference, Proceedings. 2005. p. 294-301. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/11566465_37

A tracking approach to parcellation of the cerebral cortex

Abstract

Publication series

Conference

Access to Document

Other files and links

Cite this