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MR-based automatic delineation of volumes of interest in human brain PET images using probability maps.

Research output: Contribution to journalJournal articleResearchpeer-review

Harvard

Svarer, C, Madsen, K, Hasselbalch, SG, Pinborg, LH, Haugbøl, S, Frøkjær, VG, Holm, S, Paulson, OB & Knudsen, GM 2005, 'MR-based automatic delineation of volumes of interest in human brain PET images using probability maps.' NeuroImage, vol. 24, no. 4, pp. 969-979.

APA

Svarer, C., Madsen, K., Hasselbalch, S. G., Pinborg, L. H., Haugbøl, S., Frøkjær, V. G., ... Knudsen, G. M. (2005). MR-based automatic delineation of volumes of interest in human brain PET images using probability maps. NeuroImage, 24(4), 969-979.

CBE

Svarer C, Madsen K, Hasselbalch SG, Pinborg LH, Haugbøl S, Frøkjær VG, Holm S, Paulson OB, Knudsen GM. 2005. MR-based automatic delineation of volumes of interest in human brain PET images using probability maps. NeuroImage. 24(4):969-979.

MLA

Vancouver

Svarer C, Madsen K, Hasselbalch SG, Pinborg LH, Haugbøl S, Frøkjær VG et al. MR-based automatic delineation of volumes of interest in human brain PET images using probability maps. NeuroImage. 2005;24(4):969-979.

Author

Svarer, Claus ; Madsen, Karina ; Hasselbalch, Steen G. ; Pinborg, Lars H ; Haugbøl, Steven ; Frøkjær, Vibe G. ; Holm, Søren ; Paulson, Olaf B. ; Knudsen, Gitte M. / MR-based automatic delineation of volumes of interest in human brain PET images using probability maps. In: NeuroImage. 2005 ; Vol. 24, No. 4. pp. 969-979.

Bibtex

@article{1081002068d84045a403bb44fe0ddbab,
title = "MR-based automatic delineation of volumes of interest in human brain PET images using probability maps.",
abstract = "The purpose of this study was to develop and validate an observer-independent approach for automatic generation of volume-of-interest (VOI) brain templates to be used in emission tomography studies of the brain. The method utilizes a VOI probability map created on the basis of a database of several subjects' MR-images, where VOI sets have been defined manually. High-resolution structural MR-images and 5-HT(2A) receptor binding PET-images (in terms of (18)F-altanserin binding) from 10 healthy volunteers and 10 patients with mild cognitive impairment were included for the analysis. A template including 35 VOIs was manually delineated on the subjects' MR images. Through a warping algorithm template VOI sets defined from each individual were transferred to the other subjects MR-images and the voxel overlap was compared to the VOI set specifically drawn for that particular individual. Comparisons were also made for the VOI templates 5-HT(2A) receptor binding values. It was shown that when the generated VOI set is based on more than one template VOI set, delineation of VOIs is better reproduced and shows less variation as compared both to transfer of a single set of template VOIs as well as manual delineation of the VOI set. The approach was also shown to work equally well in individuals with pronounced cerebral atrophy. Probability-map-based automatic delineation of VOIs is a fast, objective, reproducible, and safe way to assess regional brain values from PET or SPECT scans. In addition, the method applies well in elderly subjects, even in the presence of pronounced cerebral atrophy",
author = "Claus Svarer and Karina Madsen and Hasselbalch, {Steen G.} and Pinborg, {Lars H} and Steven Haugb{\o}l and Fr{\o}kj{\ae}r, {Vibe G.} and S{\o}ren Holm and Paulson, {Olaf B.} and Knudsen, {Gitte M}",
year = "2005",
language = "English",
volume = "24",
pages = "969--979",
journal = "NeuroImage",
issn = "1053-8119",
publisher = "Academic Press",
number = "4",

}

RIS

TY - JOUR

T1 - MR-based automatic delineation of volumes of interest in human brain PET images using probability maps.

AU - Svarer, Claus

AU - Madsen, Karina

AU - Hasselbalch, Steen G.

AU - Pinborg, Lars H

AU - Haugbøl, Steven

AU - Frøkjær, Vibe G.

AU - Holm, Søren

AU - Paulson, Olaf B.

AU - Knudsen, Gitte M

PY - 2005

Y1 - 2005

N2 - The purpose of this study was to develop and validate an observer-independent approach for automatic generation of volume-of-interest (VOI) brain templates to be used in emission tomography studies of the brain. The method utilizes a VOI probability map created on the basis of a database of several subjects' MR-images, where VOI sets have been defined manually. High-resolution structural MR-images and 5-HT(2A) receptor binding PET-images (in terms of (18)F-altanserin binding) from 10 healthy volunteers and 10 patients with mild cognitive impairment were included for the analysis. A template including 35 VOIs was manually delineated on the subjects' MR images. Through a warping algorithm template VOI sets defined from each individual were transferred to the other subjects MR-images and the voxel overlap was compared to the VOI set specifically drawn for that particular individual. Comparisons were also made for the VOI templates 5-HT(2A) receptor binding values. It was shown that when the generated VOI set is based on more than one template VOI set, delineation of VOIs is better reproduced and shows less variation as compared both to transfer of a single set of template VOIs as well as manual delineation of the VOI set. The approach was also shown to work equally well in individuals with pronounced cerebral atrophy. Probability-map-based automatic delineation of VOIs is a fast, objective, reproducible, and safe way to assess regional brain values from PET or SPECT scans. In addition, the method applies well in elderly subjects, even in the presence of pronounced cerebral atrophy

AB - The purpose of this study was to develop and validate an observer-independent approach for automatic generation of volume-of-interest (VOI) brain templates to be used in emission tomography studies of the brain. The method utilizes a VOI probability map created on the basis of a database of several subjects' MR-images, where VOI sets have been defined manually. High-resolution structural MR-images and 5-HT(2A) receptor binding PET-images (in terms of (18)F-altanserin binding) from 10 healthy volunteers and 10 patients with mild cognitive impairment were included for the analysis. A template including 35 VOIs was manually delineated on the subjects' MR images. Through a warping algorithm template VOI sets defined from each individual were transferred to the other subjects MR-images and the voxel overlap was compared to the VOI set specifically drawn for that particular individual. Comparisons were also made for the VOI templates 5-HT(2A) receptor binding values. It was shown that when the generated VOI set is based on more than one template VOI set, delineation of VOIs is better reproduced and shows less variation as compared both to transfer of a single set of template VOIs as well as manual delineation of the VOI set. The approach was also shown to work equally well in individuals with pronounced cerebral atrophy. Probability-map-based automatic delineation of VOIs is a fast, objective, reproducible, and safe way to assess regional brain values from PET or SPECT scans. In addition, the method applies well in elderly subjects, even in the presence of pronounced cerebral atrophy

M3 - Journal article

VL - 24

SP - 969

EP - 979

JO - NeuroImage

JF - NeuroImage

SN - 1053-8119

IS - 4

ER -

ID: 32567090