UCL Discovery
UCL home » Library Services » Electronic resources » UCL Discovery

Subject-specific Models for the Analysis of Pathological FDG PET Data

Burgos, N; Cardoso, MJ; Mendelson, AF; Schott, JM; Atkinson, D; Arridge, SR; Hutton, BF; (2015) Subject-specific Models for the Analysis of Pathological FDG PET Data. In: Navab, N and Hornegger, J and Wells, WM and Frangi, AF, (eds.) Proceedings of the 18th International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI). (pp. pp. 651-658). Springer, Cham: Munich, Germany. Green open access

[img] Text
paper639.pdf
Available under License : See the attached licence file.

Download (1MB)

Abstract

Abnormalities in cerebral glucose metabolism detectable on fluorodeoxyglucose positron emission tomography (FDG PET) can be assessed on a regional or voxel-wise basis. In regional analysis, the average relative uptake over a region of interest is compared with the average relative uptake obtained for normal controls. Prior knowledge is required to determine the regions where abnormal uptake is expected, which can limit its usability. On the other hand, voxel-wise analysis consists of comparing the metabolic activity of the patient to the normal controls voxel-by-voxel, usually in a groupwise space. Voxel-based techniques are limited by the inter-subject morphological and metabolic variability in the normal population, which can limit their sensitivity. In this paper, we combine the advantages of both regional and voxel-wise approaches through the use of subject-specific PET models for glucose metabolism. By accounting for inter-subject morphological differences, the proposed method aims to remove confounding variation and increase the sensitivity of group-wise approaches. The method was applied to a dataset of 22 individuals: 17 presenting four distinct neurodegenerative syndromes, and 5 controls. The proposed method more accurately distinguishes subgroups in this set, and improves the delineation of diseasespecific metabolic patterns.

Type: Proceedings paper
Title: Subject-specific Models for the Analysis of Pathological FDG PET Data
Event: 18th International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI)
Location: Munich, GERMANY
Dates: 05 October 2015 - 09 October 2015
ISBN-13: 9783319245706
Open access status: An open access version is available from UCL Discovery
DOI: 10.1007/978-3-319-24571-3_78
Publisher version: http://dx.doi.org/10.1007/978-3-319-24571-3_78
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Science & technology, technology, life sciences & biomedicine, computer science, artificial intelligence, computer science, interdisciplinary applications, computer science, theory & methods, radiology, nuclear medicine & medical imaging, computer science, glucose-metabolism, aphasia, brain.
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology > Neurodegenerative Diseases
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Div of Medicine
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Med Phys and Biomedical Eng
URI: https://discovery.ucl.ac.uk/id/eprint/1469264
Downloads since deposit
151Downloads
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item