uu.seUppsala University Publications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Methods for automatic analysis of glucose uptake in adipose tissue using quantitative PET/MRI data
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Radiology, Oncology and Radiation Science, Radiology.
2014 (English)Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Brown adipose tissue (BAT) is the main tissue involved in non-shivering heat production. A greater understanding of BAT could possibly lead to new ways of prevention and treatment of obesity and type 2 diabetes. The increasing prevalence of these conditions and the problems they cause society and individuals make the study of the subject important.

An ongoing study performed at the Turku University Hospital uses images acquired using PET/MRI with 18F-FDG as the tracer. Scans are performed on sedentary and athlete subjects during normal room temperature and during cold stimulation. Sedentary subjects then undergo scanning during cold stimulation again after a six weeks long exercise training intervention. This degree project used images from this study.

The objective of this degree project was to examine methods to automatically and objectively quantify parameters relevant for activation of BAT in combined PET/MRI data. A secondary goal was to create images showing glucose uptake changes in subjects from images taken at different times.

Parameters were quantified in adipose tissue directly without registration (image matching), and for neck scans also after registration. Results for the first three subjects who have completed the study are presented. Larger registration errors were encountered near moving organs and in regions with less information.

The creation of images showing changes in glucose uptake seem to be working well for the neck scans, and somewhat well for other sub-volumes. These images can be useful for identification of BAT. Examples of these images are shown in the report.

Place, publisher, year, edition, pages
2014. , 27 p.
Series
UPTEC F, ISSN 1401-5757 ; 14044
Keyword [en]
brown adipose tissue, medical images, image registration, BAT, PET, MRI
Keyword [sv]
brunt fett, medicinska bilder, bildregistrering, BAT, PET, MRI
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
URN: urn:nbn:se:uu:diva-233200OAI: oai:DiVA.org:uu-233200DiVA: diva2:751005
External cooperation
Åbo universitetscentralsjukhus
Educational program
Master Programme in Engineering Physics
Supervisors
Examiners
Available from: 2014-10-20 Created: 2014-09-30 Last updated: 2014-10-20Bibliographically approved

Open Access in DiVA

Andersson Methods for automatic analysis of glucose uptake in adipose tissue using quantitative PET MRI data(1324 kB)313 downloads
File information
File name FULLTEXT01.pdfFile size 1324 kBChecksum SHA-512
c8149c71196e4aae4447f1e9af4eaa0535efea6bfad60f8f96f6566e27b9f1942c77161975654a20b3d1b72eaef57a0f7b50a23c0a741daa6ef0903414d989f5
Type fulltextMimetype application/pdf

By organisation
Radiology
Computer Vision and Robotics (Autonomous Systems)

Search outside of DiVA

GoogleGoogle Scholar
Total: 313 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

urn-nbn

Altmetric score

urn-nbn
Total: 895 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf