PIB-PET segmentation for automatic SUVR normalisation without MR information

2007 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro - Proceedings

Volumn , Issue , 2007, Pages 348-351

  Raniga, Parnesh ^a,b   Bourgeat, Pierrick ^a   Ourselin, Sébastien ^a   Villemagne, Victor ^c   O'Keefe, Graeme ^c   Rowe, Christopher ^c  

^a CSIRO   (Australia)

^b UNIVERSITY OF SYDNEY   (Australia)

^c AUSTIN HOSPITAL   (Australia)

Author keywords

PET segmentation; PIB PET; SUVR

Indexed keywords

DATABASE SYSTEMS; DISEASES; FEATURE EXTRACTION; IMAGE SEGMENTATION; POSITRON EMISSION TOMOGRAPHY;

CEREBELLAR GREY MATTER; RADIO TRACERS; STANDARD UPTAKE VALUE RATIO (SUVR);

MEDICAL IMAGING;

EID: 36348974054     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ISBI.2007.356860     Document Type: Conference Paper

References (14)

1. A. Wimo and B. Winblad et al, "The magnitude of dementia occurrence in the world," Alzheimer Dis Assoc Disord, vol. 17. no. 2. pp. 63-67, Apr-Jun 2003.
2. L. Fratiglioni and L.J. Launer et al, "Incidence of dementia and major subtypes in Europe: A collaborative study of population-based cohorts, neurologic diseases in the elderly research group." Neurology, vol. 54, no. 11 Suppl 5, pp. 10-15, 2000.
3. J. Hardy and D.J. Selkoe, "The amyloid hypothesis of Alzheimer's disease: progress and problems on the road to therapeutics," Science, vol. 297, no. 5580, pp. 353-356, Jul 2002.
4. W.E. Klunk and H. Engler et al. "Imaging brain amyloid in Alzheimer's disease with Pittsburgh Compound-B," Ann Neurol, vol. 55. no. 3. pp. 306-319, Mar 2004.
5. W.E. Klunk and Y. Wang et al, "The binding of 2-(4'methylaminophenyl)benzothiazole to postmortem brain homogenates is dominated by the amyloid component," J Neurosa, vol. 23, no. 6, pp. 2086-2092, Mar 2003.
6. B.J. Lopresti and W.E. Klunk et al, "Simplified quantification of Pittsburgh Compound B amyloid imaging PET studies: a comparative analysis," J Nucl Med, vol. 46, no. 12, pp. 19591972, Dec 2005.
7. A. Hammers and M.J. Koepp et al, "Implementation and application of a brain template for multiple volumes of interest," Hum Brain Mapp, vol. 15, no. 3, pp. 165-174, Mar 2002.
8. A. Hammers and R. Allom et al, "Three-dimensional maximum probability atlas of the human brain, with particular reference to the temporal lobe," Hum Brain Mapp, vol. 19, no. 4, pp. 224-247, Aug 2003.
9. F. Yasuno and A.H. Hasnine et al. "Template-based method for multiple volumes of interest of human brain PET images," Neuroimage, vol. 16, no. 3 Pt 1, pp. 577-586, Jul 2002.
10. C. Svarer and K. Madsen et al, "MR-based automatic delineation of volumes of interest in human brain PET images using probability maps." Neuroimage, vol. 24. no. 4, pp. 969-979. Feb 2005.
11. K-P Wong and D. Feng et al, "Segmentation of dynamic PET images using cluster analysis." IEEE Trans Nucl Sci, vol. 49, no. 1, pp. 200-207, Feb. 2002.
12. J Kim and W. Cai et al, "Segmentation of VOI from multidimensional dynamic PET images by integrating spatial and temporal features," IEEE Trans Inf Technol Biomed, vol. 10, no. 4, pp. 637-646, Oct 2006.
13. K. Van Leemput and F. Maes et al, "Automated model-based tissue classification of MR images of the brain," IEEE TMI, vol. 18, pp. 897-908, 1999.
14. S. Ourselin and A. Roche et al. "Reconstructing a 3D structure from serial histological sections," IVC, vol. 19, pp. 25-31, 2001.