Computational atlases of severity of white matter lesions in elderly subjects with MRI

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

Volumn 5241 LNCS, Issue PART 1, 2008, Pages 450-458

  Hadjidemetriou, Stathis ^a   Lorenzen, Peter ^a   Schuff, Norbert ^b   Mueller, Susanne ^b   Weiner, Michael ^b  

^a NCIRE/VA UCSF   (United States)

^b UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

Brain lesion segmentation; Computational atlas construction; Intensity correction; Lesion severity

Indexed keywords

BRAIN FUNCTIONS; BRAIN IMAGES; BRAIN LESION SEGMENTATION; CEREBROVASCULAR DISEASE; COGNITIVE IMPAIRMENT; COMPUTATIONAL ATLAS CONSTRUCTION; INTENSITY CORRECTION; LESION IMAGE; LESION SEVERITY; NORMAL CONTROLS; PROCESSING STEPS; RIGID REGISTRATION; STATISTICAL DIFFERENCES; WHITE MATTER; WHITE MATTER LESIONS;

COMPUTER SCIENCE; MEDICAL IMAGING;

MEDICAL COMPUTING;

AGED; ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; COGNITIVE DEFECT; COMPUTER ASSISTED DIAGNOSIS; DEMYELINATING DISEASE; FEMALE; HOSPITALIZATION; HUMAN; IMAGE ENHANCEMENT; IMAGE SUBTRACTION; MALE; METHODOLOGY; MYELINATED NERVE; NUCLEAR MAGNETIC RESONANCE IMAGING; PATHOLOGY; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY;

AGED; ALGORITHMS; ARTIFICIAL INTELLIGENCE; COGNITION DISORDERS; DEMYELINATING DISEASES; FEMALE; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; MAGNETIC RESONANCE IMAGING; MALE; NERVE FIBERS, MYELINATED; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SEVERITY OF ILLNESS INDEX; SUBTRACTION TECHNIQUE;

EID: 58849085185     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-85988-8_54     Document Type: Conference Paper

References (16)

1. Erkinjuntti, T., Gao, F., Lee, D.: Lack of difference in brain hyperintensities between patients with early Alzheimer's disease and control subjects. Arch. Neurol. 51, 260-268 (1994)
2. Pantoni, L., Simoni, M., Pracucci, G.: European task on age-related white matter changes. Visual rating scales for age-related white matter changes (leukoaraiosis). Can the heterogeneity be reduced? Stroke 33, 2827-2833 (2002)
3. Jack, C., O'Brien, P., Rettman, D., Shiung, M., Xu, Y., Muthupillai, R., Manduca, A., Avula, R., Erickson, B.: FLAIR histogram segmentation for measurement of leukoaraiosis volume. Journal of Magnetic Resonance Imaging 14, 668-676 (2001)
4. Wen, W., Sachdev, P.: The topography of white matter hyperintensities on brain MRI in healthy 60-to 64-year-old individuals. Neuroimage 22, 144-154 (2004)
5. Yoshita, M., Fletcher, E., DeCarli, C.: Current concepts of analysis of cerebral white matter hyperintensities on magnetic resonance imaging. Topics in Magnetic Resonance Imaging 16(6), 399-407 (2005)
6. Walderveen, M., Kamphorst, W., Scheltens, P.: Histopathologic correlate of hypointense lesions on T1-weighted spin-echo MRI in multiple sclerosis. Neurology 50, 1282-1288 (1998)
7. Pham, S., Shen, D., Herskovits, E., Resnick, S., Davatzikos, C.: Automatic segmentation of white matter lesions in T1-weighted brain MR images. In: Proc. of ISBI, pp. 253-256 (2002)
8. Ballin, A., Galun, M., Gomori, M., Filippi, M., Valsasina, P., Basil, R., Brandt, A.: An integrated segmentation and classification approach applied to multiple sclerosis analysis. In: Proc. of CVPR, pp. 1122-1129 (2006)
9. Warfield, S., Dengler, J., Zaers, J., Guttmann, C., Wells, W., Ettinger, G., Hiller, J., Kikinis, R.: Automatic identification of grey matter structures from MRI to improve the segmentation of white matter lesions. Journal of Image Guided Surgery 1(6), 326-338 (1995)
10. Hadjidemetriou, S., Studholme, C., Mueller, S., Weiner, M., Schuff, N.: Restoration of MRI data for field nonuniformities using high order neighborhood statistics. In: Proc. of SPIE Medical Image Processing, vol. 6512 (2007)
11. Smith, S.: Fast robust automated brain extraction. Proc. of Human Brain Mapping 17, 143-155 (2002)
12. Rovaris, M., Comi, G., Rocca, M., Cercignani, M., Colombo, B., Santuccio, G., Filippi, M.: Relevance of hypointense lesions on fast fluid-attenuated inversion recovery MR images as a marker of disease severity in cases of multiple sclerosis. American Journal of Neuroradiology 20, 813-820 (1999)
13. Boykov, Y., Veksler, O., Zabih, R.: Fast approximate energy minimization via graph cuts. IEEE Trans. on PAMI 23(11), 1222-1239 (2001)
14. Kovalev, V., Kruggel, F., Gertz, H., Cramon, D.: Three-dimensional texture analysis of MRI brain datasets. IEEE Trans. on Medical Imaging 20(5), 424-433 (2001)
15. Zalesny, A., Ferrari, V., Caenen, G., Gool, L.: Composite texture synthesis. International Journal of Computer Vision 62(1/2), 161-176 (2005)
16. Joshi, S., Davis, B., Jomier, M., Gerig, G.: Unbiased diffeomorphic atlas construction for computational anatomy. Neuroimage 23, S151-S160 (2004)