Effect of slice thickness on brain magnetic resonance image texture analysis

BioMedical Engineering Online

Volumn 9, Issue , 2010, Pages

  Savio, Sami J ^a,b   Harrison, Lara C V ^b,c   Luukkaala, Tiina ^d,e   Heinonen, Tomi ^b,f   Dastidar, Prasun ^a,b,c   Soimakallio, Seppo ^a,c   Eskola, Hannu J ^a,b  

^a TAMPERE UNIVERSITY HOSPITAL   (Finland)

^b TAMPERE UNIVERSITY OF TECHNOLOGY   (Finland)

^c UNIVERSITY OF TAMPERE MEDICAL SCHOOL   (Finland)

^d PIRKANMAA HOSPITAL DISTRICT   (Finland)

^e UNIVERSITY OF TAMPERE   (Finland)

^f NOKIA RESEARCH CENTER   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BRAIN MAGNETIC RESONANCE IMAGES; BRAIN TISSUE; CLINICAL EVALUATION; IMAGE QUALITY PARAMETERS; MAGNETIC RESONANCE IMAGES; MAGNETIC RESONANCE SCANNERS; MULTIPLE SCLEROSIS; NONLINEAR DISCRIMINANT ANALYSIS; PARAMETER VALUES; REGIONS OF INTEREST; SIGNED RANK; SIMULATE-3; SLICE THICKNESS; STATISTICAL APPROACH; TEST SETS; TEXTURE ANALYSIS; WHITE MATTER; WHITE MATTER TISSUES;

DISCRIMINANT ANALYSIS; IMAGE QUALITY; IMAGE SEGMENTATION; MAGNETIC RESONANCE; MAGNETIC RESONANCE IMAGING;

TEXTURES;

ADOLESCENT; ADULT; ARTICLE; BRAIN; DISCRIMINANT ANALYSIS; FEMALE; HUMAN; IMAGE PROCESSING; MALE; METHODOLOGY; MIDDLE AGED; MULTIPLE SCLEROSIS; NONPARAMETRIC TEST; NUCLEAR MAGNETIC RESONANCE IMAGING; PATHOLOGY;

ADOLESCENT; ADULT; BRAIN; DISCRIMINANT ANALYSIS; FEMALE; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; MAGNETIC RESONANCE IMAGING; MALE; MIDDLE AGED; MULTIPLE SCLEROSIS; STATISTICS, NONPARAMETRIC; YOUNG ADULT;

EID: 77957913938     PISSN: 1475925X     EISSN: 1475925X     Source Type: Journal    
DOI: 10.1186/1475-925X-9-60     Document Type: Article

References (19)

1. Hajek M, Dezortova M, Materka A, Lerski R, . (Ed) Texture Analysis for Magnetic Resonance Imaging. 2006, Prague, Med4 Publishing, (Ed).
2. Castellano G, Bonilha L, Li LM, Cendes F. Texture analysis of medical images. Clin Radiol 2004, 59:1061-1069. 10.1016/j.crad.2004.07.008, 15556588.
3. Bonilha L, Kobayashi E, Castellano G, Coelho G, Tinois E, Cendes F, Li LM. Texture analysis of hippocampal sclerosis. Epilepsia 2003, 44:1546-1550. 10.1111/j.0013-9580.2003.27103.x, 14636326.
4. McDonald WI, Compston A, Edan G, Goodkin D, Hartung HP, Lublin FD, McFarland HF, Paty DW, Polman CH, Reingold SC, Sandberg-Wollheim M, Sibley W, Thompson A, Van Den Noort S, Weinshenker BY, Wolinsky JS. Recommended diagnostic criteria for multiple sclerosis: Guidelines from the international panel on the diagnosis of multiple sclerosis. Ann Neurol 2001, 50:121-127. 10.1002/ana.1032, 11456302.
5. Polman CH, Reingold SC, Edan G, Filippi M, Hartung HP, Kappos L, Lublin FD, Metz LM, McFarland HF, O'Connor PW, Sandberg-Wollheim M, Thompson AJ, Weinshenker BG, Wolinsky JS. Diagnostic criteria for multiple sclerosis: 2005 revisions to the "McDonald criteria". Ann Neurol 2005, 58:840-846. 10.1002/ana.20703, 16283615.
6. Herlidou-Meme S, Constans JM, Carsin B, Olivie D, Eliat PA, Nadal-Desparats L, Gondry C, Le Rumeur E, Idy-Peretti I, de Certaines JD. MRI texture analysis on texture test objects, normal brain and intracranial tumors. Magn Reson Imaging 2003, 21:989-993. 10.1016/S0730-725X(03)00212-1, 14684201.
7. Materka A, Strzelecki M, Lerski R, Schad L. Feature evaluation of texture test objects for magnetic resonance imaging. Texture Analysis in Machine Vision, Series in Machine Perception and Artificial Intelligence 2000, 40:197-206. Singapore, World Scientific Publishing Co. Pte. Ltd, Pietikainen MK.
8. Guggenbuhl P, Chappard D, Garreau M, Bansard JY, Chales G, Rolland Y. Reproducibility of CT based bone texture parameters of cancellous calf bone samples: Influence of slice thickness. Eur J Radiol 2008, 67:514-520. 10.1016/j.ejrad.2007.08.003, 17869469.
9. Jirak D, Dezortova M, Hajek M. Phantoms for texture analysis of MR images. Texture Analysis for Magnetic Resonance Imaging 2006, 115-127. Prague, Med4 Publishing, Hajek M, Dezortova M, Materka A, Lerski R.
10. Mayerhoefer ME, Szomolanyi P, Jirak D, Materka A, Trattnig S. Effects of MRI acquisition parameter variations and protocol heterogeneity on the results of texture analysis and pattern discrimination: An application-oriented study. Med Phys 2009, 36:1236-1243. 10.1118/1.3081408, 19472631.
11. Schad LR, Lundervold A. Influence of resolution and signal to noise ratio on MR image texture. Texture Analysis for Magnetic Resonance Imaging 2006, 129-149. Prague, Med4 Publishing, Hajek M, Dezortova M, Materka A, Lerski R.
12. Harrison LCV, Raunio M, Holli K, Luukkaala T, Savio S, Elovaara I, Soimakallio S, Eskola H, Dastidar P. MRI texture analysis in multiple sclerosis: Toward clinical analysis protocol. Acad Radiol 2010, 17:696-707. 10.1016/j.acra.2010.01.005, 20457414.
13. Barbosa S, Blumhardt LD, Roberts N, Lock T, Edwards RHT. Magnetic resonance relaxation time mapping in multiple sclerosis: normal appearing white matter and the 'invisible' lesion load. Magn Reson Imaging 1994, 12:33-42. 10.1016/0730-725X(94)92350-7, 8295506.
14. Filippi M, Horsfield MA, Campi A, Mammi S, Pereira C, Comi G. Resolution-dependent estimates of lesion volumes in magnetic resonance imaging studies of the brain in multiple sclerosis. Ann Neurol 1995, 38:749-754. 10.1002/ana.410380509, 7486866.
15. MATLAB - The Language Of Technical Computing. , http://www.mathworks.com/products/matlab/
16. Collewet G, Strzelecki M, Mariette F. Influence of MRI acquisition protocols and image intensity normalization methods on texture classification. Magn Reson Imaging 2004, 22:81-91. 10.1016/j.mri.2003.09.001, 14972397.
17. MaZda Web Site. , http://www.eletel.p.lodz.pl/programy/mazda/
18. Mahmoud-Ghoneim D, Toussaint G, Constans JM, de Certaines JD. Three dimensional texture analysis in MRI: A preliminary evaluation in gliomas. Magn Reson Imaging 2003, 21:983-987. 10.1016/S0730-725X(03)00201-7, 14684200.
19. Zhang J, Tong L, Wang L, Li N. Texture analysis of multiple sclerosis: A comparative study. Magn Reson Imaging 2008, 26:1160-1166. 10.1016/j.mri.2008.01.016, 18513908.