Statistical texture analysis of MRI images to classify patients affected by multiple sclerosis

IFMBE Proceedings

Volumn 29, Issue , 2010, Pages 272-275

  Faro, A ^a   Giordano, D ^a   Spampinato, C ^a   Pennisi, M ^a  

^a UNIVERSITY OF CATANIA   (Italy)

Author keywords

MRI processing; Multiple Sclerosis; Neural Network Classification; Statistical Texture Analysis

Indexed keywords

EDGE DETECTION FILTERS; IMAGE GRAY LEVEL; IMAGE PROCESSING TECHNIQUE; MLP NEURAL NETWORKS; MRI (MAGNETIC RESONANCE IMAGING); MRI IMAGE; MRI PROCESSING; MULTIPLE SCLEROSIS; NEURAL NETWORK CLASSIFICATION; PRE-PROCESSING; STATISTICAL FEATURES; STATISTICAL MOMENTS; STATISTICAL TEXTURE ANALYSIS; TEXTURE ANALYSIS; TEXTURE FEATURES; VISION BASED SYSTEM; WHITE MATTER;

BIOCHEMICAL ENGINEERING; EDGE DETECTION; FEATURE EXTRACTION; IMAGE PROCESSING; MEDICAL COMPUTING; NEURAL NETWORKS; RESONANCE; STATISTICS; TEXTURES;

MAGNETIC RESONANCE IMAGING;

EID: 77957605889     PISSN: 16800737     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1007/978-3-642-13039-7_68     Document Type: Conference Paper

References (11)

1. Mantyla R., Erkinjuntti T., Salonen O., et al Variable agreement between visual rating scales for white matter hyperintensities on MRI. Comparison of 13 rating scales in a poststroke cohort Stroke. 1997;28:1614-1623.
2. Weisenfeld N. I., Warfield S. K. Automatic segmentation of newborn brain MRI Neuroimage. 2009;47:564-572.
3. Chao W. H., Chen Y. Y., Lin S. H., Shih Y. Y., Tsang S. Automatic segmentation of magnetic resonance images using a decision tree with spatial information Comput Med Imaging Graph. 2009;33:111-121.
4. Akselrod-Ballin A., Galun M., Gomori J. M., et al Automatic segmentation and classification of multiple sclerosis in multichannel MRI IEEE Trans Biomed Eng. 2009;56:2461-2469.
5. Boer R., Vrooman H. A., Lijn F., et al White matter lesion extension to automatic brain tissue segmentation on MRI Neuroimage. 2009;45:1151-1161.
6. Khayati R., Vafadust M., Towhidkhah F., Nabavi S. M. A novel method for automatic determination of different stages of multiple sclerosis lesions in brain MR FLAIR images Comput Med Imaging Graph. 2008;32:124-133.
7. Maillard P., Delcroix N., Crivello F., et al An automated procedure for the assessment of white matter hyperintensities by multispectral (T1, T2, PD) MRI and an evaluation of its between-centre repro-ducibility based on two large community databases Neuroradiology. 2008;50:31-42.
8. Cocosco C.A., Kollokian V., Kwan R.K.-S., A.C. Evans. BrainWeb: Online Interface to a 3D MRI Simulated Brain Database in NeuroImage Proceedings of 3rd International Conference on Functional Mapping of the Human Brain 1997.
9. Prastawa M., Bullitt E., Gerig G. Simulation of Brain Tumors in MR Images for Evaluation of Segmentation Efficacy Medical Image Analysis (MedIA). 2008: (in press).
10. Wolforth M., Ward G., Marrett S. EMMA: Extensible MATLAB Medical Analysis User Manual 1995.
11. Wu Jie, Poehlman Skip, Noseworthy Michael D., Kamath Markad V. Texture Feature based Automated Seeded Region Growing in Abdominal MRI Segmentation in BMEI '08: Proceedings of the 2008 International Conference on BioMedical Engineering and Informatics: 263-267 2008.