Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/25320
Title: Segmentation and classification of brain mri using deformable, statistical And knowledge based approaches with Fft techniques
Researcher: Rajeswari, R
Guide(s): Anandhakumar, P
Keywords: CerebroSpinal Fluid
Magnetic resonance imaging
Pathological regions
White Matter
Upload Date: 22-Sep-2014
University: Anna University
Completed Date: 01-06-2012
Abstract: Magnetic resonance imaging MRI is a powerful medical imaging newlinemodality to produce high resolution images with good contrast of the newlinedifferent biological soft tissue types As a non invasive technique the large newlinequantity of data provided by MRI for brain imaging in particular aids newlinestatisticians and medical professionals in disease diagnosis and functional newlineunderstanding of the human brain In particular interest to this study is the newlineclassification of three main tissue types in the brain Gray Matter GM newlineWhite Matter WM and CerebroSpinal Fluid CSF and the segmentation of newlinemagnetic resonance images in patients with gliomas newlinePathological regions from MRI scans of normal adults and patients newlinewith neuro degenerative diseases are needed for improved understanding of newlinedisease progression in vivo As images are often confounded by acquisition newlinenoise and partial volume effects developing an automatic robust and newlineefficient segmentation is essential to the accurate quantification of disease newlineseverity A major challenge of this work is to devise robust techniques to newlineaddress the above said problems newline newline
Pagination: xxxviii, 289p.
URI: http://hdl.handle.net/10603/25320
Appears in Departments:Faculty of Information and Communication Engineering

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04_acknowledgement.pdf6.79 kBAdobe PDFView/Open
05_content.pdf91.92 kBAdobe PDFView/Open
06_chapter1.pdf1.12 MBAdobe PDFView/Open
07_chapter2.pdf123.92 kBAdobe PDFView/Open
08_chapter3.pdf1.52 MBAdobe PDFView/Open
09_chapter4.pdf3 MBAdobe PDFView/Open
10_chapter5.pdf997.54 kBAdobe PDFView/Open
11_chapter6.pdf1.31 MBAdobe PDFView/Open
12_chapter7.pdf33.46 kBAdobe PDFView/Open
13_appendix.pdf1.57 MBAdobe PDFView/Open
14_reference.pdf95.22 kBAdobe PDFView/Open
15_publication.pdf8.05 kBAdobe PDFView/Open
16_vitae.pdf5.75 kBAdobe PDFView/Open


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