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Non-invasive estimation of intracranial pressure in traumatic brain injury (TBI) using fully-anisotropic Morlet wavelet transform and support vector regression

Non-invasive estimation of intracranial pressure in traumatic brain injury (TBI) using... Biomed Eng Lett (2013) 3:190-197 DOI 10.1007/s13534-013-0102-2 ORIGINAL ARTICLE Non-invasive Estimation of Intracranial Pressure in Traumatic Brain Injury (TBI) Using Fully-anisotropic Morlet Wavelet Transform and Support Vector Regression Babak Seyed Aghazadeh, Sardar Ansari, Ramana Pidaparti and Kayvan Najarian Received: 12 July 2013 / Revised: 31 August 2013 / Accepted: 23 September 2013 © The Korean Society of Medical & Biological Engineering and Springer 2013 Abstract classification accuracy rate of 94.43 percent is achieved. Purpose This paper aims to estimate the intracranial pressure Also, using SVR, the ICP estimation results demonstrate that (ICP) in patients with traumatic brain injuries (TBI) non- the proposed algorithm yields excellent performance with a invasively using directional features obtained from the texture mean absolute error of 4.25 mmHg compared to Dual Tree of brain CT image and support vector regression (SVR) complex wavelet transform features with the mean absolute method. error of 5.48 mmHg. Methods A fully anisotropic Morlet wavelet transform is Conclusions The severity of TBI is assessed non-invasively performed on brain CT images and optimal feature vectors using brain CT images, and the directional textural features have been extracted to classify the images into two groups of of brain tissue. The proposed algorithm http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Biomedical Engineering Letters Springer Journals

Non-invasive estimation of intracranial pressure in traumatic brain injury (TBI) using fully-anisotropic Morlet wavelet transform and support vector regression

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References (15)

Publisher
Springer Journals
Copyright
Copyright © 2013 by Korean Society of Medical and Biological Engineering and Springer
Subject
Engineering; Biomedical Engineering; Biophysics and Biological Physics; Biomedicine general; Medical and Radiation Physics
ISSN
2093-9868
eISSN
2093-985X
DOI
10.1007/s13534-013-0102-2
Publisher site
See Article on Publisher Site

Abstract

Biomed Eng Lett (2013) 3:190-197 DOI 10.1007/s13534-013-0102-2 ORIGINAL ARTICLE Non-invasive Estimation of Intracranial Pressure in Traumatic Brain Injury (TBI) Using Fully-anisotropic Morlet Wavelet Transform and Support Vector Regression Babak Seyed Aghazadeh, Sardar Ansari, Ramana Pidaparti and Kayvan Najarian Received: 12 July 2013 / Revised: 31 August 2013 / Accepted: 23 September 2013 © The Korean Society of Medical & Biological Engineering and Springer 2013 Abstract classification accuracy rate of 94.43 percent is achieved. Purpose This paper aims to estimate the intracranial pressure Also, using SVR, the ICP estimation results demonstrate that (ICP) in patients with traumatic brain injuries (TBI) non- the proposed algorithm yields excellent performance with a invasively using directional features obtained from the texture mean absolute error of 4.25 mmHg compared to Dual Tree of brain CT image and support vector regression (SVR) complex wavelet transform features with the mean absolute method. error of 5.48 mmHg. Methods A fully anisotropic Morlet wavelet transform is Conclusions The severity of TBI is assessed non-invasively performed on brain CT images and optimal feature vectors using brain CT images, and the directional textural features have been extracted to classify the images into two groups of of brain tissue. The proposed algorithm

Journal

Biomedical Engineering LettersSpringer Journals

Published: Oct 9, 2013

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