<abstract xmlns="http://www.w3.org/1999/xhtml"><p>Hydrocephalus is a pathological condition of the central nervous system which often affects neonates and young children. It manifests itself as an abnormal accumulation of cerebrospinal fluid within the ventricular system of the brain with its subsequent progression. One of the most important diagnostic methods of identifying hydrocephalus is Computer Tomography (CT). The enlarged ventricular system is clearly visible on CT scans. However, the assessment of the disease progress usually relies on the radiologist’s judgment and manual measurements, which are subjective, cumbersome and have limited accuracy. Therefore, this paper regards the problem of semi-automatic assessment of hydrocephalus using image processing and analysis algorithms. In particular, automated determination of popular indices of the disease progress is considered. Algorithms for the detection, semi-automatic segmentation and numerical description of the lesion are proposed. Specifically, the disease progress is determined using shape analysis algorithms. Numerical results provided by the introduced methods are presented and compared with those calculated manually by a radiologist and a trained operator. The comparison proves the correctness of the introduced approach.</p></abstract>

Hydrocephalus is a pathological condition of the central nervous system which often affects neonates and young children. It manifests itself as an abnormal accumulation of cerebrospinal fluid within the ventricular system of the brain with its subsequent progression. One of the most important diagnostic methods of identifying hydrocephalus is Computer Tomography (CT). The enlarged ventricular system is clearly visible on CT scans. However, the assessment of the disease progress usually relies on the radiologist’s judgment and manual measurements, which are subjective, cumbersome and have limited accuracy. Therefore, this paper regards the problem of semi-automatic assessment of hydrocephalus using image processing and analysis algorithms. In particular, automated determination of popular indices of the disease progress is considered. Algorithms for the detection, semi-automatic segmentation and numerical description of the lesion are proposed. Specifically, the disease progress is determined using shape analysis algorithms. Numerical results provided by the introduced methods are presented and compared with those calculated manually by a radiologist and a trained operator. The comparison proves the correctness of the introduced approach.

Assessment of hydrocephalus in children based on digital image processing and analysis

Institute of Applied Computer Science Łódź University of Technology, Stefanowskiego 18/22, 90-924 Łódź, Poland

Department of Neurosurgery, Polish Mother’s Memorial Hospital, Research Institute in Łódź, Rzgowska 281/289, 93-338 Łódź, Poland

International Journal of Applied Mathematics and Computer Science

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Hydrocephalus is a pathological condition of the central nervous system which often affects neonates and young children. It manifests itself as an abnormal...

Assessment of hydrocephalus in children based on digital image processing and analysis

Published Online: Jun 26, 2014

Page range: 299 - 312

Received: Jan 17, 2013

DOI: https://doi.org/10.2478/amcs-2014-0022

Keywords
hydrocephalus, computed tomography, image segmentation, Evans index, frontal and occipital horn ratio, ventricular angle, frontal horn radius

© 2014 Anna Fabijańska et al.

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Assessment of hydrocephalus in children based on digital image processing and analysis

Published Online: Jun 26, 2014

Page range: 299 - 312

Received: Jan 17, 2013

DOI: https://doi.org/10.2478/amcs-2014-0022

Keywordshydrocephalus, computed tomography, image segmentation, Evans index, frontal and occipital horn ratio, ventricular angle, frontal horn radius

© 2014 Anna Fabijańska et al.

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Keywords
hydrocephalus, computed tomography, image segmentation, Evans index, frontal and occipital horn ratio, ventricular angle, frontal horn radius