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Detection of Hydrocephalus Lateral Ventricles Quantitatively in Brain MRI images of Infants

by S. Javeed Hussain, T. Satya Savitri, P. V. Sree Devi
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 83 - Number 9
Year of Publication: 2013
Authors: S. Javeed Hussain, T. Satya Savitri, P. V. Sree Devi
10.5120/14475-2698

S. Javeed Hussain, T. Satya Savitri, P. V. Sree Devi . Detection of Hydrocephalus Lateral Ventricles Quantitatively in Brain MRI images of Infants. International Journal of Computer Applications. 83, 9 ( December 2013), 12-15. DOI=10.5120/14475-2698

@article{ 10.5120/14475-2698,
author = { S. Javeed Hussain, T. Satya Savitri, P. V. Sree Devi },
title = { Detection of Hydrocephalus Lateral Ventricles Quantitatively in Brain MRI images of Infants },
journal = { International Journal of Computer Applications },
issue_date = { December 2013 },
volume = { 83 },
number = { 9 },
month = { December },
year = { 2013 },
issn = { 0975-8887 },
pages = { 12-15 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume83/number9/14475-2698/ },
doi = { 10.5120/14475-2698 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:58:53.480870+05:30
%A S. Javeed Hussain
%A T. Satya Savitri
%A P. V. Sree Devi
%T Detection of Hydrocephalus Lateral Ventricles Quantitatively in Brain MRI images of Infants
%J International Journal of Computer Applications
%@ 0975-8887
%V 83
%N 9
%P 12-15
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this paper, a new clustering method is applied to segmentation and volume change assessment in lateral ventricles affected by hydrocephalus pathology in the infants. The hydrocephalus is characterized as such, which results from excessive accumulation of cerebrospinal fluid in the ventricles, leading to enlargement of cerebral ventricles. The complex shape o the ventricular system is evaluated by a visual assessment of MRI scans, but still there is necessity to note the amount of change in volume. We present a algorithm with adjustable feature weight with Optimal feature selection using validity function. The algorithm is called Optomal feature Weight adjustable FCM with Gaussian smoothing (OfwaFCM). There was need to develop new algorithm for segmenting non-symmetric images. The objective of this algorithm is to produce fine clustering results and to reduce effect of noise. In this method, clustering centroids and functions are used to evaluate the clustering results and validity fuction based on fuzzy partitioning is used to select Optimal Feature Weights. The results produced states that the proposed scheme provides Volume calculation and clustering performances for Detecting and segmenting the hydrocephalus.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Feature Weighted Vectors Gaussian mixture model Fuzzy c-means Fuzzy medical image processing

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