Computer aided system for brain abnormalities segmentation

Ibrahim, Shafaf and Abdul Khalid, Noor Elaiza and Manaf, Mazani (2010) Computer aided system for brain abnormalities segmentation. Computer Aided System for Brain Abnormalities, 1 (1). pp. 22-39.

Abstract

Detection of abnormalities in brain tissue area in different medical images is inspired by the necessity of high accuracy when dealing with human life. A Variety of diseases occur in brain tissue area such as brain tumour, stroke, infarction, haemorrhage and others. At the present time, the current method that is used for diagnosing those diseases is using a well known digital imaging technique which is Magnetic Resonance Imaging (MRI), though the brain diseases are still difficult to diagnose due to certain circumstances. Thus, Computer Aided System (CAS) is significantly useful due to the fact that it could enhance the results of humans in such domain. It is also important that the false negative cases must be kept at a very low rate. This paper proposes a development of a CAD that implement image processing techniques for segmenting any kind of abnormalities that occur in human brain tissue area. The system is able to determine the patterns and characteristics for each part of particular brain tissue in order to identify any brain abnormalities. The behind idea is that the local textures in the images can reveal the characteristic of abnormalities of the biological structures. Therefore, the system is expected to detect threats in patients and planning for early treatment strategies in the future.

Metadata

Item Type: Article
Creators:
Creators
Email / ID Num.
Ibrahim, Shafaf
UNSPECIFIED
Abdul Khalid, Noor Elaiza
UNSPECIFIED
Manaf, Mazani
UNSPECIFIED
Subjects: A General Works > Indexes (General)
Divisions: Universiti Teknologi MARA, Shah Alam > Faculty of Computer and Mathematical Sciences
Journal or Publication Title: Computer Aided System for Brain Abnormalities
Volume: 1
Number: 1
Page Range: pp. 22-39
Date: 2010
URI: https://ir.uitm.edu.my/id/eprint/10374
Edit Item
Edit Item

Download

[thumbnail of 10374.pdf] Text
10374.pdf

Download (1MB)

ID Number

10374

Indexing

Statistic

Statistic details