Open AccessIntegrated Modelling Approach for Enhancing Brain MRI with Flexible Pre-Processing Capability
Author(s) -
S. Harish,
G. F. Ali Ahammed
Publication year - 2019
Publication title -
international journal of electrical and computer engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.277
H-Index - 22
ISSN - 2088-8708
DOI - 10.11591/ijece.v9i4.pp2416-2424
Subject(s) - computer science , preprocessor , quality assurance , segmentation , artificial intelligence , image processing , magnetic resonance imaging , image quality , image segmentation , image (mathematics) , computer vision , machine learning , medicine , radiology , pathology , external quality assessment
The assurance of an information quality of the input medical image is a critical step to offer highly precise and reliable diagnosis of clinical condition in human. The importance of such assurance becomes more while dealing with important organ like brain. Magnetic Resonance Imaging (MRI) is one of the most trusted mediums to investigate brain. Looking into the existing trends of investigating brain MRI, it was observed that researchers are more prone to investigate advanced problems e.g. segmentation, localization, classification, etc considering image dataset. There is less work carried out towards image preprocessing that potential affects the later stage of diagnosing. Therefore, this paper introduces a novel model of integrated image enhancement algorithm that is capable of solving different and discrete problems of performing image pre-processing for offering highly improved and enhanced brain MRI. The comparative outcomes exhibit the advantage of its simplistic implemetation strategy.