Comprehensive Classification Model for Diagnosing Multiple Disease Condition from Chest X-Ray

Classification plays a significant role in the diagnosis of any form of radiological images in the healthcare sector. After reviewing existing classification approaches carried out over chest radiographs, it was explored that existing techniques are highly restricted to perform binary classification...

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Bibliographic Details
Published in:International journal of advanced computer science & applications 2018, Vol.9 (9)
Main Authors: K, Savitha S, Naveen, N.C.
Format: Article
Language:English
Subjects:
Classification
Diagnosis
Image classification
Image retrieval
Iterative methods
Medical imaging
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Summary:Classification plays a significant role in the diagnosis of any form of radiological images in the healthcare sector. After reviewing existing classification approaches carried out over chest radiographs, it was explored that existing techniques are highly restricted to perform binary classification that is not comprehensive for assisting in an effective diagnosis process of chest disease condition. This paper presents a novel approach to classifying chest x-rays on the basis of the practical disease condition. Harnessing the potential features of content-based image retrieval, the proposed system introduces a novel concept of attribute map that not only performs comprehensive classification but also makes the complete computational model extremely lightweight. The study outcome proved to offer better accuracy with the proposed non-iterative process in contrast to existing classifier design.
ISSN:2158-107X
2156-5570
DOI:10.14569/IJACSA.2018.090943