NDLI: Fractional crow search-based support vector neural network for patient classification and severity analysis of tuberculosis

Content Provider	IET Digital Library
Author	Chithra, R. S. Jagatheeswari, P.
Abstract	The world is chasing towards the automation in the severity analysis and classification of the patients based on the severity of tuberculosis (TB). The automatic classification is very much useful for developing countries that are struggling to reduce the fatality rate of the persons suffering from TB as it is a top standing infectious disease. Thus, the automatic classification of the TB patients using the sputum images with the proposed fractional crow search-based support vector neural network is presented. The proposed classification method is the integration of the fractional theory in the crow search algorithm that increases the computational speed and reduces the cost and time spent on analysing the test samples. The importance of the proposed method is that it requires minimum manual power and hence, the inaccuracies are reduced. The experimentation performed using the Ziehl–Neelsen sputum smear microscopy image database proves that the proposed classifier is highly accurate and offered an improved performance in terms of accuracy rate, true positive rate, and false-positive rate.
Starting Page	108
Ending Page	117
Page Count	10
ISSN	17519659
Volume Number	13
e-ISSN	17519667
Issue Number	Issue 1, Jan (2019)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-ipr/13/1
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2018.5825
Journal	IET Image Processing
Publisher Date	2018-10-16
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Automatic Classification Biology And Medical Computing Biomedical Imaging/measurement Biomedical Optical Imaging Classification Method Computational Speed Computer Vision And Image Processing Technique Crow Search Algorithm Diseases False-positive Rate Fractional Crow Search-based Support Vector Neural Network Fractional Theory Image Classification Image Colour Analysis Image Segmentation Knowledge Engineering Technique Medical Image Processing Neural Computing Technique Neural Nets Optical And Laser Radiation Optical Microscopy Optical, Image And Video Signal Processing Patient Classification Patient Diagnostic Method And Instrumentation Severity Analysis Sputum Image Support Vector Machine TB Patients Tuberculosis
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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