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Signal, Image and Video Processing

, Volume 13, Issue 8, pp 1585–1592 | Cite as

Automated identification of mycobacterium bacillus from sputum images for tuberculosis diagnosis

  • K. S. MithraEmail author
  • W. R. Sam Emmanuel
Original Paper
  • 68 Downloads

Abstract

Tuberculosis is a terrible, transferrable disease instigated by infection with Mycobacterium tuberculosis bacillus. A common diagnosis of this infection is the microscopic examination of sputum smears of affected persons. This paper presents an automatic system for detecting the bacillus present in the stained microscopic images of sputum which eases the job of laboratory technician with manual detection. In this work, the Channel Area Thresholding algorithm is proposed for segmentation of the bacterial image. The intensity-based local bacilli features are extracted using location-oriented histogram and speeded up robust feature algorithm. The exact classification of the bacilli objects after segmentation is carried out using deep learning neural networks. Experimental results show that the proposed work had the classification accuracy of about 97.55 on sputum image dataset.

Keywords

Sputum images Tuberculosis Mycobacterium Bacilli features Segmentation 

Notes

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Copyright information

© Springer-Verlag London Ltd., part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Computer Science, NMCC, MarthandamAffiliated to Manonmaniam Sundaranar UniversityTirunelveliIndia

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