CFP last date
20 May 2024
Reseach Article

Acid Fast Stain Sputum Smear Images Data Set for Diagnosis of Tuberculosis

Published on April 2013 by Mukti Jadhav, Prachi P. Janrao, K. V. Kale
International Conference and Workshop on Emerging Trends in Technology 2013
Foundation of Computer Science USA
ICWET2013 - Number 1
April 2013
Authors: Mukti Jadhav, Prachi P. Janrao, K. V. Kale
75f7bf4b-25f2-402e-92ed-ad1b4cac8dd6

Mukti Jadhav, Prachi P. Janrao, K. V. Kale . Acid Fast Stain Sputum Smear Images Data Set for Diagnosis of Tuberculosis. International Conference and Workshop on Emerging Trends in Technology 2013. ICWET2013, 1 (April 2013), 8-13.

@article{
author = { Mukti Jadhav, Prachi P. Janrao, K. V. Kale },
title = { Acid Fast Stain Sputum Smear Images Data Set for Diagnosis of Tuberculosis },
journal = { International Conference and Workshop on Emerging Trends in Technology 2013 },
issue_date = { April 2013 },
volume = { ICWET2013 },
number = { 1 },
month = { April },
year = { 2013 },
issn = 0975-8887,
pages = { 8-13 },
numpages = 6,
url = { /proceedings/icwet2013/number1/11328-1343/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 International Conference and Workshop on Emerging Trends in Technology 2013
%A Mukti Jadhav
%A Prachi P. Janrao
%A K. V. Kale
%T Acid Fast Stain Sputum Smear Images Data Set for Diagnosis of Tuberculosis
%J International Conference and Workshop on Emerging Trends in Technology 2013
%@ 0975-8887
%V ICWET2013
%N 1
%P 8-13
%D 2013
%I International Journal of Computer Applications
Abstract

Many of the computer science researchers now work for design automatic system for fast & accurate recognition of tuberculosis(TB), to speed up the treatment process of patient to save patient life. Any type of research is not possible without data. It is critical for computer researcher to prepare Ziehl-Neelsen stain sputum smear slide & to setup image acquisition technique on simple light microscope. We are preparing acid fast stain sputum smear images data set using light microscope withdigital camera at the eye piece of microscope. The dataset contain 400 total images (300 images are positive for Tb and 100 negative for Tb). These captured image dataset is available for many researchers. One of the application is applied on 50 of these images

References
  1. "Supporting Laboratory Services", (DHHS/CDC) funded by the U. S. Agency for International Development. Grant Agreement 118-G-00-99-00112 (WHO) and PASA 118-P-00-98-00165,WHO/CDS/TB/2002. 310
  2. J. A. C. Luna, "A Tuberculosis Guide for Specialist Physicians", International Union against Tuberculosis and Lung Disease, 2004.
  3. "Surgical Pathology – Histology Staining Manual Microorganisms", Downloaded from WebPath: Internet Pathology Laboratory http://www-medlib. med. utah. edu/WebPath/webpath. html
  4. Lyon, H (1991), "Theorey and strategy in histochemistry", Springer - Verlag
  5. "Sputum Microscopy Instruction to Laboratory Technicians",Tuberculosis research center, Chetput. Printed at Diocesan press Madras-60007-C624
  6. Matlab Help Files "Analyzing mages", Math Works Cambridge MA. 2009
  7. SmailAvc?bas, Bu¨ lent Sankur, Khalid Sayood "Statistical evaluation of image quality measures", 206 / Journal of Electronic Imaging / April 2002 / Vol. 11(2)
  8. Image Statistics Based on material from Digital Imaging: Theory and Applications, H. E. Burdick, McGraw-Hill, 1997
  9. RethabileKhutlang, Sriram Krishnan, Andrew Whitelaw, Tania S Douglas, "Detection of Tuberculosis in sputum smear images using two one-class classifiers", 978-1-4244-3932-4/09/$25. 00 ©2009 IEEE
  10. MuharremMercimek, KayhanGulez and TarikVelimumcu,"Real object recognition using moment invariants", Sadhana Vol. 30, Part 6, December 2005, pp. 765–775. © Printed in India
  11. Chih-Wei Hsu, Chih-Chung Chang, and Chih-Jen Lin, "A Practical Guide to Support Vector Classification", Initial version: 2003 Last updated: April 15, 2010
  12. SergiosTheodoridisKonstantinos, "An Introduction to Pattern Recognition A MATLAB Approach", British Library Cataloguing-in-Publication Data.
  13. Bremner D, Demaine E, Erickson J, Iacono J, Langerman S, Morin P, Toussaint G, "Output-sensitive algorithms for computing nearest-neighbor decision boundaries". Discrete and Computational Geometry 33 (4): 593–604, 2005.
  14. Cover TM, Hart PE (1967). "Nearest neighbor pattern classification". IEEE Transactions on Information Theory 13 (1): 21–27
  15. Toussaint GT (April 2005). "Geometric proximity graphs for improving nearest neighbor methods in instance-based learning and data mining". International Journal of Computational Geometry and Applications 15 (2): 101–150.
  16. Howard Anton (Feb. 2002),"Elementary Linear Algebra 5e" Publisher John Wiley & Sons Inc, ISBN 0-471-85223-6
Index Terms

Computer Science
Information Sciences

Keywords

Ziehl-neelsen Stain Image Segmentation Acid Fast Stain