Classification of Colposcopic Cervigrams Using EMD in R

  • Kumar Dron Shrivastav
  • Ankan Mukherjee Das
  • Harpreet Singh
  • Priya Ranjan
  • Rajiv JanardhananEmail author
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 968)


Cervical cancer is one of the most common cancer among women world-wide which can be cured if detected early. The current gold standard for cervical cancer diagnosis is clumsy and time consuming because it relies heavily on the subjective knowledge of the medical professionals which often results in false negatives and false positives. To reduce time and operational complexities associated with early diagnosis, we require a portable interactive diagnostic tool for early detection, particularly in developing countries where cervical cancer incidence and related mortality is high. Incorporation of digital colposcopy in place of manual diagnosis for cervical cancer screening can increase the precision and strongly reduce the chances of error in a time-specific manner. Thus, we propose a robust and interactive colposcopic image analysis and diagnostic tool, which can categorically process colposcopic images into Type I, Type II and Type III cervigrams and identify lesions in least amount of time. Furthermore, successful binning of diagnosed cervigrams into digital colposcopic library and incorporation of a set of specific parameters that are typically referred to for identification of transformation zone and SCJ (squamo columnar junction) with the help of open source Programming language - “R” is one of the major highlights of the application. The software has the ability to automatically identify and quantify the morphological features, color intensity, sensitivity and other parameters digitally which may improve and accelerate screening and early diagnosis, ultimately leading to timely treatment of cervical cancer.


Cervical cancer Cervigrams Early detection Digital pathology Screening 



The authors duly acknowledge the support of mobileODT for the provision of cervigrams obtained through mobileODT EVA system at Batra Hospital & Medical Research Centre, New Delhi, India under the supervision of Dr. Shelly Batra.


  1. 1.
    Human Papillomavirus and Related Diseases Report WORLD version posted at on 27 July 2017 (2017).
  2. 2.
    Screening as well as vaccination is essential in the fight against cervical cancer. Accessed 09 July 2018
  3. 3.
    Intel & Mobile ODT Cervical cancer Screening. Accessed 10 July 2018
  4. 4.
    Yossi, R., Carlo, T., Leonidas, J.G.: The Earth Mover’s Distance as a metric for image retrieval. Int. J. Comput. Vis. 40(2), 99–121 (2000)CrossRefGoogle Scholar
  5. 5.
    WHO guidelines for screening and treatment of precancerous lesions for cervical cancer prevention. Accessed 21 May 2017
  6. 6.
    Saslow, D., Solomon, D., Lawson, H.W., et al.: American Cancer Society, American Society for Colposcopy and Cervical Pathology, and American Society for Clinical Pathology screening guidelines for the prevention and early detection of cervical cancer. CA Cancer J. Clin. 62(3), 147–172 (2012)CrossRefGoogle Scholar
  7. 7.
    Massad, L.S., et al.: 2012 updated consensus guidelines for the management of abnormal cervical cancer screening tests and cancer precursors. Obstet. Gynecol. 121(4), 829–846 (2013)CrossRefGoogle Scholar
  8. 8.
    Ginsburg, O., et al.: The global burden of women’s cancers: a grand challenge in global health. Lancet 389(10071), 847–860 (2017)CrossRefGoogle Scholar
  9. 9.
    Lin, H.-C., Wu, H.-C., Chang, C.-H., Li, T.-C., Liang, W.-M., Wang, J.-Y.W.: Development of a real-time clinical decision support system upon the web MVC-based architecture for prostate cancer treatment. BMC Med. Inform. Decis. Mak. 11(16), 1–11 (2011)Google Scholar
  10. 10.
    Karakitsos, P., et al.: Identification of women for referral to colposcopy by neural networks: a preliminary study based on LBC and molecular biomarkers. J. Biomed. Biotechnol. 2012, 1–8 (2012). Scholar
  11. 11.
    Nessa, A., et al.: Evaluation of stationary colposcope and the gynocular, by the Swede score systematic colposcopic system in VIA positive women: a crossover randomized trial. Int. J. Gynecol. Cancer 24(2), 339–345 (2014)CrossRefGoogle Scholar
  12. 12.
    Ngonzi, J., et al.: Agreement of colposcope and Gynocular in assessment of cervical lesions by Swede score: a randomized, crossover pilot trial. J. Lower Genital Tract Dis. 17(4), 372–377 (2013)CrossRefGoogle Scholar
  13. 13.
    Peddie, D.: Cervical cancer screening in Kiribati. Pac. J. Reprod. Health 1(3), 132–134 (2016)CrossRefGoogle Scholar
  14. 14.
    Kass, A., Slyper, R., Levitz, D.: Optical design of low cost imaging systems for mobile medical applications. In: Optics and Biophotonics in Low-Resource Settings, vol. 9314, pp. 93140B-1–93140B-6 (2015)Google Scholar
  15. 15.
    Mink, J.W., Wexler, S., Bolton, F.J., Hummel, C., Kahn, B.S., Levitz, D.: Initial clinical testing of a multi-spectral imaging system built on a smartphone platform. In: Optics and Biophotonics in Low-Resource Settings II, vol. 9699, p. 96990R. International Society for Optics and Photonics (2016)Google Scholar
  16. 16.
    Bolton, F.J., Weiser, R., Kass, A.J., Rose, D., Safir, A., Levitz, D.: Development and bench testing of a multi-spectral imaging technology built on a smartphone platform. In: Optics and Biophotonics in Low-Resource Settings II, vol. 9699, p. 969907. International Society for Optics and Photonics (2016)Google Scholar
  17. 17.
    Rashmi, B., et al.: Feasibility of using mobile smartphone camera as an imaging device for screening of cervical cancer in a low-resource setting. J. Postgrad. Med. Educ. Res. 50, 69–74 (2016)CrossRefGoogle Scholar
  18. 18.
    Catarino, R., et al.: Smartphone use for cervical cancer screening in low-resource countries: a pilot study conducted in Madagascar. PloS one 10(7), 1–10 (2015)MathSciNetCrossRefGoogle Scholar
  19. 19.
    Muschelli, J.: Neuroconductor: an R platform for medical imaging analysis. Biostatistics (2018)Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Kumar Dron Shrivastav
    • 1
  • Ankan Mukherjee Das
    • 1
  • Harpreet Singh
    • 2
  • Priya Ranjan
    • 3
  • Rajiv Janardhanan
    • 1
    Email author
  1. 1.Amity Institute of Public HealthNoidaIndia
  2. 2.Indian Council of Medical ResearchNew DelhiIndia
  3. 3.Amity School of Engineering & TechnologyAmity UniversityNoidaIndia

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