Survey Paper on Cervical Cancer Detection Through Artificial Intelligence Techniques

  IJCTT-book-cover
 
International Journal of Computer Trends and Technology (IJCTT)          
 
© 2018 by IJCTT Journal
Volume-57 Number-2
Year of Publication : 2018
Authors : R. Rajpriya, Dr.M.S.Saravanan
DOI :  10.14445/22312803/IJCTT-V57P119

MLA

R. Rajpriya, Dr.M.S.Saravanan, "Survey Paper on Cervical Cancer Detection Through Artificial Intelligence Techniques". International Journal of Computer Trends and Technology (IJCTT) V57(2):98-101, March 2018. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.

Abstract
Cervical cancer is one of the gravest threats to women’s lives. Cervical cancer is the second most common cancer among the females after breast cancer. It is estimated that over a million women worldwide currently affected with cervical cancer.World Health Organization estimates every year 1,22,844 women are diagnosed with cervical cancer and 67,477 women die from the disease. There are several tests that can effectively detect Pre-cancer. Artificial intelligence (AI) concepts, techniques, tools have been utilized in medical applications in improving their effectiveness, productivity and consistency. The precision in distinguishing a cancerous structure from a benign structure has the potential to immediately improve health outcomes in one of our more pressing diseases. Automating the cancer diagnosis process can play a very significant role in reducing the number of cancer diagnosis is semiautomatic and is prone to human error and time consuming. A computer system that performs automatic grading can assist pathologists by providing second opinions, reducing their workload, and altering them to cases that requires closer attention, allowing them to focus on diagnosis and prognosis. This paper discussed the recent advances and future perspectives in relation to cervical cancer detection.

References
[1]. WHO/ICO Information Centre on HPV and Cervical cancer summary report on HPV and Cervical cancer statistics in India 2017.
[2].World Health Organization, 2014, Comprehensive cervical cancer: a guide to essential practice.
[3].D.B.Patil,Dr.S.B.Patil,B.T.Salokhe,R.T.Patil, Segmentation based Specular Reflection Detection in Uterine Cervix images,IOSR-JECE,pp:37-41.
[4]. Abhishek Das, Avijit Kar,Debasis Bhattacharyya, Probabilistic Segmentation Methods for early detection of Uterine Cervical cancer, Journal of Applied Information Science, vol1,June 2013.
[5]. Melissa C.Skala,Chanfang Zhu,Annette Gendron-Fitzpatrick,An Investigation of Fiber-Optic probe designs for Spectroscopic Diagnosis of epithelial pre-cancers,NIH-PA,PMC 2009.
[6].JyotismitaTalukdar,Chandan,Kr.Nath,P.H.Talukdar, Fuzzy Clustering based Image Segmentation of pap smear images of cervical cancer cell Using FCM Algorithm,IJCTT,volume3,Issue1,July 2013.
[7]. Anita Mahadevan-Jansen, Michale Follen Mitchell,Nirmala Ramanujam,Anias Malpica,Sharon Thomson,Urs Utzinger,Rebecca Richards-Kortum, Near-Infrared Raman Spectroscopy for In Vitro Detection of Cervical Precancers, Photochemistry and photobiology,68(1),1998.
[8]. M.Anousouya Devi,S.Ravi,J.Vaishnavi S.Punitha, Detection of Cervical cancer using the Image Classification Algorithms,IJCTA,9(3),pp.153-166,2016.
[9]. Zhang,J.,&Liu,Y, Cervical cancer Detection Using SVM Based,(2),873-880,2004.
[10]. Brown,L.G.;A Survey of Image Segmentation Techniques;ACM Computing Survey,24(4):325-376,1992.
[11].S. Gordon,G. Zimmerman,H. GreenSpain” Image Segmentation of Uterine Cervix images for indexing in PACS”, symposium on Computer-Based Medical Systems, Bethesda, Meryland, vol91,pp1-6, June 2004.
[12]. Blum,A.,Langley,P.,Selection of relevant features and examples in Machine Learning: Artificial Intelligence,245- 271,1997.
[13]. http://en.wikipedia.org/wiki/discriminant.

Keywords
Cervical cancer, Pap smear test, Artificial Intelligence Techniques.