Keywords:-

Keywords: External beam radiation therapy(EBRT), Artificial Neural Network (ANN), Expectation Maximization Segmentation (EM).

Article Content:-

Abstract

External beam radiation therapy for the treatment of cancer make likely correct placement of radiation dosage on the cancerous region.Still, the deformation of soft tissue through the progress of treatment, such as in cervical cancer, presents important challenges for the outlining of the target volume and other structures .The segmentation of cervical cancer Magnetic ResonanceImage is done by using Expectation maximization segmentation algorithm. The tumor region is selected and the feature are extracted and finally the images are classified by using an Artificial Neural Network to identify the normal and abnormal tumor images.

References:-

References

C. Lopez and S. Chakravarti, ‘Imaging of cervical cancer’ ,Imaging,vol. 18, no. 1, pp. 10–19, 2006.

How many women get cancer of the cervix? Atlanta, GA, Am. Cancer Soc., 2010.

Jemal, F. Bray, M. M. Center, J. Ferlay, E.Ward, and D. Forman,“Global cancer statistics,” CA: A Cancer J. Clinicians, vol. 61, no. 2, pp. 69–90, 2011.

Chao Lu, SudhakarChelikani, David A. Jaffray, Michael F. Milosevic, Lawrence H. Staib, and James S. Duncan ,‘Simultaneous Non rigid Registration, Segmentation, and Tumor Detection in MRI Guided Cervical Cancer Radiation Therapy’, IEEE Transactions On Medical Imaging, Vol. 31, No. 6, June 2012.

Chunming Li, Rui Huang, Zhaohua Ding, J. Chris Gatenby, Dimitris N. Metaxas, , and John C. Gore, ‘A Level Set Method for Image Segmentation in the Presence of Intensity In homogeneities With Application to MRI’, IEEE Transactions On Image Processing, Vol. 20, No. 7, July 2011.

R. Potter, J. Dimopoulos, P. Georg, C. S. Lang, Waldhausl, N. Wachter-Gerstner, H. Weitmann, A. Reinthaller, T. H. Knocke, S. Wachter, and C. Kirisits, ‘Clinical impact of MRI assisted dose volume adaptation and dose escalation in brachytherapy of locallyadvanced cervix cancer,’ Radiotherapy Oncology., vol. 83, no. 2, pp. 148–155, 2007.

W. H. Greene, S. Chelikani, K. Purushothaman, Z. Chen, X. Papademetris,L. H. Staib, and J. S. Duncan, ‘Constrained non-rigid registration for use in image-guided adaptive radiotherapy,’Med.Image Anal., vol. 13, no. 5, pp. 809–817, 2009.

Devendram V, HemalathaThiagarajan, “Texturebased Scene Categorization using ArtificialNeural Networks and Support Vector Machines:A Comparative Study”, ICGST-GVIP, ISSN 1687-398X, Volume (8), Issue (IV), December 2008.

C. Kirkby, K. Stanescu, S. Rathee, M. Carlone, B. Murray, and B.G. Fallone, ‘Patient dosimetry for hybrid MRI-radiotherapy systems’,Med. Phys., vol. 35, no. 3, pp. 1019–1027, Mar. 2008.

Downloads

Citation Tools

How to Cite
Jagadeeswari, S., & Malarkhodi, S. (2014). Segmentation and Classification Using Artificial Neural Network Of Cervical Cancer In Magnetic Resonance Image. International Journal Of Mathematics And Computer Research, 2(05), 408-415. Retrieved from http://ijmcr.in/index.php/ijmcr/article/view/129