Colon Cancer Biopsy Image Analysis using Deep Learning
Anuja A. Ubale1, S. G. Shikalpure2
1Anuja Ubale, Department of Computer Science and Engineering Government College of Engineering, Aurangabad, Maharashtra, India.
2Assistant Prof. S. G. Shikalpure, Department of Computer Science and Engineering, Government College of Engineering, Aurangabad, Maharashtra, India.
Manuscript received on 01 March 2019 | Revised Manuscript received on 07 March 2019 | Manuscript published on 30 July 2019 | PP: 5694-5697 | Volume-8 Issue-2, July 2019 | Retrieval Number: B3202078219/2019©BEIESP | DOI: 10.35940/ijrte.B3202.078219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: According to WHO (world health organization) colon cancer is third most commonly identified cancer in male as well as female. It is cancer of colon or rectum, located in inner side of colon wall or rectum wall in large intestine. There are different method used to diagnoses and staging of colon cancer like, colonoscopy, blood testing, biopsy method. Clear analysis of these method used for diagnose the disease. In these method some methods are time consuming if approach is manual analysis and perform on medical images. That’s the reason it required some automated, efficient and accrete machine or technique. To design such machine biopsy image analysis by deep learning play an important role to design and creation of machine that used for biopsy method diagnoses. We work on three model, CNN, VGG16 and InceptionV3 .it provide different accuracy. CNN gives 72%, VGG16 gives 71% and InceptionV3 gives 89% accuracy. Hence proposed method used to significant accuracy improvement automated diagnoses system.
Index Terms: Deep Learning, CNN, VGG16, IncepctionV3, Colon Cancer.
Scope of the Article: Deep Learning