Computer Aided System for Automated Heterogeneous Cancer Recognition using Google Cloud Platform

International Journal of Computer Science and Engineering
© 2018 by SSRG - IJCSE Journal
Volume 5 Issue 5
Year of Publication : 2018
Authors : Ebanesar.C, Hamsa Vagini R, Sangeetha Bregit.A, Dr. J Dinesh Peter

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Citation:
MLA Style:

Ebanesar.C, Hamsa Vagini R, Sangeetha Bregit.A, Dr. J Dinesh Peter, "Computer Aided System for Automated Heterogeneous Cancer Recognition using Google Cloud Platform" SSRG International Journal of Computer Science and Engineering 5.5 (2018): 11-16.

APA Style:

Ebanesar.C, Hamsa Vagini R, Sangeetha Bregit.A, Dr. J Dinesh Peter,(2018). Computer Aided System for Automated Heterogeneous Cancer Recognition using Google Cloud Platform. SSRG International Journal of Computer Science and Engineering 5(5), 11-16.

Abstract:

 Cancer is the one of the deadliest disease that leads to the death of many people in the present decades. Earlier recognition of tumour can prevent the patient from developing the cells from benign to malignant stage which leads to cancer. computer tomography(CT) is the prevalent way to detect cancer. Our work is formulated by integrating computer and medical intelligence. A CAS accepts CT images as input and the image undergoes deep analysis. With the help of CAS, the doctor can make the decision regarding diagnosis of the cancer. This work is about stochastic recognition of a cancer by using machine learning in google cloud platform. Images incorporate a few undesirable data and some components that are imperative for processing, pre-processing is used for enhancing the image by evacuating distortion and improve vital features. To increase the quality of CT scan image, the CAS adopt Denoising, Gabor and Edge Filters in the pre-processing stage. The image acquired from the previous stage is given as an input to the model for training and automatically deduct the cancer nodule growing region and return the cancer stage of the person. The proposed approach can reduce the error rate and increase the accuracy of the system

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Key Words:

 Image Processing, Google cloud Platform, Computer aided System, Pattern Recognition.