Big Data Analytics for Medical Image Analysis in Screening and Detection of Pancreatic Tumor
7 Pages Posted: 12 Jun 2019
Date Written: February 22, 2019
Abstract
Analysis and Prediction are the two focal objectives taken into deliberation for diagnosis of tumor. The existence of tumor in patients is subjected to early diagnosis either in Stage I or Stage II. If the tumor is identified in Stage III or advanced stages, the probability of existence of the patient is very less. Moreover the tumor may be predicted in early stages will enhance the analysis, diagnosis and prognosis, which leads to appropriate medication. Presently this work focuses on image feature analysis of medical Magnetic Resonance Imaging (MRI) scan and formation of data base to identify the pancreatic tumors at an initial stage. A data set for MRI scan images for pancreas with medical diagnosis is determined. A distinct diagnosis method is proposed for identification of pancreatic tumors using image texture characters, which were statistically evaluated using MATLAB. Diagnosis is done using Recurrent Neural Networks (RNNs) and the results are compared with the values obtained from images which are kept for testing and validation by repeated matching based on the query image. Discussions are made here with future innovation and scope in medical digital image diagnosis.
Keywords: Pancreatic Cancer, Image Retrieval, Big Data, Recurrent Neural Networks, MRI Scan Images
Suggested Citation: Suggested Citation