Vol. 5 No. 3 (2021)
Articles

Detection of Pancreatic Cancer using Faster Region Convolution Neural Network

Published 2021-12-30

Abstract

Pancreatic cancer is one of the most common malignant tumors of the digestive system. According to WHO more than 2 lakh people die annually because of pancreatic cancer. The highest incidence and mortality rates of pancreatic cancer are found in developed countries. Pancreatic cancer is a highly lethal disease, for which mortality closely parallels incidence. Most patients with pancreatic cancer remain asymptomatic until the disease reaches an advanced stage. There is no standard program for screening patients at high risk of pancreatic cancer (example, those with a family history of pancreatic cancer and chronic pancreatitis).  A known cause of pancreatic cancer is tobacco smoking. This risk factor is likely to explain some of the international variations and gender differences. One of the most affected cancer that predicted to be incurable are Pancreatic Cancer, which cannot be treated efficiently once identified, in most of the cases it found to be unpredictable as it lies in the abdomen region below the stomach. Therefore, the advancements in the medical research are trending towards the implementations of an automated systems which identifies the stages of cancer if affected and provide the better diagnosis and treatment if identified. Deep learning is one such area which extended its research towards medical imaging, which automates the process of diagnosing the problems of the patients when appended with the set of machines like CT/PET Scan systems. This study was performed to predict the affected areas in pancreas by deep learning techniques like CNN, allowing this system to read CT images correctly and make diagnosis of pancreatic cancer faster using faster region-based convolution network (Faster R-CNN) model with less outliers.