Detection of Human Pancreatic Cancer using ML and DL Model: A State-of-the-Art Review

Pancreatic cancer is a highly dangerous cancer with a poor prognosis. In radiological imaging, computer-aided pancreatic tumor image segmentation is commonly employed by CAD, diagnosis, and quantitative evaluations such as CT and MRI. Over the years, pancreatic cancer rates in India have been increasing, with 100,000 new cases reported annually. The survival rate for patients with pancreatic cancer can be increased with early detection, effective treatment, and medical care delivery. Various imaging methods are used for detection of pancreatic cancer, and radiologists can utilize computer-aided diagnostic techniques to detect and diagnose abnormalities earlier and more rapidly. Before recommending a biopsy test, the radiologist consults with a computer-aided diagnostic. Several Computer-Aided Diagnosis (CAD) methods have been developed for the early detection of pancreatic cancer using mammography images, with most CAD systems focusing on identifying and detecting nodules. Since treatment for pancreatic cancer is based on the stage of cancer, staging pancreatic cancer at detection is critical. Therefore, this study focuses on evaluating CAD methods for segmenting nodules and identifying various stages of cancer to aid radiologists in assessing the disease.