Detection of Pancreatic Tumor using Particle Swarm Optimization based Image Enhancement

Abstract

Pancreatic cancer is one of the most lethal cancers, with a five-year survival rate of about 9% for all stages. Pancreatic cancer may be difficult to detect and is usually only discovered when the disease has progressed to an advanced stage. Medical imaging provides key data for diagnosing patients, analysing diseases, developing and monitoring new medications further enhancing human health care through the use of various complimentary imaging modalities. Nature inspired optimization techniques play an essential role in the field of medical imaging. This paper presents an approach to visually enhance the pancreatic cancer CT scans using particle swarm optimization and filtering techniques. The algorithm has been tested on 3D CT scans of pancreatic cancer and evaluated on validation parameter-Entropy, which gives improved results.