An Improved K-Means Clustering for Segmentation of Pancreatic Tumor from CT Images

Abstract

Pancreatic tumor is a deadly disease in which cancerous (malignant) cells form in the tissues of the pancreas. There are numerous types of pancreatic cancers, the most common is pancreatic adenocarcinoma. Almost 90% cases suffer from pancreatic adenocarcinoma. However detecting lesions from medical images is very challenging, given that the shape of the pancreas in abdomen is very irregular, low contrast in edges, variability in location which requires more complex and accurate segmentation of boundary of pancreas from abdomen images. In computer-aided diagnosis system, automatic segmentation of a specific organ and its tumor is very important. The proposed framework provides a way to apply K-means clustering method (unsupervised learning algorithm) on pancreas CT image to detect the area of interest from the background. Our aim is to build an efficient framework to segment tumors from pancreas CT images which is most commonly used in the domain of medical imaging as well as help clinicians in better decision making for surgical planning. It is observed from the results that K-means clustering segmentation algorithm produces more accuracy on CT imaging datasets. Early detection of pancreatic adenocarcinoma helps in immediate treatment planning for individuals.

KEYWORDS:

• Computer-aided diagnosis
• CT images
• K-means clustering
• Pancreatic adenocarcinoma
• Segmentation

Additional information

Notes on contributors

R. Reena Roy

R Reena Roy received her BTech degree from Anna University in 2012, ME degree from Anna University in 2014. Currently, she is working as an assistant professor in the Department of Information Technology in Easwari Engineering College, Chennai, India. She has 6 years of teaching experience. She published various research papers in various international journals/conferences. Her research area of interest is data mining, artificial intelligence and image processing.

G. S. Anandha Mala

G S Anandha Mala received BE degree from Bharathidhasan University in 1992, ME degree from University of Madras in 2001 and PhD degree from Anna University in 2007. Currently, she is working as a professor in Easwari Engineering College, Chennai, India. She has published more than 100 technical papers in various international journal/conferences. She has 26 years of teaching experience on both graduate and post graduate levels. She is a recognized supervisor of Anna University, Sathyabama University, Jawaharlal Technological University. She has completed 12 PhD works under Anna University and Jawaharlal Nehru Technological University. She has received a research grant of 20 lakhs from DST under device development programme. She has received “IET CLN Exemplary Teacher Award” by IET and “Distinguished Women Administrator Award” by VIWA. Her area of interest includes natural language processing and image processing. Email: [email protected]