Int. J. Medical Engineering and Informatics, Vol. 10, No. 1, 2018 49 Copyright © 2018 Inderscience Enterprises Ltd. Analysis of polycystic kidney disease in medical ultrasound images Prema T. Akkasaligar and Sunanda Biradar* Department of Computer Science and Engineering, BLDEA’s V.P. Dr. P.G.H College of Engineering and Technology, Vijayapur-586103, India Email: premasb@rediffmail.com Email: sunanda_biradar@rediffmail.com *Corresponding author Abstract: The growth of kidney diseases has gradually increased in recent years. Ultrasound imaging provides the internal structure of the body to detect eventually diseases or abnormal tissues non-invasively. Segmentation of required region in ultrasound images is one of the challenging tasks. The proposed method focuses on classification of medical ultrasound images of kidney as cystic and polycystic types. Segmentation is performed using gradient vector force (GVF) snakes. Before segmentation, speckle noise is removed using Gaussian filter and contrast is enhanced. We have segmented normal, cystic and polycystic kidney ultrasound images effectively using GVF snakes. We have also carried out segmentation using morphological operations which requires a user intervention during the process of segmentation. Geometrical features are used with k- NN for classifying medical US images of kidney as normal, single cystic and polycystic types for segmented regions .The proposed method has applications in analysis of organ morphology and realising quantitative measurements. Keywords: GVF snakes; morphological operations; medical ultrasound image of kidney; polycystic kidney disease; PCKD. Reference to this paper should be made as follows: Akkasaligar, P.T. and Biradar, S. (2018) ‘Analysis of polycystic kidney disease in medical ultrasound images’, Int. J. Medical Engineering and Informatics, Vol. 10, No. 1, pp.49–64. Biographical notes: Prema T. Akkasaligar is working as a Professor in Department of Computer Science and Engineering of BLDEA’s V.P. Dr. P.G.H. College of Engineering and Technology, Vijayapur, Karnataka, India. She completed her PhD from Gulbarga University, Gulbarga in 2013, ME (CSE) from Gulbarga Universuty, Gulbarga in 1999. She published three book chapters, 15 international journals, 13 international conference papers and three national conference papers. She is a life member of Computer Society of India (CSI), Indian Society for Technical Education (ISTE), The Institution of Engineers, India (IEI) and International Association of Computer Science and Information Technology (IACSIT), Singapore. Her areas of interest are medical image processing and computer vision. Sunanda Biradar is a Research Scholar and working as an Assistant Professor in Department of Computer Science and Engineering of BLDEA’s V.P. Dr. P.G.H. College of Engineering and Technology, Vijayapur, Karnataka, India. She has completed her MTech (CSE) from Visvesvaraya Technological University, Belagavi, Karnataka, India in 2009. Her areas of interest are medical image processing and pattern recognition.