A novel resolution independent gradient edge predictor for lossless compression of medical image sequences

ABSTRACT

Digital visualization of human body in terms of medical images with high resolution and bit depth generates tremendous amount of data. In the field of medical diagnosis, lossless compression technique is preferred that facilitates efficient archiving and transmission of medical images avoiding false diagnosis. Among various approaches to lossless compression of medical images, predictive coding techniques have high coding efficiency and low complexity. Gradient Edge Detector (GED) used in predictive coding is based on threshold value for prediction and choice of threshold is very important for efficient prediction. However, no specific method is adopted in the literature for threshold value selection. This paper presents an efficient prediction solution targeted at lossless compression of 8 bits and higher bit depth volumetric medical images up to 16 bits. Novelty of the proposed technique is developing Resolution Independent Gradient Edge Predictor (RIGED) algorithm to support 8- and 16-bit depth medical images. Percentage improvement of the proposed model is 30.39% over state-of-the-art Median Edge Detector (MED) and 0.92% over Gradient Adaptive Predictor (GAP) in terms of entropy for medical image dataset of different modalities having different resolutions and bit depths.

KEYWORDS:

• Lossless compression
• predictive coding
• predictor
• resolution independent gradient edge detection

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Notes on contributors

Urvashi Sharma

Urvashi Sharma is a Research Scholar and Teaching Assistant in the Department of Electronics and Communication Engineering at Jaypee University of Information Technology, Waknaghat, Distt. Solan, HP, India. She received her B.Tech. degree from the HPTU India in the year 2015. She received M.Tech. degree from Jaypee University of Information Technology, Waknaghat, HP, India in the year of 2017. Her research interests include Biomedical Image Processing.

Meenakshi Sood

Meenakshi Sood is Senior Assistant Professor in the Department of Electronics and Communication Engineering at Jaypee University of Information Technology, Waknaghat, HP, India and received her Ph.D. in Biomedical Signal Processing. She is Gold Medalist and has been awarded Academic Award for her performance in Master of Engineering (Hons.) from Panjab Univeristy, Chandigarh. Her research areas and interests are Image and Signal processing, Antenna Design, Meta-materials and Soft Computing. She has published more than 25 papers in reputed journals and 30 papers in International conferences. She is a senior member of IEEE and giving her continuous guidance and efforts as Department Coordinator at JUIT. She has published course material of “Digital Electronics and Microprocessors” for ICDOEL, HP University. She has been selected as a GSE member of Rotary International and visited the USA in Exchange Program.

Emjee Puthooran

Dr Emjee Puthooran is an Assistant Professor in the Department of Electronics and Communication Engineering at Jaypee University of Information Technology, Waknaghat, HP, India. He received his B.Tech. from the University of Calicut in the year 2000. He received M.Tech. and Ph.D. from Indian Institute of Technology, Roorkee. He worked as a research fellow at C-DAC (Erstwhile ER & DCI), Trivandrum, from 2002 to 2004 and at IIT Roorkee from 2006 to 2007. From 2013 to 2017 he worked as an Assistant Professor at the National Institute of Technology, Jalandhar. He is a life member of the Biomedical Engineering Society of India. His research interests include Biomedical Image Processing, Digital Signal Processing and Soft Computing Techniques.