Biomedical Image Compression Techniques for Clinical Image Processing

Authors

  • Abdul Khader Jilani Saudagar Imam Mohammad Ibn Saud Islamic University

DOI:

https://doi.org/10.3991/ijoe.v16i12.17019

Keywords:

accuracy, fuzzy logic, image compression, neural networks, telemedicine

Abstract


Image processing is widely used in the domain of biomedical engineering especially for compression of clinical images. Clinical diagnosis receives high importance which involves handling patient’s data more accurately and wisely when treating patients remotely. Many researchers proposed different methods for compression of medical images using Artificial Intelligence techniques. Developing efficient automated systems for compression of medical images in telemedicine is the focal point in this paper. Three major approaches were proposed here for medical image compression. They are image compression using neural network, fuzzy logic and neuro-fuzzy logic to preserve higher spectral representation to maintain finer edge information’s, and relational coding for inter band coefficients to achieve high compressions. The developed image coding model is evaluated over various quality factors. From the simulation results it is observed that the proposed image coding system can achieve efficient compression performance compared with existing block coding and JPEG coding approaches, even under resource constraint environments.

Author Biography

Abdul Khader Jilani Saudagar, Imam Mohammad Ibn Saud Islamic University

Abdul Khader Jilani Saudagar   received his Bachelor of Engineering B.E, Master of Technology M.Tech and Doctor of Philosophy PhD in Computer Science & Engineering in 2001, 2006 and 2010 respectively. His areas of interests are: Artificial Image Processing, Information Technology, Databases, Web and Mobile Application Development. He has 10 years of research and teaching experience at both undergraduate (UG) and postgraduate (PG) level. Presently working as Associate Professor in Information Systems Department, College of Computer & Information Sciences (CCIS), Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, Kingdom of Saudi Arabia. He is also the Head of Intelligent Interactive Systems Research Group (IISRG) at CCIS. He was the principal investigator of the funded projects from KACST, Deanship of Scientific Research (IMSIU) and Research Development Office (RDO) Ministry of Education, Kingdom of Saudi Arabia. Dr. Saudagar has published a number of research papers in International Journals and Conferences. He is associated as member with various professional bodies like ACM, IACSIT, IAENG, ISTE etc., and working as Editorial Board member, Reviewer for many international Journals.

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Published

2020-10-19

How to Cite

Saudagar, A. K. J. (2020). Biomedical Image Compression Techniques for Clinical Image Processing. International Journal of Online and Biomedical Engineering (iJOE), 16(12), pp. 133–154. https://doi.org/10.3991/ijoe.v16i12.17019

Issue

Vol. 16 No. 12 (2020)

Section

Papers

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