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ABSTRACT
Medical image segmentation techniques have become a very imperative prerequisite for accuracy and easiness of diagnosis in image analysis processes. An effective and novel segmentation technique is still needed for the hour, as it is very challenging for medical practitioners to differentiate the normal and pathological brain tissues in unaided sight. To combat the above limitation, the researchers proposed a robust algorithm for the segmentation of MR brain image based on a novel combination of FCM for segmentation, GLCM for feature extraction and Jaya Algorithm (JA) for optimisation. The combination of GLCM and FCM improves the accuracy of the operation by incorporating the neighbourhood spatial characteristics. Then, the study uses the JA to find the optimal threshold value. At last, the segmented images are subjected to threshold operation using the optimal value. The ground truth images validate the effectiveness of the proposed algorithm, and it also uses the domain-specific parameters such as Peak Signal to Noise Ratio (PSNR) index, Dice Coefficient (DCI) index, Mean Squared Error (MSE) index, Jaccard-Tanimoto Coefficient (JTC) index and Hausdorff Distance (HD). The proposed algorithm delivers JTC and DCI values of 69.3% and 81.9%, respectively, the highest among the other traditional algorithms specified in this work.
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No potential conflict of interest was reported by the author(s).
Additional information
Notes on contributors
Senthilkumar Natarajan
Mr. N. Senthilkumar is a research scholar at Kalasalingam Academy of Research and Education. He is currently working on optimization techniques for medical image processing. He completed under graduation (B.E) in Electronics and Communication Engineering from V.R.S College of Engineering and Technology, affiliated to Anna University, Villupuram, India, and also pursued a Master degree in Digital Communication and Networking from Bharath Institute of Higher Education and Research, Chennai. His areas of interest are image and signal processing, optimization, and soft computing techniques.
Vishnuvarthanan Govindaraj
Dr. G. Vishnuvarthanan, born in 1986, has research stints in the avenues of medical image processing and artificial intelligence. He was awarded a Ph.D. in 2015 and bachelor’s degree in Instrumentation and Control Engineering by 2007, and a Master’s Degree in VLSI by 2009. Currently working in Kalasalingam Academy of Research and Education as Head of Department in Biomedical Engineering Department. He is highly knowledgeable in teaching and research with more than a decade of experience in teaching and research. He is a member of ISTE and has 22 SCI Journal and 30 International Publications which have been indexed in the SCOPUS database.
Ravipudi Venkata Rao Narayana
Dr. Ravipudi Venkata Rao is currently working as Professor at the Department of Mechanical Engineering Sardar Vallabhbhai National Institute of Technology (SVNIT), Surat (An Institute of National importance of Government of India), Gujarat state, India. He has nearly 30 years of teaching and research experience, having completed his B.Tech. in 1988, M.Tech. in 1991, Ph.D. in 2002, and D.Sc (Poland). in 2017. He has more than 300 research papers to his credit, published in national and international journals and conference proceedings, and has received national and international awards for his research efforts.
He also worked as a Visiting Professor at the Cracow University of Technology, Poland in January and November 2016 and at the Asian Institute of Technology, Thailand in 2008, 2010, 2015, and 2018. He reaches overall 6483 citations and h-index of 39 in Web of Science, and 17644 citations and h-index of 61 in Google Scholar.
Yu-Dong Zhang
Prof. Yu-Dong Zhangreceived his Ph.D. degree from Southeast University in 2010. He worked as a postdoc from 2010 to 2012 in Columbia University, USA, and as an assistant research scientist from 2012 to 2013 at the Research Foundation of Mental Hygiene (RFMH), USA. He served as a full professor from 2013 to 2017 in Nanjing Normal University, where he was the director and founder of the Advanced Medical Image Processing Group in NJNU. Now he serves as a Professor in the Department of Informatics, University of Leicester, UK.
He was included in “Most Cited Chinese Researchers (Computer Science)” by Elsevier from 2014 to 2018. He was the 2019 recipient of “Highly Cited Researcher” by Web of Science. He won “Emerald Citation of Excellence 2017” and “MDPI Top 10 Most Cited Papers 2015”. He was included in „Top Scientist„ in Guide2Research. He publishedover 160 papers, including 50 “ESI Highly Cited Papers”, and 3 “ESI Hot Papers”. He reaches overall 9973 citations and h-index of 55 in ISI Web of Knowledge, and 16851 citations and h-index of 72 in Google Scholar.
He is a fellow of IET (FIET), the senior member of IEEE, and ACM Senior member. He is the editor of Scientific Reports, IEEE Transactions on Circuits and Systems for Video Technology, etc. He served as the (leading) guest editor of Information Fusion, Neural Networks, IEEE Transactions on Intelligent Transportation Systems, etc. He has conducted many successful industrial projects and academic grants from NSFC, NIH, Royal Society, and British Council.
Pallikonda Rajasekaran Murugan
Dr. Pallikonda Rajasekaran Murugan is working as a professor at Kalasalingam Academy of Research and Education since 2012. He graduated in Electronics and Instrumentation in 2001 from Shanmuga College of Engineering, Thanjavur, and received his M.Tech at SASTRA University in 2002. He received a Ph.D. Degree from, Anna University, Chennai, India. He has rich experience in the field of bioimage and signal processing. Under his guidance, more than 8 scholars completed their doctorates across various fields like Image Processing, Biomedical Instrumentation, and Wireless Sensor Networks. He has a strong track record of publications with more than 89 papers published in various journals and conferences. He holds membership in various technical bodies like ISTE, IEEE, IE, APCBEES, IAENG, and IACSIT.
Karunanithi Kandasamy
Dr. Karunanithi Kandasamy is currently working as a Professor in the Department of Electrical and Electronics Engineering, Vel Tech Rangarajan Dr. Sagunthala R and D Institute of Science and Technology, Avadi, India. He received his B.E. degree from the Institution of Engineers (India), Kolkata, and M.E. degree (with Distinction) from Anna University, Tirunelveli, India. He is awarded a doctoral degree from Kalasalingam University, Krishnankoil, and Tamilnadu, India. He is an Associate Member of The Institution of Engineers (India) (AMIE). He has published many dissertations in International Conferences and Journals in his research field. His research area of interest is in Power System Planning and Power Systems.
Khurram Ejaz
Dr. Khurram Ejaz did his Ph.D. in 2021 from University Technology Malaysia (UTM) Malaysia (University QS rank is 187, Faculty QS rank is 100). He did his Master of Sciences (MSCS) in computer science from University Central Punjab (UCP), Lahore Pakistan in 2010. He had served as a lecturer at Federal Urdu University of Arts Science and Technology (FUUAST) Islamabad Pakistan from 2008 to 2010. He is also a member of virtual reality lab (Vicube lab) in UTM. He is the author of various index articles (Impact factor and Scopus). His research interests are in Pattern Recognition and Computer Vision.