EWPCO-enabled Shepard convolutional neural network for classification of brain tumour using MRI image

ABSTRACT

Numerous imaging techniques, like X-rays, Computerized Tomography (CT) scans, and ultrasound are utilized to predict brain tumours, but these imaging techniques experience difficulties in generating accurate results. To overcome such limitations, an effectual approach for the classification of brain cancer utilizing the proposed Exponentially Weighted Pelican Chimp Optimization-based Shepard Convolutional Neural Network (EWPCO-ShCNN) is introduced. At first, preprocessing is carried out employing a median filter, and Region of Interest (RoI) extraction and segmentation are performed utilizing a Pyramid Scene Parsing Network (PSP-Net), which is trained by Pelican Chimp Optimization (PCO) algorithm. After that, data augmentation and feature extraction are performed for more processing. Thereafter, the categorization is executed by ShCNN, which is instructed by the proposed Exponential Weighted Pelican Chimp Optimization (EWPCO) algorithm. Furthermore, the proposed EWPCO-ShCNN has attained better sensitivity of 95.90%, accuracy of 94.90% and specificity of 95.60% respectively.

KEYWORDS:

• Magnetic resonance imaging (MRI)
• Pelican Optimization Algorithm (POA)
• Chimp Optimization Algorithm (ChOA)
• deep learning (DL)
• Exponential Weighted Pelican Chimp Optimization (EWPCO)
• Region of Interest (RoI)
• Computerized Tomography (CT)
• Pyramid Scene Parsing Network (PSP-Net)

Additional information

Notes on contributors

K. Mohana Sundaram

K. Mohana Sundaram working as Assistant Professor in the Department of Computer Science and Engineering, R.M.D. Engineering College, Kavaraipettai, Tamil Nadu. He has completed his B.E Computer Science and Engineering Degree at K.S.R. College of Technology, Tiruchengodu and M.E Computer Science and Engineering Degree at Sathyabama University (Sathyabama Institute of Science and Technology), Chennai. He has been in the teaching profession for the past 19 years and has handled both UG and PG programmes. He has attended many workshops related to his area of interest. He has published 4 papers in various International / National Journals and Conferences. He has organized various Seminars, Guest lectures and FDPs. His current research interests are in the areas of Artificial Intelligence and Cloud Computing. He is a Member of various professional societies ACM, IAENG, CSI and ISTE.

R. Sasikumar

Dr. R. Sasikumar is a Professor in the Department of Computer Science and Engineering, R.M.D. Engineering College, Kavaraipettai, Tamil Nadu. He has completed his B.E Computer Science and Engineering Degree at Kongu Engineering College, Perunduari, Erode and M.E Computer Science and Engineering Degree at Annamalai University, Chidambaram. He obtained his Doctorate in the area of “Network Security” and is awarded Ph.D Degree by Anna University Chennai. He has been in the teaching profession for the past 24.04 years and has handled both UG and PG programmes. He has attended many workshops related to his area of interest. He has published 35 papers in various highly cited International / National journals and conferences including WOS and Scopus Indexed Journals. He has organized various seminars, Guest lectures and conference. He acted as a Session Chair and Advisory Board Member in many Conferences. His current research interests are in the areas of Wireless Networks and Cloud Computing. He is a life member of various professional societies ACM, IAENG, CSTA, IACSIT and SIAM.