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Article type: Research Article
Authors: Javeed, M.D.a | Nagaraju, Regondab | Chandrasekaran, Rajac | Rajulu, Govindad | Tumuluru, Praveene | Ramesh, M.f | Suman, Sanjay Kumarg; * | Shrivastava, Rajeevh
Affiliations: [a] Department of od ECE and Director, IQAC, Princeton Institute of Engineering and Technology for Women, Hyderabad, Telangana, India | [b] Department of CSE – AI&ML, School of Engineering, Mallareddy University, Hyderabad, Telangana, India | [c] Department of ECE, Vel Tech Rangarajan Dr. Sagunthala R & D Institute of Science and Technology, Chennai, Tamil Nadu, India | [d] Department of Computer Science and Design, St Martins Engineering college, Secundrabad, Telangana, India | [e] Department of CSE, Koneru Lakshmaiah Education Foundation, Vaddeswaram, AP, India | [f] Department of CSE, National Institute of Technology, Goa, India | [g] Department of ECE, and Dean R&D, St. Martin’s Engineering College Secunderabad Telangana, India | [h] Princeton Institute of Engineering and Technology for Women, Hyderabad, Telangana, India
Correspondence: [*] Corresponding author. Sanjay Kumar Suman, Professor, Department of ECE, and Dean R&D, St. Martin’s Engineering College Secunderabad Telangana India. Tel.: +919652141557; E-mail: javeed.rahmanee@gmail.com.
Abstract: The process of partitioning into different objects of an image is segmentation. In different major fields like face tracking, Satellite, Object Identification, Remote Sensing and majorly in medical field segmentation process is very important to find the different objects in the image. To investigate the functions and processes of human boy in radiology magnetic resonance imaging (MRI) will be used. MRI technique is using in many hospitals for the diagnosis purpose widely in finding the stage of a particular disease. In this paper, we proposed a new method for detecting the tumor with enhanced performance over traditional techniques such as K-Means Clustering, fuzzy c means (FCM). Different research methods have been proposed by researchers to detect the tumor in brain. To classify normal and abnormal form of brain, a system for screening is discussed in this paper which is developed with a framework of artificial intelligence with deep learning probabilistic neural networks by focusing on hybrid clustering for segmentation on brain image and crystal contrast enhancement. Feature’s extraction and classification are included in the developing process. Performance in Simulation of proposed design has shown the superior results than the traditional methods.
Keywords: Segmentation, brain tumor, probabilistic neural networks, feature extraction, classification
DOI: 10.3233/JIFS-232493
Journal: Journal of Intelligent & Fuzzy Systems, vol. 45, no. 4, pp. 6485-6500, 2023
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