A Brain Tumor Detection by Using the Lee Sigma Filter Model and Deep Image Prior Techniques Pavithra M.1, Sheeba J.I.2,*, Devaneyan S. Pradeep3 1M.Tech Student, Department of Computer Science and Engineering, Puducherry Technological University, Puducherry-605014, India 2Associate Professor, Department of Computer Science and Engineering, Puducherry Technological University, Puducherry-605014, India 3Professor, Department of Mechanical Engineering, Sri Venkateshwaraa College of Engineering and Technology, Puducherry-605102, India *Corresponding author email id: sheeba@ptuniv.edu.in
Online Published on 27 March, 2024. Abstract A brain tumor is a disease brought on by the development of irregular cells in the head. The endurance rate of patients with brain tumors is often exaggerated. Brain tumors can be predicted by Magnetic Resonance Imaging (MRI) images, which play a significant role in the medical field. The Computer-Aided Diagnosis (CAD) system has various issues, such as the inability to accurately detect diseases in MRI images. In the existing system, the Deep Convolutional Neural Network (DCNN) architecture with three types of pre-processing steps is used to improve the value of the MRI scan images. In the proposed system, the Deep Image Prior technique will be used to denoise the MRI images, the Lee Sigma Filter Model will be used to enhance the contrast of the MRI image, and the Recurrent Convolutional Neural Network Model will improve accuracy. Top Keywords Deep convolutional neural network, Brain tumor, Deep image prior, Lee sigma filter model, Recurrent convolutional neural network. Top |