Brain tumor detection and classification using deep learning techniques based on MRI images

B Kokila, MS Devadharshini, A Anitha… - Journal of Physics …, 2021 - iopscience.iop.org
The application of deep learning approaches in context to improve health diagnosis is
providing impactful solutions. According to the World Health Organization (WHO), proper …

Computational Intelligence Approach to improve the Classification Accuracy of Brain Tumour Detection

P Sarkar, D Srivastava - 2022 2nd International Conference on …, 2022 - ieeexplore.ieee.org
A brain tumour is one of the most severe illnesses that can strike both children and
teenagers. 85–90 per cent of all primary Central Nervous System (CNS) malignancies are …

[HTML][HTML] Design and development of modified ensemble learning with weighted RBM features for enhanced multi-disease prediction model

AS Prakaash, K Sivakumar, B Surendiran… - New Generation …, 2022 - Springer
In this computer world, huge data are generated in several fields. Statistics in the healthcare
engineering provides data about many diseases and corresponding patient's information …

Computational Intelligence Approach to Improve The Classification Accuracy of Brain Tumor Detection

SK UmaMaheswaran, S Deivasigamani… - … on System Modeling …, 2022 - ieeexplore.ieee.org
One of its most serious diseases that may affect kids and teens is a cancerous tumor.
Gliomas account for 85% to 90% of all recurrent System (CNS) cancers. An estimated …

Multi‐scaled feature fusion enabled convolutional neural network for predicting fibrous dysplasia bone disorder

S Arirangan, K Kottursamy - Expert Systems, 2023 - Wiley Online Library
Abstract Background Convolutional Neural Network (CNN) has exciting advantages in the
processing of medical images. It produces the denoised and segmented results of images …

Enhancing Brain Tumor Detection Classification Accuracy with Computational Intelligence

K Parashar - 2023 3rd International Conference on Advance …, 2023 - ieeexplore.ieee.org
A brain tumour is one of the most dangerous conditions that may afflict children and young
adults. 90% to 92% of the all the primary leukaemias of the nervous system's are caused by …

Evolutionary gravitational neocognitron neural network optimized with marine predators optimization algorithm for MRI brain tumor classification

A Lakshmi, M Alagarsamy… - … Biology and Medicine, 2024 - Taylor & Francis
Magnetic resonance imaging (MRI) is a powerful tool for tumor diagnosis in human brain.
Here, the MRI images are considered to detect the brain tumor and classify the regions as …

An effective transfer learning model for multiclass brain tumor classification using MRI images

J Rubia, B Lincy, P Sheeba, S Shibi - AIP Conference Proceedings, 2023 - pubs.aip.org
The brain tumor is a life-threatening disease which is caused by the uncontrolled spread of
cancerous cells. The diagnosis of this disease is a challenging task due to the variability and …

Computational Intelligence approach to improve the Classification accuracy of Brain Tumor Detection

AK Bhagat, D Vekariya - 2022 5th International Conference on …, 2022 - ieeexplore.ieee.org
One of the most dangerous diseases is a brain tumor that may affect children as well as
adults both. Brain tumors are responsible for 80-90 percent of all primary Central Nervous …

[PDF][PDF] Brain Tumor Classification Using Machine Learning and Deep Learning Algorithms

SR Sowrirajan, S Balasubramanian - IJEER, 2022 - academia.edu
░ ABSTRACT-Early identification and diagnosis of brain tumors have been a difficult
problem. Many approaches have been proposed using machine learning techniques and a …