An enhanced deep learning approach for brain cancer MRI images classification using residual networks

SAA Ismael, A Mohammed, H Hefny - Artificial intelligence in medicine, 2020 - Elsevier
Cancer is the second leading cause of death after cardiovascular diseases. Out of all types
of cancer, brain cancer has the lowest survival rate. Brain tumors can have different types …

Early diagnosis of brain tumour mri images using hybrid techniques between deep and machine learning

EM Senan, ME Jadhav, TH Rassem… - … Methods in Medicine, 2022 - Wiley Online Library
Cancer is considered one of the most aggressive and destructive diseases that shortens the
average lives of patients. Misdiagnosed brain tumours lead to false medical intervention …

Brain tumor classification via statistical features and back-propagation neural network

MR Ismael, I Abdel-Qader - 2018 IEEE international conference …, 2018 - ieeexplore.ieee.org
Classification of brain tumor is the heart of the computer-aided diagnosis (CAD) system
designed to aid the radiologist in the diagnosis of such tumors using Magnetic Resonance …

Machine learning assisted methodology for multiclass classification of malignant brain tumors

A Vidyarthi, R Agarwal, D Gupta, R Sharma… - IEEE …, 2022 - ieeexplore.ieee.org
Analysis of malignant and non-malignant brain tumors is done using a computer-aided
diagnosis system by practitioners worldwide. Radiologists refer computer-assisted …

Detecting brain tumors using deep learning convolutional neural network with transfer learning approach

S Anjum, L Hussain, M Ali, MH Alkinani… - … Journal of Imaging …, 2022 - Wiley Online Library
Accurate classification of brain tumor subtypes is important for prognosis and treatment. In
this study, we optimized and applied non‐deep learning methods based on hand‐crafted …

A review on feature extraction techniques for tumor detection and classification from brain MRI

AR Matthew, A Prasad, PB Anto - … International Conference on …, 2017 - ieeexplore.ieee.org
In medical fields, the detection of brain abnormalities is a very important and crucial task.
Medical image processing provides basic information of abnormality of brain and it helps the …

[HTML][HTML] Automatic detection of brain tumors with the aid of ensemble deep learning architectures and class activation map indicators by employing magnetic …

O Turk, D Ozhan, E Acar, TC Akinci, M Yilmaz - Zeitschrift für Medizinische …, 2022 - Elsevier
Today, as in every life-threatening disease, early diagnosis of brain tumors plays a life-
saving role. The brain tumor is formed by the transformation of brain cells from their normal …

Deep learning hybrid techniques for brain tumor segmentation

K Munir, F Frezza, A Rizzi - Sensors, 2022 - mdpi.com
Medical images play an important role in medical diagnosis and treatment. Oncologists
analyze images to determine the different characteristics of deadly diseases, plan the …

Bayesian dynamic profiling and optimization of important ranked energy from gray level co-occurrence (GLCM) features for empirical analysis of brain MRI

L Hussain, AA Malibari, JS Alzahrani, M Alamgeer… - Scientific Reports, 2022 - nature.com
Accurate classification of brain tumor subtypes is important for prognosis and treatment.
Researchers are developing tools based on static and dynamic feature extraction and …

Brain tumor segmentation and classification using DWT, Gabour wavelet and GLCM

AR Mathew, PB Anto, NK Thara - … International Conference on …, 2017 - ieeexplore.ieee.org
The brain is the central control unit of human body. Tumor affects the brain means it causes
the death of the patient if it is not diagnosed in the early stage. Among the different available …