Deep learning techniques for the classification of brain tumor: A comprehensive survey

A Younis, Q Li, M Khalid, B Clemence… - IEEE Access, 2023‏ - ieeexplore.ieee.org
Researchers have given immense consideration to unsupervised approaches because of
their tendency for automatic feature generation and excellent performance with a reduced …

[HTML][HTML] A survey of brain tumor segmentation and classification algorithms

ES Biratu, F Schwenker, YM Ayano, TG Debelee - Journal of Imaging, 2021‏ - mdpi.com
A brain Magnetic resonance imaging (MRI) scan of a single individual consists of several
slices across the 3D anatomical view. Therefore, manual segmentation of brain tumors from …

Brain tumor segmentation and classification with hybrid clustering, probabilistic neural networks

MD Javeed, R Nagaraju… - Journal of Intelligent …, 2023‏ - content.iospress.com
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 …

Meningioma brain tumor detection and classification using hybrid CNN method and RIDGELET transform

BV Prakash, AR Kannan, N Santhiyakumari… - Scientific Reports, 2023‏ - nature.com
The detection of meningioma tumors is the most crucial task compared with other tumors
because of their lower pixel intensity. Modern medical platforms require a fully automated …

[HTML][HTML] A hybrid learning-architecture for improved brain tumor recognition

J Dixon, O Akinniyi, A Abdelhamid, GA Saleh… - Algorithms, 2024‏ - mdpi.com
The accurate classification of brain tumors is an important step for early intervention. Artificial
intelligence (AI)-based diagnostic systems have been utilized in recent years to help …

Simultaneous quantification of perfusion, permeability, and leakage effects in brain gliomas using dynamic spin-and-gradient-echo echoplanar imaging MRI

F Sanvito, C Raymond, NS Cho, J Yao, A Hagiwara… - European …, 2024‏ - Springer
Objective To determine the feasibility and biologic correlations of dynamic susceptibility
contrast (DSC), dynamic contrast enhanced (DCE), and quantitative maps derived from …

[HTML][HTML] Glucose fluxes in glycolytic and oxidative pathways detected in vivo by deuterium magnetic resonance spectroscopy reflect proliferation in mouse …

RV Simões, RN Henriques, BM Cardoso… - NeuroImage: Clinical, 2022‏ - Elsevier
Objectives Glioblastoma multiforme (GBM), the most aggressive glial brain tumors, can
metabolize glucose through glycolysis and mitochondrial oxidation pathways. While specific …

Advancements in neuroimaging to unravel biological and molecular features of brain tumors

F Sanvito, A Castellano, A Falini - Cancers, 2021‏ - mdpi.com
Simple Summary Advanced neuroimaging is gaining increasing relevance for the
characterization and the molecular profiling of brain tumor tissue. On one hand, for some …

A computer-aided diagnosis system for brain tumors based on artificial intelligence algorithms

T Chen, L Hu, Q Lu, F **ao, H Xu, H Li… - Frontiers in Neuroscience, 2023‏ - frontiersin.org
The choice of treatment and prognosis evaluation depend on the accurate early diagnosis of
brain tumors. Many brain tumors go undiagnosed or are overlooked by clinicians as a result …