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High-grade glioma treatment response monitoring biomarkers: a position statement on the evidence supporting the use of advanced MRI techniques in the clinic, and …
Objective Summarize evidence for use of advanced MRI techniques as monitoring
biomarkers in the clinic, and highlight the latest bench-to-bedside developments. Methods …
biomarkers in the clinic, and highlight the latest bench-to-bedside developments. Methods …
Deep learning techniques for the classification of brain tumor: A comprehensive survey
Researchers have given immense consideration to unsupervised approaches because of
their tendency for automatic feature generation and excellent performance with a reduced …
their tendency for automatic feature generation and excellent performance with a reduced …
[HTML][HTML] A survey of brain tumor segmentation and classification algorithms
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 …
slices across the 3D anatomical view. Therefore, manual segmentation of brain tumors from …
Brain tumor segmentation and classification with hybrid clustering, probabilistic neural networks
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 …
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 …
because of their lower pixel intensity. Modern medical platforms require a fully automated …
[HTML][HTML] A hybrid learning-architecture for improved brain tumor recognition
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 …
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
Objective To determine the feasibility and biologic correlations of dynamic susceptibility
contrast (DSC), dynamic contrast enhanced (DCE), and quantitative maps derived from …
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 …
Objectives Glioblastoma multiforme (GBM), the most aggressive glial brain tumors, can
metabolize glucose through glycolysis and mitochondrial oxidation pathways. While specific …
metabolize glucose through glycolysis and mitochondrial oxidation pathways. While specific …
Advancements in neuroimaging to unravel biological and molecular features of brain tumors
Simple Summary Advanced neuroimaging is gaining increasing relevance for the
characterization and the molecular profiling of brain tumor tissue. On one hand, for some …
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
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 …
brain tumors. Many brain tumors go undiagnosed or are overlooked by clinicians as a result …