AIMC Topic: Glioma

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Impaired phase synchronization of motor-evoked potentials reflects the degree of motor dysfunction in the lesioned human brain.

Human brain mapping Feb 24, 2022
The functional corticospinal integrity (CSI) can be indexed by motor-evoked potentials (MEP) following transcranial magnetic stimulation of the motor cortex. Glial brain tumors in motor-eloquent areas are frequently disturbing CSI resulting in differ...
Anticonvulsants Brain Neoplasms Evoked Potentials, Motor Motor Cortex Transcranial Magnetic Stimulation Glioma Humans Brain
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A multi-modal fusion framework based on multi-task correlation learning for cancer prognosis prediction.

Artificial intelligence in medicine Feb 24, 2022
Morphological attributes from histopathological images and molecular profiles from genomic data are important information to drive diagnosis, prognosis, and therapy of cancers. By integrating these heterogeneous but complementary data, many multi-mod...
Prognosis Genomics Humans Glioma Neural Networks, Computer
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Application of Deep Learning Technology in Glioma.

Journal of healthcare engineering Feb 18, 2022
A common and most basic brain tumor is glioma that is exceptionally dangerous to health of various patients. A glioma segmentation, which is primarily magnetic resonance imaging (MRI) oriented, is considered as one of common tools developed for docto...
Technology Brain Neoplasms Humans Neural Networks, Computer Glioma Magnetic Resonance Imaging Deep Learning Image Processing, Computer-Assisted
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Segmenting pediatric optic pathway gliomas from MRI using deep learning.

Computers in biology and medicine Jan 17, 2022
Optic pathway gliomas are low-grade neoplastic lesions that account for approximately 3-5% of brain tumors in children. Assessing tumor burden from magnetic resonance imaging (MRI) plays a central role in its efficient management, yet it is a challen...
Humans Image Processing, Computer-Assisted Deep Learning Glioma Magnetic Resonance Imaging Child Reproducibility of Results Brain Neoplasms
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Grade classification of human glioma using a convolutional neural network based on mid-infrared spectroscopy mapping.

Journal of biophotonics Jan 10, 2022
This study proposes a convolutional neural network (CNN)-based computer-aided diagnosis (CAD) system for the grade classification of human glioma by using mid-infrared (MIR) spectroscopic mappings. Through data augmentation of pixels recombination, t...
Microscopy Fourier Analysis Humans Diagnosis, Computer-Assisted Neural Networks, Computer Glioma
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Molecular Biology in Treatment Decision Processes-Neuro-Oncology Edition.

International journal of molecular sciences Dec 10, 2021
Computational approaches including machine learning, deep learning, and artificial intelligence are growing in importance in all medical specialties as large data repositories are increasingly being optimised. Radiation oncology as a discipline is at...
Machine Learning Biomarkers, Tumor Computational Biology Glioma Humans Radiation Oncology Central Nervous System Neoplasms
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Machine learning modeling of genome-wide copy number alteration signatures reliably predicts IDH mutational status in adult diffuse glioma.

Acta neuropathologica communications Dec 4, 2021
Knowledge of 1p/19q-codeletion and IDH1/2 mutational status is necessary to interpret any investigational study of diffuse gliomas in the modern era. While DNA sequencing is the gold standard for determining IDH mutational status, genome-wide methyla...
Isocitrate Dehydrogenase Biomarkers, Tumor Brain Neoplasms Humans DNA Copy Number Variations Machine Learning Glioma Whole Genome Sequencing
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Development and Practical Implementation of a Deep Learning-Based Pipeline for Automated Pre- and Postoperative Glioma Segmentation.

AJNR. American journal of neuroradiology Dec 2, 2021
BACKGROUND AND PURPOSE: Quantitative volumetric segmentation of gliomas has important implications for diagnosis, treatment, and prognosis. We present a deep-learning model that accommodates automated preoperative and postoperative glioma segmentatio...
Image Processing, Computer-Assisted Glioma Magnetic Resonance Imaging Postoperative Period Neural Networks, Computer Deep Learning Humans
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Artificial intelligence on MRI for molecular subtyping of diffuse gliomas: feature comparison, visualization, and correlation between radiomics and deep learning.

European radiology Nov 26, 2021
Magnetic Resonance Imaging Deep Learning Glioma Humans Artificial Intelligence
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Research and Analysis of Brain Glioma Imaging Based on Deep Learning.

Journal of healthcare engineering Nov 18, 2021
The incidence of glioma is increasing year by year, seriously endangering people's health. Magnetic resonance imaging (MRI) can effectively provide intracranial images of brain tumors and provide strong support for the diagnosis and treatment of the ...
Brain Humans Magnetic Resonance Imaging Deep Learning Image Processing, Computer-Assisted Neural Networks, Computer Glioma
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