AIMC Topic: Glioblastoma

Clear Filters Showing 61 to 70 of 213 articles

Therapy-induced modulation of tumor vasculature and oxygenation in a murine glioblastoma model quantified by deep learning-based feature extraction.

Scientific reports Jan 23, 2024
Glioblastoma presents characteristically with an exuberant, poorly functional vasculature that causes malperfusion, hypoxia and necrosis. Despite limited clinical efficacy, anti-angiogenesis resulting in vascular normalization remains a promising the...
Animals Glioma Glioblastoma Hypoxia Deep Learning Mice Immunotherapy
View on PubMed DOI

A deep convolutional neural network for the automatic segmentation of glioblastoma brain tumor: Joint spatial pyramid module and attention mechanism network.

Artificial intelligence in medicine Jan 19, 2024
This study proposes a deep convolutional neural network for the automatic segmentation of glioblastoma brain tumors, aiming sat replacing the manual segmentation method that is both time-consuming and labor-intensive. There are many challenges for au...
Magnetic Resonance Imaging Glioblastoma Neural Networks, Computer Brain Neoplasms Image Processing, Computer-Assisted Humans
View on PubMed DOI

Rapid visualization of PD-L1 expression level in glioblastoma immune microenvironment via machine learning cascade-based Raman histopathology.

Journal of advanced research Dec 10, 2023
INTRODUCTION: Combination immunotherapy holds promise for improving survival in responsive glioblastoma (GBM) patients. Programmed death-ligand 1 (PD-L1) expression in immune microenvironment (IME) is the most important predictive biomarker for immun...
B7-H1 Antigen Mice Spectrum Analysis, Raman Support Vector Machine Glioblastoma Brain Neoplasms Humans Animals Machine Learning Cell Line, Tumor Tumor Microenvironment
View on PubMed DOI

Differentiation Between Glioblastoma and Metastatic Disease on Conventional MRI Imaging Using 3D-Convolutional Neural Networks: Model Development and Validation.

Academic radiology Nov 17, 2023
RATIONALE AND OBJECTIVES: Imaging-based differentiation between glioblastoma (GB) and brain metastases (BM) remains challenging. Our aim was to evaluate the performance of 3D-convolutional neural networks (CNN) to address this binary classification p...
Adult Brain Neoplasms Male Middle Aged Imaging, Three-Dimensional Magnetic Resonance Imaging Female Reproducibility of Results Aged Humans Neural Networks, Computer Diagnosis, Differential Glioblastoma Image Interpretation, Computer-Assisted
View on PubMed DOI

Editorial for "Glioblastoma and Solitary Brain Metastasis: Differentiation by Integrating Demographic-MRI and Deep-Learning Radiomics Signatures".

Journal of magnetic resonance imaging : JMRI Nov 16, 2023
Humans Diagnosis, Differential Brain Neoplasms Glioblastoma Brain Deep Learning Radiomics Magnetic Resonance Imaging
View on PubMed DOI

Glioblastoma and Solitary Brain Metastasis: Differentiation by Integrating Demographic-MRI and Deep-Learning Radiomics Signatures.

Journal of magnetic resonance imaging : JMRI Nov 13, 2023
BACKGROUND: Studies have shown that deep-learning radiomics (DLR) could help differentiate glioblastoma (GBM) from solitary brain metastasis (SBM), but whether integrating demographic-MRI and DLR features can more accurately distinguish GBM from SBM ...
Magnetic Resonance Imaging Diagnosis, Differential Glioblastoma Radiomics Brain Neoplasms Male Middle Aged Deep Learning Nomograms Female Aged Adult Brain Retrospective Studies Humans
View on PubMed DOI

Multi-class glioma segmentation on real-world data with missing MRI sequences: comparison of three deep learning algorithms.

Scientific reports Nov 2, 2023
This study tests the generalisability of three Brain Tumor Segmentation (BraTS) challenge models using a multi-center dataset of varying image quality and incomplete MRI datasets. In this retrospective study, DeepMedic, no-new-Unet (nn-Unet), and NVI...
Humans Algorithms Retrospective Studies Glioma Magnetic Resonance Imaging Glioblastoma Brain Neoplasms Deep Learning Image Processing, Computer-Assisted
View on PubMed DOI

"A net for everyone": fully personalized and unsupervised neural networks trained with longitudinal data from a single patient.

BMC medical imaging Oct 31, 2023
BACKGROUND: With the rise in importance of personalized medicine and deep learning, we combine the two to create personalized neural networks. The aim of the study is to show a proof of concept that data from just one patient can be used to train dee...
Image Processing, Computer-Assisted Magnetic Resonance Imaging Glioblastoma Humans Neural Networks, Computer Brain
View on PubMed DOI

Emerging trends in post-translational modification: Shedding light on Glioblastoma multiforme.

Biochimica et biophysica acta. Reviews on cancer Oct 18, 2023
Recent multi-omics studies, including proteomics, transcriptomics, genomics, and metabolomics have revealed the critical role of post-translational modifications (PTMs) in the progression and pathogenesis of Glioblastoma multiforme (GBM). Further, PT...
Tumor Microenvironment Genomics Protein Processing, Post-Translational Humans Glioblastoma Artificial Intelligence Biomarkers
View on PubMed DOI

MGMT promoter methylation status prediction using MRI scans? An extensive experimental evaluation of deep learning models.

Medical image analysis Oct 6, 2023
The number of studies on deep learning for medical diagnosis is expanding, and these systems are often claimed to outperform clinicians. However, only a few systems have shown medical efficacy. From this perspective, we examine a wide range of deep l...
Magnetic Resonance Imaging Glioblastoma DNA Modification Methylases DNA Repair Enzymes Tumor Suppressor Proteins Humans Aged Methylation Reproducibility of Results Brain Neoplasms Deep Learning
View on PubMed DOI
Popular Topics
Recent Journals