AIMC Topic: Meningioma
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Research Progress of Artificial Intelligence in the Grading and Classification of Meningiomas.
Academic radiology
Feb 26, 2024
A meningioma is a common primary central nervous system tumor. The histological features of meningiomas vary significantly depending on the grade and subtype, leading to differences in treatment and prognosis. Therefore, early diagnosis, grading, and...
Meningioma consistency assessment based on the fusion of deep learning features and radiomics features.
European journal of radiology
Dec 5, 2023
PURPOSE: This study aims to combine deep learning features with radiomics features for the computer-assisted preoperative assessment of meningioma consistency.
Multicenter Study of the Utility of Convolutional Neural Network and Transformer Models for the Detection and Segmentation of Meningiomas.
Journal of computer assisted tomography
Nov 27, 2023
PURPOSE: This study aimed to investigate the effectiveness and practicality of using models like convolutional neural network and transformer in detecting and precise segmenting meningioma from magnetic resonance images.
Predicting meningioma grades and pathologic marker expression via deep learning.
European radiology
Oct 19, 2023
OBJECTIVES: To establish a deep learning (DL) model for predicting tumor grades and expression of pathologic markers of meningioma.
TumorDetNet: A unified deep learning model for brain tumor detection and classification.
PloS one
Sep 27, 2023
Accurate diagnosis of the brain tumor type at an earlier stage is crucial for the treatment process and helps to save the lives of a large number of people worldwide. Because they are non-invasive and spare patients from having an unpleasant biopsy, ...
Federated Learning: A Cross-Institutional Feasibility Study of Deep Learning Based Intracranial Tumor Delineation Framework for Stereotactic Radiosurgery.
Journal of magnetic resonance imaging : JMRI
Aug 12, 2023
BACKGROUND: Deep learning-based segmentation algorithms usually required large or multi-institute data sets to improve the performance and ability of generalization. However, protecting patient privacy is a key concern in the multi-institutional stud...
Traditional Machine Learning Methods versus Deep Learning for Meningioma Classification, Grading, Outcome Prediction, and Segmentation: A Systematic Review and Meta-Analysis.
World neurosurgery
Aug 12, 2023
BACKGROUND: Meningiomas are common intracranial tumors. Machine learning (ML) algorithms are emerging to improve accuracy in 4 primary domains: classification, grading, outcome prediction, and segmentation. Such algorithms include both traditional ap...
Intelligent noninvasive meningioma grading with a fully automatic segmentation using interpretable multiparametric deep learning.
European radiology
Apr 13, 2023
OBJECTIVES: To establish a robust interpretable multiparametric deep learning (DL) model for automatic noninvasive grading of meningiomas along with segmentation.
MRI-based brain tumor detection using convolutional deep learning methods and chosen machine learning techniques.
BMC medical informatics and decision making
Jan 23, 2023
BACKGROUND: Detecting brain tumors in their early stages is crucial. Brain tumors are classified by biopsy, which can only be performed through definitive brain surgery. Computational intelligence-oriented techniques can help physicians identify and ...
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