AIMC Topic: Meningioma
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Mixture Model Segmentation System for Parasagittal Meningioma brain Tumor Classification based on Hybrid Feature Vector.
Journal of medical systems
Nov 3, 2018
Meningioma is the one of the most common type of brain tumor, it as arises from the meninges and encloses the spine and the brain inside the skull. It accounts for 30% of all types of brain tumor. Meningioma's can occur in many parts of the brain and...
A methodological approach for deep learning to distinguish between meningiomas and gliomas on canine MR-images.
BMC veterinary research
Oct 22, 2018
BACKGROUND: Distinguishing between meningeal-based and intra-axial lesions by means of magnetic resonance (MR) imaging findings may occasionally be challenging. Meningiomas and gliomas account for most of the total primary brain neoplasms in dogs, an...
The diagnostic value of texture analysis in predicting WHO grades of meningiomas based on ADC maps: an attempt using decision tree and decision forest.
European radiology
Aug 7, 2018
OBJECTIVES: The preoperative prediction of the WHO grade of a meningioma is important for further treatment plans. This study aimed to assess whether texture analysis (TA) based on apparent diffusion coefficient (ADC) maps could non-invasively classi...
Fully automated detection and segmentation of meningiomas using deep learning on routine multiparametric MRI.
European radiology
Jun 25, 2018
OBJECTIVES: Magnetic resonance imaging (MRI) is the method of choice for imaging meningiomas. Volumetric assessment of meningiomas is highly relevant for therapy planning and monitoring. We used a multiparametric deep-learning model (DLM) on routine ...
Development of a deep convolutional neural network to predict grading of canine meningiomas from magnetic resonance images.
Veterinary journal (London, England : 1997)
Apr 4, 2018
An established deep neural network (DNN) based on transfer learning and a newly designed DNN were tested to predict the grade of meningiomas from magnetic resonance (MR) images in dogs and to determine the accuracy of classification of using pre- and...
eNAL++: a new and effective off-line correction protocol for rotational setup errors when using a robotic couch.
Journal of applied clinical medical physics
Nov 8, 2015
Cone-beam CTs (CBCTs) installed on a linear accelerator can be used to provide fast and accurate automatic six degrees of freedom (6DoF) vector displacement information of the patient position just prior to radiotherapy. These displacement correction...
A multiresolution clinical decision support system based on fractal model design for classification of histological brain tumours.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Jun 7, 2014
Tissue texture is known to exhibit a heterogeneous or non-stationary nature; therefore using a single resolution approach for optimum classification might not suffice. A clinical decision support system that exploits the subbands' textural fractal ch...
Fractals
Reproducibility of Results
Decision Support Systems, Clinical
Meningeal Neoplasms
Image Enhancement
Support Vector Machine
Sensitivity and Specificity
Humans
Image Interpretation, Computer-Assisted
Microscopy
Machine Learning
Pattern Recognition, Automated
Algorithms
Meningioma
Brain Neoplasms
[Radiosurgery of benign intracranial lesions. Indications, results , and perspectives].
Revue medicale suisse
May 14, 2025
Stereotactic radiosurgery (SRS) is a non-invasive technique that is transforming the management of benign intracranial lesions through its precision and preservation of healthy tissues. It is effective for meningiomas, trigeminal neuralgia (TN), pitu...
An MRI-based deep transfer learning radiomics nomogram for predicting meningioma grade.
Scientific reports
May 13, 2025
The aim of this study was to establish a nomogram based on clinical, radiomics, and deep transfer learning (DTL) features to predict meningioma grade. Three hundred forty meningiomas from one hospital composed the training set, and 102 meningiomas fr...
Machine Learning Analysis of Single-Voxel Proton MR Spectroscopy for Differentiating Solitary Fibrous Tumors and Meningiomas.
NMR in biomedicine
May 1, 2025
Solitary fibrous tumor (SFT), formerly known as hemangiopericytoma, is an uncommon brain tumor often confused with meningioma on MRI. Unlike meningiomas, SFTs exhibit a myoinositol peak on magnetic resonance spectroscopy (MRS). This study aimed to de...
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