EANO guidelines for the diagnosis and treatment of meningiomas
R Goldbrunner, G Minniti, M Preusser… - The Lancet …, 2016 - thelancet.com
Although meningiomas are the most common intracranial tumours, the level of evidence to
provide recommendations for the diagnosis and treatment of meningiomas is low compared …
provide recommendations for the diagnosis and treatment of meningiomas is low compared …
Brain tumor analysis empowered with deep learning: A review, taxonomy, and future challenges
Deep Learning (DL) algorithms enabled computational models consist of multiple
processing layers that represent data with multiple levels of abstraction. In recent years …
processing layers that represent data with multiple levels of abstraction. In recent years …
Radiomics and machine learning may accurately predict the grade and histological subtype in meningiomas using conventional and diffusion tensor imaging
Objectives Preoperative, noninvasive prediction of the meningioma grade is important
because it influences the treatment strategy. The purpose of this study was to evaluate the …
because it influences the treatment strategy. The purpose of this study was to evaluate the …
Imaging and diagnostic advances for intracranial meningiomas
The archetypal imaging characteristics of meningiomas are among the most stereotypic of
all central nervous system (CNS) tumors. In the era of plain film and ventriculography …
all central nervous system (CNS) tumors. In the era of plain film and ventriculography …
Brain tumor classification based on hybrid approach
Various computer systems have attracted more researchers' attention to arrive at a
qualitative diagnosis in a few times. Different brain tumor classification approaches are …
qualitative diagnosis in a few times. Different brain tumor classification approaches are …
Diagnostic challenges in meningioma
M Nowosielski, N Galldiks, S Iglseder… - Neuro …, 2017 - academic.oup.com
Advances in molecular profiling and the application of advanced imaging techniques are
currently refreshing diagnostic considerations in meningioma patients. Not only technical …
currently refreshing diagnostic considerations in meningioma patients. Not only technical …
Computer-assisted brain tumor type discrimination using magnetic resonance imaging features
Medical imaging plays an integral role in the identification, segmentation, and classification
of brain tumors. The invention of MRI has opened new horizons for brain-related research …
of brain tumors. The invention of MRI has opened new horizons for brain-related research …
Imaging and extent of surgical resection predict risk of meningioma recurrence better than WHO histopathological grade
Background Risk stratification of meningiomas by histopathological grade alone does not
reliably predict which patients will progress/recur after treatment. We sought to determine …
reliably predict which patients will progress/recur after treatment. We sought to determine …
The diagnostic value of radiomics-based machine learning in predicting the grade of meningiomas using conventional magnetic resonance imaging: a preliminary …
C Chen, X Guo, J Wang, W Guo, X Ma, J Xu - Frontiers in oncology, 2019 - frontiersin.org
Objective: The purpose of the current study is to investigate whether texture analysis-based
machine learning algorithms could help devise a non-invasive imaging biomarker for …
machine learning algorithms could help devise a non-invasive imaging biomarker for …
Accuracy of radiomics-based feature analysis on multiparametric magnetic resonance images for noninvasive meningioma grading
KR Laukamp, G Shakirin, B Baeßler, F Thiele… - World Neurosurgery, 2019 - Elsevier
Objective Meningioma grading is relevant to therapy decisions in complete or partial
resection, observation, and radiotherapy because higher grades are associated with tumor …
resection, observation, and radiotherapy because higher grades are associated with tumor …