Frontiers of Cranial Base Surgery: Integrating Technique, Technology, and Teamwork for the Future of Neurosurgery

C Toader, L Eva, CI Tataru, RA Covache-Busuioc… - Brain Sciences, 2023 - mdpi.com
The landscape of cranial base surgery has undergone monumental transformations over the
past several decades. This article serves as a comprehensive survey, detailing both the …

Noninvasive quantification of 2-hydroxyglutarate in human gliomas with IDH1 and IDH2 mutations

UE Emir, SJ Larkin, N de Pennington, N Voets, P Plaha… - Cancer research, 2016 - AACR
Mutations in the isocitrate dehydrogenase genes (IDH1/2) occur often in diffuse gliomas,
where they are associated with abnormal accumulation of the oncometabolite 2 …

Classification of brain tumours from MR spectra: the INTERPRET collaboration and its outcomes

M Julià‐Sapé, JR Griffiths, RA Tate… - NMR in …, 2015 - Wiley Online Library
The INTERPRET project was a multicentre European collaboration, carried out from 2000 to
2002, which developed a decision‐support system (DSS) for helping neuroradiologists with …

Machine-learning classifiers in discrimination of lesions located in the anterior skull base

Y Zhang, L Shang, C Chen, X Ma, X Ou, J Wang… - Frontiers in …, 2020 - frontiersin.org
Purpose: The aim of this study was to investigate the diagnostic value of machine-learning
models with radiomic features and clinical features in preoperative differentiation of common …

Tracking Therapy Response in Glioblastoma Using 1D Convolutional Neural Networks

S Ortega-Martorell, I Olier, O Hernandez… - Cancers, 2023 - mdpi.com
Simple Summary Glioblastoma (GB) is a malignant brain tumour with no cure, even after the
best treatment. The evaluation of a therapy response is usually based on magnetic …

Seeing is believing: The importance of visualization in real-world machine learning applications

A Vellido Alcacena, JD Martín, F Rossi… - … on Artificial Neural …, 2011 - upcommons.upc.edu
The increasing availability of data sets with a huge amount of information, coded in many diff
erent features, justifi es the research on new methods of knowledge extraction: the great …

The INTERPRET Decision-Support System version 3.0 for evaluation of Magnetic Resonance Spectroscopy data from human brain tumours and other abnormal brain …

A Pérez-Ruiz, M Julià-Sapé, G Mercadal, I Olier… - BMC …, 2010 - Springer
Abstract Background Proton Magnetic Resonance (MR) Spectroscopy (MRS) is a widely
available technique for those clinical centres equipped with MR scanners. Unlike the rest of …

Quality of clinical brain tumor MR spectra judged by humans and machine learning tools

SP Kyathanahally, V Mocioiu… - Magnetic resonance …, 2018 - Wiley Online Library
Purpose To investigate and compare human judgment and machine learning tools for
quality assessment of clinical MR spectra of brain tumors. Methods A very large set of 2574 …

Molecular imaging coupled to pattern recognition distinguishes response to temozolomide in preclinical glioblastoma

T Delgado‐Goñi, M Julià‐Sapé… - NMR in …, 2014 - Wiley Online Library
Non‐invasive monitoring of response to treatment of glioblastoma (GB) is nowadays carried
out using MRI. MRS and MR spectroscopic imaging (MRSI) constitute promising tools for this …

Non-negative matrix factorisation methods for the spectral decomposition of MRS data from human brain tumours

S Ortega-Martorell, PJG Lisboa, A Vellido… - BMC …, 2012 - Springer
Background In-vivo single voxel proton magnetic resonance spectroscopy (SV 1 H-MRS),
coupled with supervised pattern recognition (PR) methods, has been widely used in clinical …