[HTML][HTML] Magnetic resonance spectroscopy—revisiting the biochemical and molecular milieu of brain tumors

A Verma, I Kumar, N Verma, P Aggarwal, R Ojha - BBA clinical, 2016 - Elsevier
Background Magnetic resonance spectroscopy (MRS) is an established tool for in-vivo
evaluation of the biochemical basis of human diseases. On one hand, such lucid depiction …

The importance of interpretability and visualization in machine learning for applications in medicine and health care

A Vellido - Neural computing and applications, 2020 - Springer
In a short period of time, many areas of science have made a sharp transition towards data-
dependent methods. In some cases, this process has been enabled by simultaneous …

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 …

Surface recognition improvement in 3D medical laser scanner using Levenberg–Marquardt method

JC Rodriguez-Quinonez, O Sergiyenko… - Signal Processing, 2013 - Elsevier
The 3D measurements of the human body surface or anatomical areas have gained
importance in many medical applications. Three dimensional laser scanning systems can …

Classification of human brain tumours from MRS data using Discrete Wavelet Transform and Bayesian Neural Networks

C Arizmendi, A Vellido, E Romero - Expert Systems with Applications, 2012 - Elsevier
The diagnosis of brain tumours is an extremely sensitive and complex clinical task that must
rely upon information gathered through non-invasive techniques. One such technique is …

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 …

SpectraClassifier 1.0: a user friendly, automated MRS-based classifier-development system

S Ortega-Martorell, I Olier, M Julià-Sapé, C Arús - BMC bioinformatics, 2010 - Springer
Background SpectraClassifier (SC) is a Java solution for designing and implementing
Magnetic Resonance Spectroscopy (MRS)-based classifiers. The main goal of SC is to allow …

A comparison of non‐negative matrix underapproximation methods for the decomposition of magnetic resonance spectroscopy data from human brain tumors

G Ungan, C Arús, A Vellido… - NMR in …, 2023 - Wiley Online Library
Magnetic resonance spectroscopy (MRS) is an MR technique that provides information
about the biochemistry of tissues in a noninvasive way. MRS has been widely used for the …

Robust discrimination of glioblastomas from metastatic brain tumors on the basis of single‐voxel 1H MRS

A Vellido, E Romero, M Julià‐Sapé, C Majós… - NMR in …, 2012 - Wiley Online Library
This article investigates methods for the accurate and robust differentiation of metastases
from glioblastomas on the basis of single‐voxel 1H MRS information. Single‐voxel 1H MR …

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 …