Exploració per tema "Brain -- Tumors -- Diagnosis"
Ara es mostren els items 1-17 de 17
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A comparison of non-negative matrix underapproximation methods for the decomposition of magnetic resonance spectroscopy data from human brain tumors
(John Wiley & sons, 2023-12)
Article
Accés obertMagnetic resonance spectroscopy (MRS) is an MR technique that provides informa-tion about the biochemistry of tissues in a noninvasive way. MRS has been widelyused for the study of brain tumors, both preoperatively and ... -
Automated classification of brain tumours from short echo time in vivo MRS data using Gaussian decomposition and Bayesian neural networks
(2014-09)
Article
Accés restringit per política de l'editorialNeuro-oncologists must ultimately rely on their acquired knowledge and accumulated experience to undertake the sensitive task of brain tumour diagnosis. This task strongly depends on indirect, non-invasive measurements, ... -
Automated quality control for proton magnetic resonance spectroscopy data using convex non-negative matrix factorization
(Springer, 2016)
Text en actes de congrés
Accés obertProton Magnetic Resonance Spectroscopy (1H MRS) has proven its diagnostic potential in a variety of conditions. However, MRS is not yet widely used in clinical routine because of the lack of experts on its diagnostic ... -
Classifying malignant brain tumours from 1H-MRS data using Breadth Ensemble Learning
(Institute of Electrical and Electronics Engineers (IEEE), 2012)
Text en actes de congrés
Accés obertIn neuro oncology, the accurate diagnostic identification and characterization of tumours is paramount for determining their prognosis and the adequate course of treatment. This is usually a difficult problem per se, due ... -
Discriminating glioblastomas from metastases in a SV1H-MRS brain tumour database
(2009)
Text en actes de congrés
Accés obertA Feature Selection (FS) process with a simple Machine Learning method, namely the Single-Layer Perceptron (SLP), is shown to discriminate metastases from glioblastomas with high accuracy using single voxel H-MRS from an ... -
Exploratory characterization of a multi-centre 1H-MRS brain tumour database
(Future Technology Press, 2009-01-31)
Capítol de llibre
Accés restringit per política de l'editorialNon-invasive techniques such asMagnetic Resonance Imaging (MRI) and Magnetic Resonance Spectroscopy (MRS) are often required for the diagnosis of tumours for which conclusive biopsies are not commonly available.While ... -
Exploratory characterization of outliers in a multi-centre 1H-MRS brain tumour dataset
(2008-09)
Article
Accés restringit per política de l'editorialAs part of the AIDTumour research project, the analysis of MRS data corresponding to various tumour pathologies is used to assist expert diagnosis. The high dimensionality of the MR spectra might obscure atypical aspects ... -
Feature selection for the prediction and visualization of brain tumor types using proton magnetic resonance spectroscopy data
(Springer, 2012)
Capítol de llibre
Accés restringit per política de l'editorialIn cancer diagnosis, classification of the different tumor types is of great importance. An accurate prediction of basic tumor types provides better treatment and may minimize the negative impact of incorrectly targeted ... -
Feature selection in proton magnetic resonance spectroscopy data of brain tumors
(Università degli Studi di Salerno, 2011)
Text en actes de congrés
Accés obertIn cancer diagnosis, classification of the different tumor types is of great importance. An accurate prediction of different tumor types provides better treatment and may minimize the negative impact of incorrectly targeted ... -
Feature selection in proton magnetic resonance spectroscopy for brain tumor classification
(2008)
Text en actes de congrés
Accés obertH-MRS is a technique that uses response of protons under certain magnetic conditions to reveal the biochemical structure of human tissue. An important application is found in brain tumor diagnosis, due to the known ... -
Feature Selection with Single-Layer Perceptrons for a multicentre 1H-MRS brain tumour database
(2009-06-12)
Article
Accés restringit per política de l'editorialA Feature Selection process with Single-Layer Perceptrons is shown to provide optimum discrimination of an international, multi-centre 1H-MRS database of brain tumors at reasonable computational cost. Results are both ... -
Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the BRATS challenge
(2019-03-19)
Report de recerca
Accés obertGliomas are the most common primary brain malignancies, with different degrees of aggressiveness, variable prognosis and various heterogeneous histologic sub-regions, i.e., peritumoral edematous/invaded tissue, necrotic ... -
MRI brain tumor segmentation and uncertainty estimation using 3D-UNet architectures
(Springer Nature, 2021)
Capítol de llibre
Accés obertAutomation of brain tumor segmentation in 3D magnetic resonance images (MRIs) is key to assess the diagnostic and treatment of the disease. In recent years, convolutional neural networks (CNNs) have shown improved results ... -
QU-BraTS: MICCAI BraTS 2020 challenge on quantifying uncertainty in brain tumor segmentation -- analysis of ranking metrics and benchmarking results
(2021-12-19)
Report de recerca
Accés obertDeep learning (DL) models have provided the state-of-the-art performance in a wide variety of medical imaging benchmarking challenges, including the Brain Tumor Segmentation (BraTS) challenges. However, the task of focal ... -
QU-BraTS: MICCAI BraTS 2020 challenge on quantifying uncertainty in brain tumor segmentation: analysis of ranking scores and benchmarking results
(2022-08-26)
Article
Accés obertDeep learning (DL) models have provided state-of-the-art performance in various medical imaging benchmarking challenges, including the Brain Tumor Segmentation (BraTS) chal- lenges. However, the task of focal pathology ... -
Rule-based assistance to brain tumour diagnosis using LR-FIR
(2008-09)
Article
Accés restringit per política de l'editorialThis paper describes a process of rule-extraction from a multi-centre brain tumour database consisting of nuclear magnetic res- onance spectroscopic signals. The expert diagnosis of human brain tumours can benefit from ... -
Using single-voxel magnetic resonance spectroscopy data acquired at 1.5T to classify multivoxel data at 3T: a proof-of-concept study
(Multidisciplinary Digital Publishing Institute (MDPI), 2023-07-01)
Article
Accés obertIn vivo magnetic resonance spectroscopy (MRS) has two modalities, single-voxel (SV) and multivoxel (MV), in which one or more contiguous grids of SVs are acquired. Purpose: To test whether MV grids can be classified with ...