12 Result(s)
within
Elies Fuster-Garcia
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Article
Open AccessInterpreting deep learning models for glioma survival classification using visualization and textual explanations
Saliency-based algorithms are able to explain the relationship between input image pixels and deep-learning model predictions. However, it may be difficult to assess the clinical value of the most important im...
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Article
Open AccessLocal detection of microvessels in IDH-wildtype glioblastoma using relative cerebral blood volume: an imaging marker useful for astrocytoma grade 4 classification
The microvessels area (MVA), derived from microvascular proliferation, is a biomarker useful for high-grade glioma classification. Nevertheless, its measurement is costly, labor-intense, and invasive. Finding ...
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Article
Open AccessMGMT methylation may benefit overall survival in patients with moderately vascularized glioblastomas
To assess the combined role of tumor vascularity, estimated from perfusion MRI, and MGMT methylation status on overall survival (OS) in patients with glioblastoma.
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Article
Non-local spatially varying finite mixture models for image segmentation
In this work, we propose a new Bayesian model for unsupervised image segmentation based on a combination of the spatially varying finite mixture models (SVFMMs) and the non-local means (NLM) framework. The pro...
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Chapter and Conference Paper
ONCOhabitats Glioma Segmentation Model
ONCOhabitats is an open online service that provides a fully automatic analysis of tumor vascular heterogeneity in gliomas based on multiparametric MRI. Having a model capable of accurately segment pathologica...
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Chapter
Use Case II: Imaging Biomarkers and New Trends for Integrated Glioblastoma Management
Glioblastoma (GB) implies a devastating prognosis with an average survival of 14–16 months using the current standard of care treatment [1]. GB is the most frequent malignant tumour originating from the brain ...
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Chapter and Conference Paper
GBM Modeling with Proliferation and Migration Phenotypes: A Proposal of Initialization for Real Cases
Glioblastoma is the most aggressive tumor originated in the central nervous system. Modeling its evolution is of great interest for therapy planning and early response to treatment assessment. Using a continuo...
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Chapter and Conference Paper
An Online Platform for the Automatic Reporting of Multi-parametric Tissue Signatures: A Case Study in Glioblastoma
Glioblastomas are infiltrative and deeply invasive neoplasms characterized by high vascular proliferation and diffuse margins. As a consequence, this lesion presents a high degree of heterogeneity that require...
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Protocol
Actigraphy Pattern Analysis for Outpatient Monitoring
The actigraphy is a cost-effective method for assessing specific sleep disorders such as diagnosing insomnia, circadian rhythm disorders, or excessive sleepiness. Due to recent advances in wireless connectivit...
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Chapter and Conference Paper
Next Generation HPC Clouds: A View for Large-Scale Scientific and Data-Intensive Applications
In spite of the rapid growth of Infrastructure-as-a-Service offers, support to run data-intensive and scientific applications large-scale is still limited. On the user side, existing features and programming m...
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Article
Compatibility between 3T 1H SV-MRS data and automatic brain tumour diagnosis support systems based on databases of 1.5T 1H SV-MRS spectra
This study demonstrates that 3T SV-MRS data can be used with the currently available automatic brain tumour diagnostic classifiers which were trained on databases of 1.5T spectra. This will allow the existing ...
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Article
Open AccessMultiproject–multicenter evaluation of automatic brain tumor classification by magnetic resonance spectroscopy
Automatic brain tumor classification by MRS has been under development for more than a decade. Nonetheless, to our knowledge, there are no published evaluations of predictive models with unseen cases that are ...
