M
Montserrat Robles
Researcher at Polytechnic University of Valencia
Publications - 113
Citations - 19595
Montserrat Robles is an academic researcher from Polytechnic University of Valencia. The author has contributed to research in topics: Semantic interoperability & Noise reduction. The author has an hindex of 37, co-authored 113 publications receiving 17305 citations.
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Blast2GO: a universal tool for annotation, visualization and analysis in functional genomics research
TL;DR: Blast2GO (B2G), a research tool designed with the main purpose of enabling Gene Ontology (GO) based data mining on sequence data for which no GO annotation is yet available, is presented.
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High-throughput functional annotation and data mining with the Blast2GO suite.
Stefan Götz,Juan M. García-Gómez,Javier Terol,Tim D. Williams,Shivashankar H. Nagaraj,María José Nueda,Montserrat Robles,Manuel Talon,Joaquín Dopazo,Ana Conesa +9 more
TL;DR: The Blast2GO framework is used to carry out a detailed analysis of annotation behaviour through homology transfer and its impact in functional genomics research to offer biologists useful information to take into account when addressing the task of functionally characterizing their sequence data.
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Adaptive non‐local means denoising of MR images with spatially varying noise levels
TL;DR: In this article, the authors proposed a new method where information regarding the local image noise level is used to adjust the amount of denoising strength of the filter, which is automatically obtained from the images using a new local noise estimation method.
Journal ArticleDOI
Patch-based segmentation using expert priors: application to hippocampus and ventricle segmentation.
Pierrick Coupé,José V. Manjón,Vladimir S. Fonov,Jens C. Pruessner,Montserrat Robles,D. Louis Collins +5 more
TL;DR: Inspired by recent work in image denoising, the proposed nonlocal patch-based label fusion produces accurate and robust segmentation in quantitative magnetic resonance analysis.
Journal ArticleDOI
MRI denoising using non-local means.
José V. Manjón,José Carbonell-Caballero,Juan José Lull,Gracián García-Martí,Luis Martí-Bonmatí,Montserrat Robles +5 more
TL;DR: From the results over synthetic and real images, it can be concluded that this recently proposed filter for random noise removal can be successfully used for automatic MR denoising.