Browsing by Author "Sanchez Lasheras, Fernando"

Now showing 1 - 4 of 4
  • No Thumbnail Available
    Item
    A nomogram for predicting complications in patients with solid tumours and seemingly stable febrile neutropenia
    (2016) Jimenez Fonseca, Paula; Carmona-Bayonas, Alberto; Matos Garcia, Ignacio; Marcos, Rosana; Castanon, Eduardo; Antonio, Maite; Font, Carme; Biosca, Merce; Blasco, Ana; Lozano, Rebeca; Ramchandani, Avinash; Beato, Carmen; Martinez de Castro, Eva; Espinosa, Javier; Martinez-Garcia, Jeronimo; Ghanem, Ismael; Hernando Cubero, Jorge; Aragon Manrique, Isabel; Garcia Navalon, Francisco; Sevillano, Elena; Manzano, Aranzazu; Virizuela, Juan; Garrido, Marcelo; Mondejar, Rebeca; Angeles Arcusa, Maria; Bonilla, Yaiza; Perez, Quionia; Gallardo, Elena; del Carmen Soriano, Maria; Cardona, Merce; Sanchez Lasheras, Fernando; Jesus Cruz, Juan; Ayala, Francisco
    Background: We sought to develop and externally validate a nomogram and web-based calculator to individually predict the development of serious complications in seemingly stable adult patients with solid tumours and episodes of febrile neutropenia (FN).
  • Thumbnail Image
    Item
    An ANN-Based Smart Tomographic Reconstructor in a Dynamic Environment
    (MDPI, 2012) de Cos Juez, Francisco J.; Sanchez Lasheras, Fernando; Roqueni, Nieves; Osborn, James
    In astronomy, the light emitted by an object travels through the vacuum of space and then the turbulent atmosphere before arriving at a ground based telescope. By passing through the atmosphere a series of turbulent layers modify the light's wave-front in such a way that Adaptive Optics reconstruction techniques are needed to improve the image quality. A novel reconstruction technique based in Artificial Neural Networks (ANN) is proposed. The network is designed to use the local tilts of the wave-front measured by a Shack Hartmann Wave-front Sensor (SHWFS) as inputs and estimate the turbulence in terms of Zernike coefficients. The ANN used is a Multi-Layer Perceptron (MLP) trained with simulated data with one turbulent layer changing in altitude. The reconstructor was tested using three different atmospheric profiles and compared with two existing reconstruction techniques: Least Squares type Matrix Vector Multiplication (LS) and Learn and Apply (L + A).
  • Thumbnail Image
    Item
    Deformable mirror model for open-loop adaptive optics using multivariate adaptive regression splines
    (OPTICAL SOC AMER, 2010) Guzman, Dani; de Cos Juez, Francisco Javier; Sanchez Lasheras, Fernando; Myers, Richard; Young, Laura
    Open-loop adaptive optics is a technique in which the turbulent wavefront is measured before it hits the deformable mirror for correction. We present a technique to model a deformable mirror working in open-loop based on multivariate adaptive regression splines (MARS), a non-parametric regression technique. The model's input is the wavefront correction to apply to the mirror and its output is the set of voltages to shape the mirror. We performed experiments with an electrostrictive deformable mirror, achieving positioning errors of the order of 1.2% RMS of the peak-to-peak wavefront excursion. The technique does not depend on the physical parameters of the device; therefore it may be included in the control scheme of any type of deformable mirror. (C) 2010 Optical Society of America
  • Thumbnail Image
    Item
    Modeling a MEMS deformable mirror using non-parametric estimation techniques
    (OPTICAL SOC AMER, 2010) Guzman, Dani; de Cos Juez, Francisco Javier; Myers, Richard; Guesalaga, Andres; Sanchez Lasheras, Fernando
    Using non-parametric estimation techniques, we have modeled an area of 126 actuators of a micro-electro-mechanical deformable mirror with 1024 actuators. These techniques produce models applicable to open-loop adaptive optics, where the turbulent wavefront is measured before it hits the deformable mirror. The model's input is the wavefront correction to apply to the mirror and its output is the set of voltages to shape the mirror. Our experiments have achieved positioning errors of 3.1% rms of the peak-to-peak wavefront excursion. (C) 2010 Optical Society of America