Laboratorio de Procesado de Imagen

(Image Processing Lab)
E.T.S.I. Telecomunicación
Campus Miguel Delibes s/n
Universidad de Valladolid
47011 Valladolid, Spain

Un trabajo fin de grado realizado en el LPI consigue un 98% de acierto en el diagnóstico del TDAH

[30 Aug 2019]

El TFG realizado por Patricia Amado Caballero "Ayuda al diagnóstico del TDAH en la infancia mediante técnicas de procesado de señal y aprendizaje" ha dado lugar a un sistema que alcanza un 98% de acierto en el diagnóstico del TDAH. El TFG aplica técnicas de aprendizaje profundo (deep learning) para analizar firmas espectrales en patrones de movimiento. Para adquirir estos patrones se han utilizado pulseras de actividad que no interfieren para nada en la vida diaria del niño.

OpenCLIPER: An OpenCL-Based C++ Framework for Overhead-Reduced Medical Image Processing and Reconstruction on Heterogeneous Devices

OpenCLIPER performance vs. alternatives
[03 Jul 2019]

OpenCLIPER allows us to take advantage of any parallel computing device (CPUs, GPUs, FPGAs, DSPs, etc., as long as there is an OpenCL implementation for it), while developing medical imaging methods, but without the burden that OpenCL generally conveys. The work has been published in the IEEE Journal of Biomedical and Health Informatics journal.

Thesis distinction

[31 May 2019]

Tomasz Pieciak has received a distinction for his thesis entitled "Non-stationary noise estimation in accelerated parallel MRI data" in the contest sponsored by the ABB HQ in Poland. The contest is organized in the area of technical sciences and includes theses defended in various fields such as advanced technologies and engineering systems, automation and industrial diagnostics, power electronics and technologies, and computer science systems. The thesis was co-supervised by Prof. Santiago Aja-Fernández.

A Novel Second-Order Scheme for the Multi-Stencil Fast Marching Method

[12 Feb 2019]

A paper entitled "A Second Order Multi-Stencil Fast Marching Method With a Non-Constant Local Cost Model" has been recently published in the IEEE Transactions on Image Processing. The proposed scheme has been applied to optimal course planning of an unmanned aerial vehicle (UAV) in a flooding episode, and achieves better tradeoff between the distance travelled by the UAV and the amount of visited flooded land than previous state-of-the-art schemes of the Fast Marching method.