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.
Laboratorio de Procesado de Imagen
(Image Processing Lab)
Campus Miguel Delibes s/n
Universidad de Valladolid
47011 Valladolid, Spain
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.
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 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.