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 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.
El pasado 4 de octubre de 2019, en el Paraninfo de la Facultad de Derecho de la Universidad de Valladolid, tuvo lugar la toma de posesión protocolaria del Personal Docente e Investigador que ha cambiado de Cuerpo o Escala, entre ellos dos miembros del LPI: Pablo Casaseca (Profesor Titular de Universidad) y Santiago Aja (Catedrático de Universidad).
Santiago Aja-Fernandez has received the Best Poster Award in the Computational Diffusion MRI (CDMRI) workshop, held at MICCAI 2018 last Sept. 20th 2018 in Granada (Spain), for the communication "Return-to-axis probability calculation from single-shell acquisitions".
An article entitled "Scalar diffusion-MRI measures invariant to acquisition parameters: A first step towards imaging biomarkers" has recently been published in the Magnetic Resonance Imaging journal (Elsevier). In that work, we propose a new set of quantitative measures based on diffusion magnetic resonance imaging from single-shell acquisitions that are designed to be robust to the variations of several acquisition parameters (number of gradient directions, b-value and SNR) while keeping a high discrimination power on differences in the diffusion characteristics of the tissue.