Descripción

She obtained her B.Sc. degree in Health Engineering speciality on Biomedical Engineering in 2018 from the “Universidad de Málaga” (UMA) and her Master’s Degree in Management and Development of Biomedical Technologies from “Universidad Carlos III de Madrid” (UC3M) in 2019.

She is currently a PhD student at the Electronic and Microelectronic Design Group (GDEM) at the “Universidad Politécnica de Madrid” (UPM). Her research interest include design of new multidimensional image modalities for real-time brain tumour detection.

Publicaciones

• An Embedded GPU Accelerated Hyperspectral Video Classification System in Real-Time

• IEEE, editor. (2022). An Embedded GPU Accelerated Hyperspectral Video Classification System in Real-Time, 2021 XXXVI Conference on Design of Circuits and Integrated Systems (DCIS).

• Stitching technique based on SURF for Hyperspectral Pushbroom Linescan Cameras

• IEEE, editor. (2022). Stitching technique based on SURF for Hyperspectral Pushbroom Linescan Cameras, 2021 XXXVI Conference on Design of Circuits and Integrated Systems (DCIS).

• Supervised Machine Learning Methods and Hyperspectral Imaging Techniques Jointly Applied for Brain Cancer Classification

• Urbanos García, G., Villanueva, M., Jiménez-Roldán, L., Chavarrías Lapastora, M., Lagares, A., Juárez Martínez, E. et al
  2021
  Sensors, 21 (11)(3827), 1‐29

• Hyperspectral Images Acquisition: an Efficient Capture and Processing Stitching Procedure for Medical Environments

• IEEE, editor. (2020). Hyperspectral Images Acquisition: an Efficient Capture and Processing Stitching Procedure for Medical Environments, 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS).

• Multiclass Brain Tumor Classification Using Hyperspectral Imaging and Supervised Machine Learning

• IEEE, editor. (2020). Multiclass Brain Tumor Classification Using Hyperspectral Imaging and Supervised Machine Learning, 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS).

• Towards GPU Accelerated HyperSpectral Depth Estimation in Medical Applications

• IEEE, editor. (2020). Towards GPU Accelerated HyperSpectral Depth Estimation in Medical Applications, 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS).

Proyectos

• TALENT-HIPSTER: HIgh Performance Systems and Technologies for E-health and fish faRming

• NEMESIS-3D-CM: clasificacióN intraopEratoria de tuMores cErebraleS mediante modelos InmerSivos 3D