Checking date: 18/05/2023

Course: 2023/2024

Biosignals & Bioimages
Master in Machine Learning for Health (Plan: 480 - Estudio: 359)

Coordinating teacher: IZQUIERDO GARCÍA, DAVID

Department assigned to the subject: Bioengineering Department

Type: Compulsory
ECTS Credits: 6.0 ECTS


Requirements (Subjects that are assumed to be known)
- Signals and systems - Fundamentals of bioengineering - Differential equations - Image processing
The 'Biosignals and BioImages' course deepens in the understanding of the BioSignals and BioImages initiated on the Introduction course. During this course we will analyze in detail the processes related to detecting, obtaining, recording and analyzing the different BioSignal and BioImages that can be later on used in pre-clinical and clinical applications. We will deepen on the physical and physiological origin of the different signals and images. During this course we will explore different modalities, such as ECG, EEG, MRI, CT or PET among others. We will study the physical devices, tools and methods that enable the acquisition and recording of their signals and images. We will discover the fundamental methods behind signal and image processing to record and analyze the data obtained from BioSignal and BioImages, on 1D, 2D, 3D and even 4D.
Skills and learning outcomes
Description of contents: programme
Biosignals: Sources of physiological signals and images: physical principles, acquisition, clinical use Methods of biomedical signal acquisition. Information extraction, advanced processing, diagnostic aids Applications: ECG, EEG, others Modeling Bioimages: 2d, 3D and nD image Physics of medical imaging Identification of biomarkers Electromagnetic radiation and its effects on biological tissue. Molecular and multimodal imaging concept Image quantification: dynamic data, parametric images, kinetic analysis DICOM information model and its use for the transmission of files
Learning activities and methodology
AF3 Theoretical practical classes AF4 Laboratory practices AF6 Team work AF7 Student individual work AF8 Partial and final exams Activity code total hours number presencial hours number % Student Presence AF3 84 84 100% AF4 63 63 100% AF6 90 0 0% AF7 222 0 0% AF8 9 9 100% TOTAL SUBJECT 468 156 33,3%
Assessment System
  • % end-of-term-examination 30
  • % of continuous assessment (assigments, laboratory, practicals...) 70
Calendar of Continuous assessment
Basic Bibliography
  • Sörnmo, Laguna. Biolectrical Signal Processing in Cardiac and Neurological Applications. Elsevier. 2005
  • Toenies . Guide to Medical Image Analysis. Springer. 2017
  • van Drongelen. Signal Processing for Neuroscientists. Academic Press. 2018
Additional Bibliography
  • Bailey, Townsend, Valk and Maisey. Positron Emission Tomography: Basic Sciences. Springer. 2003
  • Hendee, Ritenour. Medical Imaging Physics. Wiley. 2002
  • McRobbie, Moore, Graves and Prince. MRI From Picture to Proton. Cambridge University Press. 2017
  • Michael E. Phelps. PET Molecular Imaging and Its Biological Applications. Springer. 2004

The course syllabus may change due academic events or other reasons.