Identifying Data 2020/21
Subject (*) Instrumentation and Processing for Biomedical Applications Code 614535012
Study programme
Máster Universitario en Visión por Computador
Descriptors Cycle Period Year Type Credits
Official Master's Degree 1st four-month period
 First Obligatory 6
Language
English
Teaching method Hybrid
Prerequisites
Department Ciencias da Computación e Tecnoloxías da Información
Coordinador
Novo Bujan, Jorge
 E-mail
j.novo@udc.es
Lecturers
Novo Bujan, Jorge
Ortega Hortas, Marcos
 E-mail
j.novo@udc.es
m.ortega@udc.es
Web
General description
Contingency plan 1. Modificacións nos contidos
Sen cambios.

2. Metodoloxías
*Metodoloxías docentes que se manteñen
Todas.

*Metodoloxías docentes que se modifican
O ensino será telemático e as clases desenvolveranse de maneira síncrona no horario oficial de clases. Pode ser que, por razóns subrevenidas, algunhas das clases sexan realizadas de forma asíncrona, o que se comunicará ao alumnado con anticipación.


3. Mecanismos de atención personalizada ao alumnado
As titorías serán telemáticas e requirirán cita previa.

4. Modificacións na avaliación

As actividades de avaliación que non se poidan levar a cabo en persoa, se non poden posporse, levaranse a cabo telemáticamente a través das ferramentas institucionais en Office 365 e Moodle. Neste caso, requirirase a adopción dunha serie de medidas que requirirán que o alumnado teña un dispositivo cun micrófono e unha cámara, mentres non se dispoña dun software de avaliación adecuado. Pódese chamar a cada estudante para unha entrevista para comentar ou explicar parte ou a totalidade da proba. A duración das actividades telemáticas será dun máximo de 1 hora nas probas de avaliación continua e de 2 horas no caso dun exame final.
NOTA: Nestes escenarios, pode cambiar o tipo de actividades que se realizarán ou a modalidade, pero non a súa contribución xeral á cualificación final (a porcentaxe de ponderación).

5. Modificacións da bibliografía ou webgrafía
Sen cambios.

Study programme competencies
Code Study programme competences
A1 CE1 - To know and apply the concepts, methodologies and technologies of image processing
A3 CE3 - To know and apply the concepts, methodologies and technologies of image and video analysis
A7 CE7 - To understand and apply the fundamentals of medical image acquisition, processing and analysis
B2 CB7 - That students are able to apply their acquired knowledge and problem-solving skills in new or unfamiliar environments within broader (or multidisciplinary) contexts related to their area of study
B3 CB8 - That students are able to integrate knowledge and deal with the complexity of making judgements based on information that is incomplete or limited, including reflections on social and ethical responsibilities linked to the application of their knowledge and judgements
B5 CB10 - That students possess the learning skills to enable them to continue studying in a largely self-directed or autonomous manner
B8 CG3 - Ability to develop computer vision systems depending on existing needs and apply the most appropriate technological tools
B9 CG4 - Ability to critically analyze and rigorously evaluate technologies and methodology
B12 CG7 - Ability to learn autonomously for specialization in one or more fields of study
C4 CT4 - Ability to understand the meaning and application of the gender perspective in different areas of knowledge and professional practice with the aim of achieving a more just and equal society

Learning aims
Learning outcomes Study programme competences
Understand the basic concepts related to different biomedical imaging modalities and the physical factors that influence their properties. AC1
AC3
AC7
 BC2
BC3
BC5
BC8
BC9
BC12
 CC4
To know the statistical techniques currently used for the validation of biomedical applications. AC1
AC3
AC7
 BC2
BC3
BC5
BC8
BC9
BC12
 CC4
Ability to apply different processing and analysis techniques in biomedical imaging applications. AC1
AC3
AC7
 BC2
BC3
BC5
BC8
BC9
BC12
 CC4
Knowledge of image registration techniques and their applications in biomedical imaging. AC1
AC3
AC7
 BC2
BC3
BC5
BC8
BC9
BC12
 CC4

Contents
Topic Sub-topic
Basic concepts of biomedical imaging.
Biomedical imaging modalities.
Validation techniques in biomedical applications.
Biomedical image processing and analysis.
Registration of biomedical images.
Biomedical imaging applications.

Planning
Methodologies / tests Competencies Ordinary class hours Student’s personal work hours Total hours
Laboratory practice B2 B3 B8 B12 15 51.84 66.84
Supervised projects B2 B3 B8 B12 10 34.56 44.56
Guest lecture / keynote speech A1 A3 A7 B5 B9 C4 14 21.6 35.6
 
Personalized attention 3 0 3
 
(*)The information in the planning table is for guidance only and does not take into account the heterogeneity of the students.

Methodologies
Methodologies Description
Laboratory practice Practical exercises in computer classrooms, learning based on the resolution of practical cases, combining work and autonomous learning with group work for cooperative learning
Supervised projects Presentations of project-oriented works
Guest lecture / keynote speech Participatory Master Lessons

Personalized attention
Methodologies
Laboratory practice
Supervised projects
Description

Attention to the challenges posed to students both in the practices and in the work.

Assessment
Methodologies Competencies Description Qualification
Laboratory practice B2 B3 B8 B12 Development practices of applied cases 50
Guest lecture / keynote speech A1 A3 A7 B5 B9 C4 Demonstration of application of knowledge taught in class 20
Supervised projects B2 B3 B8 B12 Practical projects related to the subject 30
 
Assessment comments

Sources of information
Basic

- Bushberg JT, Seibert JA, Leidholdt EM, Boone JM: “The Essential Physics of Medical Imaging”. Lippincott Williams & Wilkins. 2002.

- Fish P: “Physics and Instrumentation of Diagnostic Medical Ultrasound”. John Wiley & Sons. 1999.

- Sprawls Perry: "Magnetic Resonance Imaging. Principles, Methods and Techniques". Medical Physics Publishing. 2000.
Complementary


Recommendations
Subjects that it is recommended to have taken before

Subjects that are recommended to be taken simultaneously
Fundamentals of Machine Learning for Computer Vision /614535007
Fundamentals of Image Processing and Analysis /614535001

Subjects that continue the syllabus
Biomedical Image Analysis/614535013

Other comments


(*)The teaching guide is the document in which the URV publishes the information about all its courses. It is a public document and cannot be modified. Only in exceptional cases can it be revised by the competent agent or duly revised so that it is in line with current legislation.