Design and Diagnostics by Image
Module: ELECTIVE
Matter: ELECTIVE
Main language of instruction: English
Other languages of instruction: Catalan, Spanish
Head instructor
Dr. Xavier MARIMON - xmarimon@uic.es
Office hours
An appointment with the teacher must be arranged by institutional email.
In this course, the principle of the operation of the most important diagnostic imaging equipment will be presented. Next, the basic algorithms for image processing and their application in the field of biomedical images will be studied. Finally, Computer Vision will be studied in the biomedical field, i.e. the application of Artificial Intelligence algorithms for the automatic detection or measurement of patterns or characteristics in medical images.
To participate in the course, the following subjects must have been taken:
First year subjects
Calculus
Second year subjects
Computing
Third year subjects
Computing, Robotics and Bionics 1 (recommended, but not mandatory)
To describe the physical operation of the main diagnostic imaging equipment.
To describe what Digital Image Processing consists of and its usefulness.
To describe what Computer Vision is and its usefulness.
To know how to pre-process /process a medical image.
To know how to extract characteristics from a medical image.
Identify the functional parts /blocks of the different diagnostic imaging equipment.
Know and describe the radiological personal protection measures.
Know and describe the biological effects of radiation.
Describe and know how to reconstruct a tomographic image.
Describe and know how to use image enhancement algorithms.
Describe and know how to use image scaling and rotation algorithms.
Describe and know how to use image segmentation algorithms.
Know the different formats of medical images.
Know how to apply Deep Learning algorithms in an image.
Know how to extract relevant characteristics from a medical image.
Know how to use and program the RspberryPi hardware platform to acquire images in real time.
Know how to use and program the RspberryPi hardware platform to process images.
Block 1. Medical imaging devices
1.X-rays and Computerised Axial Tomography (CT).
2.Positron Emission Tomography (PET).
3.Single Positron Emission Computed Tomography (SPECT).
4.Magnetic resonance (MR).
5.Functional Magnetic Resonance (fMRI).
6.Ultrasounds (US).
Block 2. Image processing
1.Introduction to image processing.
2.Intensity transformations.
3.Spatial filtering.
4.Frequency filtering.
5.Geometric transformations.
6.Morphological image processing.
7.Image segmentation.
8.Feature extraction and Machine learning.
TRAINING ACTIVITY | METHODOLOGY | COMPETENCES |
Cooperative learning plays a significant role in the Bachelor’s degree in Bioengineering, its approach is based on organising activities inside the classroom so they become both a social and an academic learning experience. This type of learning depends on an exchange of information between students, who are motivated both to achieve their own learning and to increase the achievements of others. This activity covers practicums undertaken in a laboratory environment. Project-oriented learning is a method based on experiential and reflective learning in which the research process on a particular subject is of great importance. The aim is to resolve complex problems based on open solutions or tackle difficult issues that allow new knowledge to be generated and new skills to be developed by students. Lectures are the setting for: learning and managing the terminology and language structures related to each scientific field. Practicing and developing oral and written communication skills. And learning how to analyse the bibliography and literature on Bioengineering. Using guidelines to identify and understand the main ideas during lectures. This academic activity has been an essential tool in education since it first began and should have a significant presence within the framework of this degree programme. Case studies are a learning technique in which the subject is faced with a description of a specific situation that involves a problem, that must be understood, evaluated and resolved by a group of people through a process of debate. Case studies will generally be undertaken through group work, which promotes student participation, thus developing their critical thinking skills. It also prepares students for decision-making, teaching them to defend their arguments and contrast them with opinions from others in the group. Reading texts with the aim of engaging critical thinking plays a fundamental role in learning for citizens who are both aware and responsible. The professor sets out exercises and problems, helps students to progress in terms of the engineering process the design involves, and guides the student, thus partial goals are achieved that facilitate the incorporation of the theoretical knowledge acquired. An activity for outside the classroom. During this activity, students complete exercises autonomously, without the presence of a lecturer/professor. At this stage many questions always arise, but since they cannot be asked immediately then the student has to make more effort to understand them | Practical classes allow students to interact at first hand with the tools they will need to use in their work. In small groups or individually practical demonstrations will be carried out based on the theoretical knowledge acquired during the theory classes. In theory classes the fundamental and scientific knowledge that forms the basis of the knowledge and rigour that engineering studies require must be established. Group work is an essential tool in today’s society. In the field of bioengineering in which design and production processes are not carried out by an individual, it is essential to learn how to work as part of a team Individual work, involving study, the search for information, data processing and the internalisation of knowledge will allow students to consolidate their learning. | CB1 CB2 CB3 CB4 CB5 CE1 CE12 CE15 CE16 CE17 CE20 CE21 CE3 CE5 CG10 CG2 CG3 CG4 CG5 CG6 CG7 CG8 CG9 CT1 CT2 CT3 CT4 CT5 CT6 CT7 |
The final mark of the subject will be obtained as
Nota=0,4·Nef +0,3·Nlab+0,3·Ntreb
where
Nef: Final exam mark
Nlab: Lab mark
Ntreb: Coursework mark
No mid-term exam.
In order to pass the course, it is essential to carry out the laboratory exercises in the subject.
Important considerations:
Plagiarism, copying or any other action that may be considered cheating will score zero in that assessment. Moreover, plagiarism during the exams will mean the immediate failure of the whole subject.
In the second-sitting exams, the maximum mark students will be able to obtain is "Excellent" (a mark with honours distinction will not be possible).
Changes of the calendar, exam dates or the evaluation system will not be accepted.
Exchange students (Erasmus and others) or students resitting will be subject to the same conditions as the rest of the students.
Bibliography medical imaging
[1] John Enderle, Joseph Bronzino. 2011. Introduction to Biomedical Engineering, 3 ed. ISBN : 978-0123749796
[1] Bushong, Stewart. 2017. Manual de radiología para técnicos
ISBN: 9788491132028, 11 ed.
[2] Paolo Russo. 2018. Handbook of X-ray Imaging: Physics and Technology (Series in Medical Physics and Biomedical Engineering). ISBN:1498741525
Bibliography Digital Image Processing
[1] Gonzalez, Woods, and Eddins. 2018. Digital Image Processing, 4th Ed. ISBN: 9780982085417
[2] Gonzalez, Woods, and Eddins. 2020. Digital Image Processing Using MATLAB, 3rd Ed. ISBN: 9780133356724
E: exam date | R: revision date | 1: first session | 2: second session: