With this function you can construct your weekly calendar of lessons, which is customized on the basis of the courses that you intend to follow. Warning: the personal schedule does not replace the presentation of the study plan! It's an informal tool that can help you better manage the organization of class attendance before the study plan presentation. After the study plan presentation we recommend you to use the Lecture timetable service in your Online Services.
To create your customized schedule follow these instructions:
Click on the "Enable" link to proceed. You will be asked your surname and first name in order to determine your alphabetic grouping.
To add or remove courses from your personal schedule, use the small icons which are found next to the courses:
addition of the course
removal of the course
selection of the section of the Laboratory of Architecture (Note: the effective area in which the teaching will be carried out will be determined after the presentation of the Study Plans)
The sidebar on the left displays the number of lessons included in schedule. There are also these commands:
View the schedule: allows the viewing of the weekly synoptic schedule
Delete the schedule: cancels the selections made
When you have finished the entry, you can print the calendar you have made.
Course completely offered in italian
Course completely offered in english
The credits shown next to this symbol indicate the part of the course CFUs provided with Innovative teaching. These CFUs include:
Subject taught jointly with companies or organizations
Blended Learning & Flipped Classroom
Massive Open Online Courses (MOOC)
School of Industrial and Information Engineering
(Master of Science degree)(ord. 270) - MI (471) Biomedical Engineering
BIF - Bioingegneria dell'informazione - Information Bioengineering
BIOMEDICAL IMAGE PROCESSING LABORATORY
Credits (CFU / ECTS)
The main goal of this class is to provide to the student the theoretical and practical basis for biomedical image processing, in particular using the Matlab Image Processing toolbox.
This is an example of the topics which will faced during the class:
1) Introduction to Matlab
2) Dicom format, color space, multiframe array e movie creation, image enhancement
3) Characteristics of biomedical images, compression algorithms
4) 2D convolution and filtering
6) Edge detection
7) 2D Fourier transform, algebric operations between images, filtering in the frequency domain, Radon transform
8) Unsharp filter, filter design
9) Morphological image processing: basic concepts and advanced operations
10) Deep learning
11) Spatial interpolation and image registration
12) Polar representation and 3D Visualization
13) Image restoration
There is not a distinction between laboratory and theory activity. In the classroom, the application of the basic concepts presented above to different biomedical images (MRI, ultrasounds, RX, TAC, etc.) will be discussed, pointing out the processing techniques available to address the major problems, and the methods applied to extract quantitative parameters utilized in the clinical practice as an aid to the qualitative interpretation. The active involvement in the class is highly reccomended for the positive outcome of the final examination.
Expected learning results
Knowledge of basic strategies in image processing, ability to understand and code the proper solution in view of a practical problem relevant to biomedical image processing.
Modalitā di valutazione: evaluation of 3-4 projects that will be assigned during the semester, every 2-3 weeks, to be completed singularly or as group work, based on the solution of practical image processing problems. The final vote will be constituted by the sum of the projects' evaluations. Following oral exam is not mandatory.
Attivitā di Didattica Innovativa: To complement the project activities and to stimulate active learning, the structuring skills of thinking and knowledge and the assessment among colleagues, at least one project will be assigned as group project, that will be then discussed and presented in flipped/blended classroom modality. Such modality could be also applied to the evaluation of the assigned projects.
It should be noted that this is a limited number access course. The mandatory procedure for access request is here (http://www.ccsbio.polimi.it/?page_id=27&lang=en)
Even if not mandatory for attending the class, a pre-existing knowledge of Matlab programming and of biomedical signal processing techniques is reccomended for the comprehension of the discussed arguments.
Scientific-Disciplinary Sector (SSD)
ELECTRONIC AND INFORMATICS BIOENGINEERING
The course includes 1.0 credits in Innovative Teaching as follows: