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Glossary
Semester (Sem)
1First Semester
2Second Semester
AAnnual course
Educational activities
BIdentifying activities
Language
Course completely offered in italian
Course completely offered in english
--Not available
Innovative teaching
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)
  • Soft Skills
Course Details
Context
Academic Year 2018/2019
School School of Industrial and Information Engineering
Name (Master of Science degree)(ord. 270) - MI (471) Biomedical Engineering
Track BBB - Biomeccanica e biomateriali - Biomechanics and biomaterials
Programme Year 2

Course Details
ID Code 052383
Course Title BIOMEDICAL IMAGE PROCESSING LABORATORY
Course Type Mono-Disciplinary Course
Credits (CFU / ECTS) 5.0
Semester Second Semester
Course Description Class objectives 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. Course description 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 5) Thresholding 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 Laboratory activity 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. Prerequisites 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)
Educational activities SSD Code SSD Description CFU
B
ING-INF/06
ELECTRONIC AND INFORMATICS BIOENGINEERING
5.0
Innovative teaching The course includes  1.0  credits in Innovative Teaching as follows:
  • Blended Learning & Flipped Classroom

Schedule, add and removeAlphabetical groupProfessorLanguageCourse details
From (included)To (excluded)
--AZZZZCaiani Enrico Gianluca
manifesti v. 3.1.9 / 3.1.9
Area Servizi ICT
21/11/2019