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102191-FS2025-0-Introduction to Image Analysis





Root number 102191
Semester FS2025
Type of course Lecture
Allocation to subject Biomedical Engineering
Type of exam not defined
Title Introduction to Image Analysis
Description All information on this course (timetable, exams, course description) is still preliminary.

Auditors (Gasthörer) are not admitted to this course.

Course type: lecture / lab

Module: Mandatory Courses / Major Module "Image-Guided Therapy"

Selection criteria: 1. BME students with the Major Module "Image-Guided Therapy"; 2. AIM students; 3. Bioinformatics students; 4. Other BME students. PhD students or students from other study programs are admitted to this course if free places are available.

For questions on course and exam registration contact bme.artorg@unibe.ch

Course materials are regularly posted on Ilias (www.ilias.unibe.ch).

Lectures: Lectures will consist of fourteen sessions of 2 hours each.
Lab sessions: Lab sessions will consist of fourteen 1 hour-long sessions.
Lab sessions will be organized as follows:
- Students will be presented with homework sets with both theoretical and programming exercises. Material in the exercises will be from the course material covered in class.
- Students will work on homework sets and have the opportunity to ask questions to the teaching assistants.
- Students will work on a team project during the last quarter of the semester
- Students will be graded on their provided exercise sets.

Prerequisites: Linear algebra, Calculus, a programming course

Recommended courses/skills:
- Course(s): Probability, Statistics
- Skill(s): Knowledge in Python

Required Material or Equipment:
- A laptop with Python installed.

Textbook(s) and other reading material:
" Mark Lutz, "Learning Python" (5th Edition, O'Reilly)
" Alasdair McAndrew "A computational introduction to digital image processing (2nd edition)

Course policies and classroom rules of conduct:
• Academic dishonesty, plagiarism, and any other kind of fraud will lead to the exclusion from the course.
• Punctuality
• No radios, audio/cd player, earphones
• No food and beverages in the classroom
ILIAS-Link (Learning resource for course) Registrations are transmitted from CTS to ILIAS (no admission in ILIAS possible). ILIAS
Link to another web site Further information for this course
Lecturers Prof. Dr. Raphael Sznitman, ARTORG Center - Artificial Intelligence in Medical Image Computing ✉
Dr. Pablo Márquez Neila, ARTORG Center for Biomedical Engineering Research ✉
ECTS 3
Recognition as optional course possible No
Grading 1 to 6
 
Dates Wednesday 13:15-15:00 Weekly
 
Rooms Hörsaal U113, Chemie, Biochemie und Pharmazie, DCBP
 
Students please consult the detailed view for complete information on dates, rooms and planned podcasts.