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102191-FS2026-0-Introduction to Image Analysis





Root number 102191
Semester FS2026
Type of course Lecture
Allocation to subject Biomedical Engineering
Type of exam not defined
Title Introduction to Image Analysis
Description 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

Teaching assistants:
Davide Scandella (davide.scandella@unibe.ch)
Seyedehsharareh Mirzargar (seyedeh.mirzargar@unibe.ch)

Course materials are regularly posted on Ilias (www.ilias.unibe.ch). The course website is here: https://ubern-image-analysis.github.io

Lectures: Lectures will consist of fourteen sessions of 2 hours each, including two exams.
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 be graded on their provided exercise sets.

Prerequisites:
• Course(s): Linear algebra, Calculus, a programming course
Skill(s):
• Programming: Experience with Python programming
• Mathematics: Linear algebra, calculus, and basic statistics

Recommended courses/skills:
• Course(s): Probability, Statistics
• Skill(s): Basic understanding of signals and systems

Required Material or Equipment:
• A laptop with Python installed. Instructions will be shared in the first lecture.

Textbook(s) and other reading material:
• "Digital Image Processing" by Gonzalez and Woods
• "Computer Vision: Algorithms and Applications" by Richard Szeliski
• "Deep Learning" by Goodfellow, Bengio, and Courville

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. Mauricio Reyes, ARTORG Center for Biomedical Engineering Research - Medical Image Analysis ✉
Dr. Hugo Armando Guillen Ramirez, Clinic of Visceral Surgery and Medicine, Visceral and Transplant Surgery ✉
Amith Jagannath Kamath, ARTORG Center - Artificial Intelligence in Medical Image Computing ✉
PD Dr. Pablo Márquez Neila, ARTORG Center - Artificial Intelligence in Medical Image Computing ✉
ECTS 3
Recognition as optional course possible No
Grading 1 to 6
 
Dates Wednesday 13:15-15:00 Weekly
 
Rooms Hörsaal S481, Chemie, Biochemie und Pharmazie, DCBP
Hörsaal U113, Chemie, Biochemie und Pharmazie, DCBP
 
Students please consult the detailed view for complete information on dates, rooms and planned podcasts.