Mauricio Antonio Reyes Aguirre: Katalogdaten im Frühjahrssemester 2022

NameHerr Prof. Dr. Mauricio Antonio Reyes Aguirre
(Professor Universität Bern)
Erlenauweg 28
3110 Münsingen
Telefon031 631 59 50
DepartementInformationstechnologie und Elektrotechnik

227-0391-00LMedical Image Analysis
Basic knowledge of computer vision would be helpful.
3 KP2GE. Konukoglu, M. A. Reyes Aguirre
KurzbeschreibungIt is the objective of this lecture to introduce the basic concepts used
in Medical Image Analysis. In particular the lecture focuses on shape
representation schemes, segmentation techniques, machine learning based predictive models and various image registration methods commonly used in Medical Image Analysis applications.
LernzielThis lecture aims to give an overview of the basic concepts of Medical Image Analysis and its application areas.
Voraussetzungen / BesonderesPrerequisites:
Basic concepts of mathematical analysis and linear algebra.

Basic knowledge of computer vision and machine learning would be helpful.

The course will be held in English.
227-0449-00LSeminar in Biomedical Image Computing1 KP2SE. Konukoglu, B. Menze, M. A. Reyes Aguirre
KurzbeschreibungThis is a seminar lecture focusing on recent research topics in biomedical image computing, machine learning techniques related to interpreting biomedical images and medical data in general. Every week a different topic will be presented and discussed.
LernzielThe goal of this lecture is to provide a glimpse of the current research landscape to graduate students who are interested in working on biomedical image computing and related areas. Different topics will be covered by different speakers every week to provide a broad perspective and highlight current challenges. Every week students will be asked to read a paper, prepare discussion questions and participate in the discussion. Upon completion of this course, students will have a broad overview of the recent developments in biomedical image computing and ability to critically discuss a scientific article.
Voraussetzungen / BesonderesKnowledge in computer vision, machine learning and biomedical image analysis would be essential.