Sommersemester 2024
Master Practical (Fortgeschrittenenpraktikum) "Deep Learning for Biomedical Image Analysis"
Field: | Biomedical Image Analysis, Machine Learning |
Scope: | 6 SWS, 8 ECTS |
Date: | Tuesday, 15:00-18:00, weekly (or by arrangement) |
Duration: | 16.4. – 23.7.2024 (or by arrangement) |
Place: | INF 267 (BioQuant), SR44 or online |
Lecturer: | |
Language: | English or German |
Content:
Students work on selected advanced topics in biomedical image analysis. The focus is on deep learning methods for automated analysis of biological microscopy images and medical images. Examples for topics are segmentation and tracking of cells in microscopy images, segmentation of organs or blood vessels, and registration of multimodal images of the human brain. The tasks comprise: Study relevant literature, learn theoretical foundations, design and implementation of image analysis methods and algorithms, test and evaluation of implemented methods, specification and development of software, presentation of results.
Requirements: Basic knowledge in Image Analysis (Computer Vision) or Machine Learning (Pattern Recognition)
Target group: MSc Data and Computer Science (8 ECTS) and related, MSc Molecular Biotechnology (8 or 4 ECTS)
First date: Tuesday, 16.4.2024, 15:00 (s.t.), SR44 (or by arrangement)
Type of course: Master Practical (Fortgeschrittenenpraktikum) (IFP)
Module handbook info: Modulhandbuch
Contact: PD Dr. Karl Rohr (k.rohr{at}dkfz.de, k.rohr{at}uni-heidelberg.de)