Students

MA Thesis: Deep Learning based detection model of the temporal and axillary artery in suspected giant cell arteritis in ultrasound images -- Not available

Abstract. Giant cell arteritis (GCA) is a systemic autoimmune disease marked by inflammation of blood vessels (“vasculitis”) that can cause impairment and damage to organs [1]. GCA typically affects large and medium size arteries, such as the aorta and the temporal and axillary arteries [2–4].

Autumn School on AI (EEDA -- ايدا)

Welcome/Willkommen (de)/اهلا وسهلا (ar) to the AI Autumn School, one of the measures of our project on affordablE collaborativE learning for global Digital heAlth (EEDA – ايدا), a platform where academia meets innovation, and global collaboration sparks intellectual excellence. Through the partnership of Albarqouni Lab at the University Hospital Bonn, University of Bonn and Helmholtz Munich in Germany and the Faculty of Health Sciences at Beirut Arab University in Lebanon, we offer an enriching educational experience that marries cutting-edge AI advancements with multi-discplines through lectures, hands-on labs, and real-world hackathon led by faculty and skilled tutors.

Call for Participation at the Autumn School on AI (EEDA -- ايدا)

Our lab at Universitätsklinikum Bonn, The University of Bonn, and Helmholtz Munich in cooperation with the Faculty of Health Sciences at Beirut Arab University are delighted to announce the upcoming EEDA Autumn School on Artificial Intelligence (EEDA -- ايدا) in Bonn, 14-18 Dec 2023.

MA Thesis: Deep Learning based model for detection and grading of prostate cancer using mpMRI and MR-Fingerprinting -- Not available

Abstract. Prostate cancer (PCa) is the most common cancer in men and the second leading cause of cancer death in Germany [4,14]. Both digital rectal examination (DRE) along with the prostate-specific antigen (PSA) level in blood samples are typically used in PCa screening.

Course: Introduction to Machine Learning

Machine Learning has gained a lot of momentum within development organizations that are actively looking for innovative solutions to leverage their data to identify new levels of understanding their operations and processes. Machine learning is a subfield of Artificial Intelligence where the machine learns from data rather than from explicit programming.

Seminar: Federated Learning in Healthcare (SoSe2021)

Organizers: Dr. Shadi Albarqouni, Helmholtz AI and TU Munich, Prof. Nassir Navab, Chair for Computer Aided Medical Procedures, and Prof. Daniel Rueckert, Chair for AI in Medicine, TU Munich Time: Fridays, 10:00 - 12:00

Seminar: Federated Learning in Healthcare (WiSe2020)

Organizers: Dr. Shadi Albarqouni, Helmholtz AI and TU Munich, and Prof. Nassir Navab, TU Munich. Announcements - 17-12-2020: The deadline to submit the blog post is moved to 1st. Feb. 2021.

AI Week: Synergizing Human and AI for Multidisciplinary Solutions (SHAMS)

This 5-day intensive course is tailored for PhD students from diverse disciplines seeking a robust introduction to Artificial Intelligence (AI) and Machine Learning (ML). The module begins with essential mathematical concepts, including algebra, probability, and optimization, before moving into fundamental and advanced machine learning techniques. Students will explore deep learning architectures, engage in hands-on coding exercises, and apply their knowledge to real-world problems, with a particular focus on healthcare and resource-constrained environments. The course also addresses the ethical implications of AI and the importance of explainability in AI models, preparing students to implement AI solutions responsibly in their research.

Course: AI for Medical Diagnosis and Prediction (AAI643O)

This 8-week intensive course provides non-computer science students with the essential skills to apply AI in medical diagnosis and prediction. The course covers topics such as medical image classification, detection, segmentation, and reconstruction, as well as time-series classification, regression, forecasting, and learning techniques like weakly-, semi-, and self-supervised learning. Ethical considerations, fairness, and robustness in AI are also highlighted.

MA Thesis: Deep Learning-based method for virtual ECV in cardiac magnetic resonance imaging

Abstract. Diseases of the cardiovascular system are among the most common diseases worldwide and are the leading cause of death. The World Health Organization (WHO) estimates that about 17.9 million people die of cardiovascular diseases each year worldwide.