Medical Imaging

BA/MA Thesis: Deep Learning for Inherited Retinal Diseases Detection -- Not available

Abstract. Our project aims to improve the diagnosis of Inherited Retinal Dystrophies (IRDs), a group of rare retinal diseases impacting over 2 million people globally [1]. IRDs can lead to vision problems like night blindness, color blindness, tunnel vision, and eventual blindness, greatly affecting patients’ and their families’ quality of life [4].

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].

Open Medical Inference (OMI)

BMBF Funded Project through Medical Informatics Initaitive (MII) consortia (2024-2028)

Affordable AI and Collaborative Federated Learning for Global Healthcare (EEDA)

DAAD Funded Project with Beirut Arab University, Lebanon (2023-2023)

Deep learning to estimate aging from chest imaging

The 3-year DFG Funded project with UniKlinikum Freiburg (2023-2026)

Utilising Artificial Intelligence in Cancer Imaging To Improve Patient Outcomes

Bonn-Melbourne Research Excellence Fund (2023-2024)

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.

FLamby: Datasets and Benchmarks for Cross-Silo Federated Learning in Realistic Healthcare Settings

Federated Learning (FL) is a novel approach enabling several clients holding sensitive data to collaboratively train machine learning models, without centralizing data. The cross-silo FL setting corresponds to the case of few (--) reliable clients, …

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.

Joint Self-Supervised Image-Volume Representation Learning with Intra-Inter Contrastive Clustering

Collecting large-scale medical datasets with fully annotated samples for training of deep networks is prohibitively expensive, especially for 3D volume data. Recent breakthroughs in self-supervised learning (SSL) offer the ability to overcome the …