Abstract. In the last decade, several studies suggested that physical fitness may positively influence brain and cardiovascular health. Brain health is usually assessed through structural and functional imaging techniques to extract biomarkers of aging that can be used to predict brain age ( Dunås et al.
Abstract: Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancers, with lymph node metastasis (LNM) being a critical determinant in patient prognosis and therapeutic planning [1-2]. Conventional methods for detecting LNM in PDAC primarily rely on contrast-enhanced CT scans, but these often fall short in sensitivity, especially in early-stage disease.
The Computational Imaging Research (Albarqouni Lab) at the Clinic of Diagnostic and Interventional Radiology at the University Hospital Bonn is pleased to present a seminar on *Artificial Intelligence in Radiology: Applications and Research.* This cutting-edge seminar, spanning two semester hours per week (2 SWS), is specially curated for medical students to explore the transformative role of deep learning in medical imaging, with a focus on tasks such as classification, detection, segmentation, reconstruction, tracking, and disease progression.
Abstract. Conjunctival Melanocytic Intraepithelial Lesions (CMIL) are a significant precursor to conjunctival melanoma, a rare but potentially fatal ocular cancer. The histopathological classification of CMIL is crucial for early diagnosis and treatment planning.
We are excited to announce that Albarqouni Lab is proud to be one of the host institutions for the prestigious DAAD AInet Fellowship, which is awarded twice a year to outstanding international early-career researchers in artificial intelligence. This fellowship offers a unique opportunity to join the Postdoctoral Networking Tour in Artificial Intelligence (Postdoc-NeT-AI), where awardees can engage with leading researchers in Germany, fostering collaborations and creating new research and career opportunities. At Albarqouni Lab, we are at the forefront of AI research in medical imaging, machine learning, and large language models, and have successfully hosted several AInet Fellows in the past. We invite interested applicants to apply and consider joining us to advance cutting-edge AI research in healthcare. More details can be found [here](https://www.daad.de/en/the-daad/postdocnet/details-and-application/).
Abstract. Breast density is a critical factor in breast cancer risk and detection, influencing the effectiveness of mammography. Higher breast density, characterized by a greater proportion of fibroglandular tissue relative to fatty tissue, is associated with a four- to sixfold increase in breast cancer risk.
Abstract. Magnetic Resonance Imaging (MRI) plays a vital role in modern diagnostics, offering detailed, non-invasive insights into human anatomy [1-2]. High-field MRI (HF-MRI) systems, which operate at higher magnetic field strengths, provide superior image resolution and contrast compared to low-field MRI (LF-MRI) systems [3-4].
Our lab at Universitätsklinikum Bonn, The University of Bonn, and Helmholtz AI in cooperation with the Arab-German Young Academy of Sciences and Humanities (AGYA) are delighted to announce the upcoming AGYA Summer School on Affordable Artificial Intelligence (SAAI -سعي) in Bonn, 22-26 July 2024.
Abstract. Fetuses with diaphragmatic hernias face severe health and survival risks. Treatment and outcomes can be improved if this condition is detected early. Ultrasound measurement of the lung-to-head ratio (o/e LHR) is widely used in obstetric ultrasound procedures for the assessment of the observed to expected lung-to-head ratio.
Our lab at Universitätsklinikum Bonn, The University of Bonn, and Helmholtz AI in cooperation with the Arab-German Young Academy of Sciences and Humanities (AGYA) are delighted to announce the upcoming AGYA Summer School on Affordable Artificial Intelligence (SAAI -سعي) in Bonn, 22-26 July 2024.