Foundation AI Models in Biomedical Imaging (FAIBI)
Tuesday | April 15, 2025 | 9:00 – 11:30
Abstract: Foundation AI models are generalistic AI models that have recently garnered huge attention in the AI research community. Foundation AI models bring scalability and broad applicability and, thus, possess transformative potential in medical imaging applications, including (but not limited to) synthesis of medical image data, automatic report generation from radiology images, cross-lingual report generation, and image analysis. This workshop aims to explore new applications of foundations AI models in biomedical imaging with a focus on multimodal foundation models for multimodality medical data comprising medical images (radiology, pathology, fundus, etc), electronic health records, medical reports, radiomics, etc. Furthermore, the workshop will also provide a platform to identify the practical challenges of implementing foundation AI models in the biomedical imaging domains and the potential solutions related to the robustness, trustworthiness, and explainability of the medical foundation AI models. Thus, the workshop will offer an understanding of the impact of foundation AI models on the biomedical imaging domain. The workshop will comprise keynote presentations by experts, contributed paper presentations, poster sessions, and a panel discussion to encourage knowledge sharing, ideas exchange, and collaboration among the participants.
Hazrat Ali
University of Stirling, United Kingdom (Great Britain)
Rizwan Qureshi
University of Central Florida, USA
Jia Wu
MD Anderson, USA
Islem Rikek
Imperial College London, United Kingdom (Great Britain)
Open-source MONAI: Next-Generation Capabilities for Biomedical Imaging AI
Tuesday | April 15, 2025 | 15:00 – 17:30
Abstract: In this course we will provide an overview of MONAI’s well-established capabilities, and we will introduce two exciting new capabilities: generative AI for image simulation and vision-language models (VLMs) for medical image co-pilots. We demonstrate how to explore, use, and optimize these new features in biomedical research and product developments. We will also explore how to integrate MONAI with the tools you use every day: 3D Slicer, CVAT, Jupyter Notebooks, and cloud services. Finally, we will talk about and give LIVE demonstration of MONAI Label integration with ImPartial pathology interactive deep learning segmentation tool; attendees are encouraged to install the ImPartial framework from our GitHub (https://github.com/nadeemlab/ImPartial).
Stephen R Aylward
NVIDIA & The University of North Carolina at Chapel Hill, USA
Jayashree Kalpathy-Cramer
University of Colorado (CU) School of Medicine, USA
Gunjan Shrivastava
Memorial Sloan Kettering Cancer Center
Preclinical and Clinical Applications of Photoacoustic Imaging
Thursday | April 17, 2025 | 8:00 – 11:00
Abstract: This workshop will focus on the preclinical applications and clinical translation of photoacoustic imaging (PAI), a hybrid imaging technique that combines optical and ultrasound modalities to provide high-resolution, functional, and molecular information from deep within biological tissues. The session will explore cutting-edge advancements in PAI and its transformative potential in areas such as cancer detection, vascular imaging, and functional brain imaging. The topic is highly relevant to the IEEE ISBI conference, as it bridges the gap between engineering innovation and biomedical applications, aligning with the conference’s focus on biomedical imaging and signal processing. By emphasizing the translational impact of photoacoustic imaging, this session will provide valuable insights into how cutting-edge imaging technologies can address real-world clinical challenges, attracting interest from researchers, clinicians, and engineers.
Lei S. Li
Rice University, USA
Jun Xia
University of Buffalo SUNY, USA