Theme 2. Biomedical Imaging and Image Processing

Trustworthy AI in Cancer Imaging Research

Minisymposia

Ioanna Chouvarda, Aristotle University of Thessaloniki, Greece Karim Lekadir, University of Barcelona, Spain
Fuensanta Bellvis Bataller, Quibim, Spain Sara Colantonio, CNR, Italy
Haridimos Kondylakis, ICS-FORTH, Greece
Alexandra Kosvyra, Aristotle University of Thessaloniki, Greece
João Santinha, Champalimaud Foundation, Portugal

Cancer research has been central in the biomedical community, seeking earlier and safer cancer diagnosis and prognosis, as well as better and more personalized treatment decisions. AI is increasingly receiving attention as a major component leveraging cancer imaging and multi-omics data analysis, towards these goals.

A key factor to ensure the success and impact of AI in cancer research and secure the wider adoption in clinical practice is the aspect of trustworthiness. This entails a multifaceted strategy in all phases of an AI service development, spanning from AI design to training and validation and including –among others– human oversight, technical robustness, data governance, transparency, fairness, and auditability. AI trustworthiness is currently moving from the definition of its theoretical framework capturing all trustworthiness perspectives to guidelines and best practices for its practical implementation. It is also evolving to incorporate the particularities of the cancer research areas and the needs of the w hole user spectrum. Incorporating explainability/interpretability in AI is an emerging field that is receiving lately much attention, while XAI validation is still an open issue that also involves several human aspects. As regards the much-discussed AI fairness, recent initiatives attempt to generate a framework based on best practices. Keeping in mind these multiple and diverse challenges and opportunities in the field of cancer research, the aim of this mini-symposium is to address the important questions: “How to design AI that is trustworthy”, and “How to validate AI trustworthiness” in the scope of AI for cancer imaging.

International Workshop on Biomedical Photoacoustics

Workshop

Wenfeng Xia, King’s College London, UK
Wiendelt Steenbergen, University of Twente, Netherlands
Nam Trung Huynh, University College London, UK
Sacha Noimark, University College London, UK
James Joseph, University of Dundee, UK
James Guggenheim, University of Birmingham, UK
Francis Kalloor Joseph, University of Twente,  Netherlands
Tianrui Zhao, King’s College London, UK
Mithun Kuniyil Ajith Singh, CYBERDYNE INC, Netherlands
Mengjie Shi, King’s College London, UK
Semyon Bodian, University College London, UK

Photoacoustic imaging (also called optoacoustic imaging) has undergone exponential growth over the last two decades, and it is now widely viewed as one of the most exciting biomedical imaging modalities. This hybrid imaging modality offers the unique capability of visualising tissue functional, molecular and structural information at scalable depth and spatial resolution. Many studies have demonstrated its tremendous potential in various preclinical and clinical applications. This workshop aims to bring together researchers in the field of biomedical photoacoustics to discuss the state-of-the-art, current challenges, research problems, and opportunities. This workshop includes invited talks from leading experts from both academia and industry with topics ranging from technological developments, to preclinical and clinical applications and commercialization.