Innovating in Medical Device Development

This is a hybrid event. You can also join remotely. Please see Teams link on the seminar webpage in booking url.

Miguel is a Research Engineer at University College London within the Advanced Research Computing Centre and WEISS where he is advancing AI-based Surgical Navigation tools. Previously, he was a Research Associate at King’s College London where he advanced research in Ultrasound-Guidance Procedures and AI-enabled echocardiography pipelines. In 2019, he was awarded a Ph.D. degree in Computer Engineering from the University of Birmingham, researching “Nonlinear Analysis to Quantify Movement Variability in Human-Humanoid Interaction”. His primary research interests are in developing data-centric AI algorithms for Medical Imaging, MedTech, SurgTech, Biomechanics and clinical translation. Additionally, his work includes generative models for fetal imaging, sensor fusion data from time-series and medical imaging, real-time AI for echocardiography, image-guided procedures, AI-based surgical navigation tools, and child-robot interaction in low-resource countries.

Development of Software as a Medical Device have shown progress in the last two decades due to rapid innovation and adaption of new technologies, good documentation and educational resources for students, researchers, academics, engineers and clinicians. However, research-driven technologies bring other challenges when using the latest generation of hardware and software, including the validation of new algorithms and the standardisation of data quality and data privacy to mention but a few. These challenges raise the question of how to quickly adopt the latest technologies (e.g., artificial intelligence, augmented reality, high-performance computing, etc) while still complying with relevant quality standards. Hence, Miguel is presenting his work and challenges on finding the right balance between innovation and regulations on clinical translation of different case studies in Ultrasound Imaging: needle tracking, echordiography classification in low-resource countries, GAN-based and Diffusion-based Fetal Ultrasound Image synthesis and Open-Source Software technologies aligning with medical regulations.