On April 23rd, 2024 at 2.30 pm the seminar "Embracing Intelligent Robotic Sonography Colleagues" will take place at DEIB BIO1 Room (Building 21) and on line by Webex.

Medical ultrasound is crucial for modern clinical intervention. Owing to the advantages of being real-time, affordable, and ionizing radiation-free, ultrasound imaging has been widely used for biometric measurement and diagnosis, in particular of internal organs. However, traditional ultrasound examinations are highly operator-dependent, as it is challenging to accurately maintain or replicate acquisition parameters (the contact force and relative orientation between a probe and a tested object), even for experienced sonographers.
The inter and intra-operator variations hamper the diagnosis accuracy, thereby further limiting the full clinical acceptance of ultrasound imaging. With the aim to improve clinical diagnostic accuracy and consistency, an intelligent robotic sonographer system is designed to automatically, accurately, and reliably accomplish image acquisition.

Dr. Zhongliang Jiang is a postdoctoral researcher and research leader of the Robotics and Ultrasound team (RobUSt) at the Computer Aided Medical Procedures (CAMP) Lab, at the Technical University of Munich, Germany. He received his Ph.D. in computer sciences with the highest distinction, “summa cum laude” at TUM. His research interests include medical imaging, robotic learning, human-machine interaction, and sensor-based real-time surgical state perception. Dr. Jiang has authored or co-authored over 30 publications in high-quality journals and conferences in the field of both robotics and medical imaging, including IJRR, MedIA, ARCRAS, TIE, TASE, TIM, TMRB, ICRA, IROS, and MICCAI. He won the award of the Best Paper Runner-up at MICCAI 2023. He is also one of the founders and main organizers of the series workshop on robot-assisted medical imaging (RAMI) at ICRA2023 and ICRA2024 and served as an associate editor for ICRA.