July 6, 2017 - Alexis Cheng

Calibration and Tracking in Intraoperative Ultrasound with Active Acoustic and Photoacoustic Point Localization

Location: Malone 107
Time: 2:00 pm - 4:00 pm


Image-guided therapy is a central part of modern medicine. By incorporating medical imaging into the planning, surgical, and evaluation process, image-guided therapy has helped surgeons perform less invasive and more precise procedures. Of the most commonly used medical imaging modalities, ultrasound imaging offers a unique combination of cost-effectiveness, safety, and mobility. Advanced ultrasound-guided interventional systems will often require calibration and tracking technologies to enable all of their capabilities. Many of these technologies rely on localizing point-based fiducials to accomplish their task.

In this talk, I introduce various methods for localizing active acoustic and photoacoustic point sources. The goals of these methods are (1) to improve localization and visualization for point targets that are not easily distinguished under conventional ultrasound and (2) to track and register ultrasound sensors with the use of active point sources as non-physical fiducials or markers.

We applied these methods to three main research topics. The first is an ultrasound calibration framework that utilizes an active acoustic source as the phantom to aid in in-plane segmentation as well as out-of-plane estimation. The second is an interventional photoacoustic surgical system that utilizes the photoacoustic effect to create markers for tracking ultrasound transducers. We demonstrate variations of this idea to track a wide range of ultrasound transducers (three-dimensional, two-dimensional, bi-planar). The third is a set of interventional tool tracking methods combining the use of acoustic elements embedded onto the tool with the use of photoacoustic markers.


Alexis Cheng was raised in Vancouver, British Columbia. He received a Bachelor’s degree in Electrical and Computer Engineering from the University of British Columbia in 2011, and a Master’s degree in Computer Science from Johns Hopkins University in 2013. During his studies as a PhD candidate in the department of Computer Science at the Johns Hopkins University, he was involved in 6 journal articles, 19 conference publications, 8 abstracts, and 4 patents. He won the MUUSS fellowship in 2012, the best poster award at CARS in 2014, and the Professor Joel Dean Excellence in Teaching Award in 2016. His research interests include ultrasound-guided interventions, photoacoustic tracking, and surgical robotics.