Dr. Axel Krieger
Dr. Axel Krieger is an Assistant Professor of Mechanical Engineering at the Johns Hopkins University. Dr. Krieger’s work focuses on the development of novel tools, imaging, and robot control techniques for medical robotics. Specifically, Dr. Krieger investigates methodologies that (i) increase the smartness and autonomy and (ii) improve image guidance of medical robots to perform previously impossible tasks, improve efficiency, and improve patient outcomes.LEARN MORE
Here are our amazing team members at the IMERSE Lab.
Xiaolong Liu, PhD
Onder Erin, PhD
Medical Robotic Systems
Michael Kam, MS
Jiawei Ge, MS
Seda Aslan, MS
Computational Fluid Dynamics
Lydia Zoghbi, MS
Justin Opfermann, MS
Trevor Schwehr, BS
Idris Sunmola, BS
CS PhD Student
AI in Surgical Robotics
Noah Barnes, BS
Jesse Haworth, BS
Qiyuan Wu, BEng
Computational Fluid Dynamics Surgical Planning
Our work focuses on both basic research and translational research in the development of novel tools, imaging, and robot control techniques for medical robotics. Specifically we investigate methodologies that (i) increase the smartness and autonomy and (ii) improve image guidance of medical robots to perform previously impossible tasks, improve efficiency, and improve patient outcomes.
Smart Surgical Systems
Increased autonomy has transformed fields such as manufacturing and aviation by drastically increasing efficiency and reducing failure rates. While pre-operative planning and automation has also improved the outcomes of surgical procedures with rigid anatomy, practical considerations have hindered progress in soft-tissue surgery mainly because of unpredictable shape changes, tissue deformations, and motions limiting the use of pre-operative planning.
Magnetic Suturing Systems
Magnetic fields can exert forces and torques onto remote magnetic surgical tools that is located inside of the patient’s body, and obviate the physical connections with the standard robotic arm structures. This property of magnetic robotics provides a promising alternative to miniaturize the surgical tools for the next generation of surgical systems, where less tissue trauma and more patient comfort in clinics. As a target medical application, we focus on magnetic suturing, where the needle is magnetic and can be guided to penetrate into the tissue to complete a suturing task. Our research continues towards enhancing the penetration capability and system-level intelligence via merging the digital and physical intelligence.
Semi-Automatic Planning and Three-Dimensional Electrospinning of Patient-Specific Grafts for Fontan Surgery
This work aims to develop a semi-automatic tissue engineered vascular graft (TEVG) planning method for designing and 3D-printing hemodynamically optimized Fontan TEVGs. We present a computation framework by parameterizing Fontan grafts to explore patient-specific vascular graft design space and search for optimal designs. We employed nonlinear constrained optimization technique to minimize indexed power loss of Fontan grafts while keeping hepatic flow distribution (HFD) and percentage of abnormal wall shear stress (%WSS) within clinically acceptable thresholds. Our work significantly reduces the collaborative effort and turnaround time between clinicians and engineering teams for designing patient-specific hemodynamically optimized TEVGs.
Image Guided Interventions and Planning
Diagnostic imaging has dramatically improved over the years, where now small tumors and defects are often detectable before affecting a patient’s health. However, in many cases imaging during intervention and surgery is limited to basic color cameras, resulting in missed tumors and sub-optimal surgical results.
Cardiac Surgical Planning
For complex congenital heart disease (CHD) involving a single functioning ventricle, the Fontan operation is performed which results
in a circulation where deoxygenated venous blood passively flows into the pulmonary arteries without a ventricular pump. However, conventional fontan graft designs may result in suboptimal cardiovascular emodynamics leading to post-surgical complications.
Novel Robotic Actuators
We are developing new actuation schemes for precision guidance of needles and other surgical implements that will allow for complex procedures such as Deep Anterior Lamellar Keratoplasty (DALK) to be performed faster and more precisely, using robotic methods.
READ ABOUT OUR WORKJournal PublicationsConference PublicationsAbstracts and Other Conference Papers
Latest News from Our Lab
Congratulations on the Student Initiatives Fund
Congratulations to Justin and Jiawei for being awarded a Student Initiatives Fund (SIF) with the project “Fluorescent Suture with AI-Based Surgical Planner for Image Guided Surgery.”Read more
News on NIBIB: Robot Performs Soft Tissue Surgery with Minimal Human Help
National Institute of Biomedical Imaging and Bioengineering (NIBIB) has featured our recent study published in Science Robotics on the NIBIB webpage.Read more
Baltimore Sun: Johns Hopkins engineers build robot to perform surgery without a doctor
Johns Hopkins engineers build robot to perform surgery without a doctorRead more
Please reach out if have any questions about the research or opportunities.
Axel Krieger, PhD
Department of Mechanical Engineering
Whiting School of Engineering
Johns Hopkins University
Email: [email protected]
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