The I-STAR Laboratory

Faculty and Staff

Dr. Jeff Siewerdsen founded the I-STAR Lab as a collaborative endeavor among technical disciplines (such as engineering and physics) and clinical disciplines, such as radiology, surgery, and radiation therapy. He is primary faculty in Biomedical Engineering and Principal Investigator on topics of image quality and cone-beam CT applications in diagnostic and image-guided procedures. He leads a program of interdisciplinary research spanning projects in medical imaging physics, diagnostic radiology, and image-guided interventions. His core interests include the physics of medical imaging, with a focus on advanced x-ray CT and spectral imaging modalities, the mathematics of image quality, the design of novel imaging systems for new applications, and 3D deformable image registration. Strong collaboration with experts in surgery, radiation therapy, and radiology guides and accelerates the translation of new technologies into early clinical application.

More information: Hopkins BME/~siewerdsen

Dr. Web Stayman is faculty in Biomedical Engineering and Principal Investigator on topics of advanced 3D image reconstruction with applications in diagnostic radiology, and image-guided interventions. With over 15 years of experience in tomography and other imaging applications, his expertise includes both emission tomography and transmission tomography (CT, tomosynthesis, and cone-beam CT). He leads research activities in advanced 3D reconstruction, including model-based statistical / iterative reconstruction, regularization methods, and modeling of imaging systems. He leads development of a generalized framework for penalized likelihood (PL) reconstruction combining statistical models of noise and image formation with incorporation of prior information, including patient-specific prior images, atlases, and models of components / devices known to be in the field of view. His research includes algorithm development and physical experimentation for imaging system design and optimization.

Dr. Wojtek Zbijewski is a physicist whose research interests include x-ray CT image reconstruction, Monte Carlo modeling, and the development and novel imaging systems. He leads activities in imaging system instrumentation throughout the I-STAR Lab, including cone-beam CT, photon counting CT, and and advanced volumetric imaging for extremities imaging in musculoskeletal radiology, orthopaedics, and rheumatology. He obtained his PhD from University of Utrecht, the Netherlands, under the supervision of Dr. F. Beekman. His background includes the development of statistical reconstruction algorithms for x-ray CT and scatter correction methods for cone-beam CT using accelerated Monte Carlo techniques. His experience includes industrial R&D, where his work involved the design of specialized cone-beam CT systems for image-guided surgery, ENT, and dental applications.

Dr. Wang is a research scientist with expertise in imaging physics and dual-energy CT. His research involves the development of novel 3D imaging techniques for image-guided surgery for improved image quality and reduced radiation dose. Methods for model-based reconstruction in cone-beam CT offer the capability to image with sparse projections at low dose and with reduced artifacts. Adam also works on the development of new dual-energy CT imaging techniques, including modeling of image quality, the development of low-noise decomposition / reconstruction methods, and application to new platforms for dual-energy and photon-counting CT.

Dr. Yoshito Otake is a research fellow in the Department of Computer Science at Johns Hopkins University and recipient of a JSPS Postdoctoral Fellowship for Research Abroad. His work includes the integration of novel surgical navigation and visualization systems for intraoprative guidance. He leads research and mentors students in the development of novel tracking systems, video augmentation techniques, GPU-accelerated (CUDA) algorithms for image registration and reconstruction, and streamlined integration with C-arm cone-beam CT within the TREK software architecture.

Dr. Muhit is a research scientist in the I-STAR Lab at Johns Hopkins University, where he works on the development and application of a new cone-beam CT imaging system for musculoskeletal radiology, orthopaedics imaging, and rheumatology. Muhit works closely with Dr. Carrino in applying the novel scanner in early patient trials designed to evaluate imaging performance. He is also developing novel methods for dual-energy CT and kinematic imaging of the joints. Muhit earned his Ph.D. from the University of New South Wales, Canberra Australia, where his research included novel 3D-2D registration techniques in kinematic analysis of CT and fluoroscopic images.

Dan Mirota is a Postdoctoral Fellow in Computer Science and Biomedical Engineering, earning his PhD in Computer Science at Hopkins in 2012. His work includes development of video registration methods for high-precision fusion of endoscopic video with cone-beam CT. His research interests include computer vision, medical image analysis, and computer-aided surgical systems. His current work focuses on robust analysis of structure-from-motion for augmented reality in transnasal neurosurgery and surgical training. Such work offers to overcome limitations of conventional, tracker-based video-CT registration through high-precision registration of 3D video and intraoperative cone-beam CT. His undergraduate studies included the creation of an expert system for MR cardiac perfusion analysis at Siemens Corporate Research.

Hao Dang is a PhD student in the Department of Biomedical Engineering at Johns Hopkins University doing his rotation project in the I-STAR Lab. His research includes development of advanced 3D image reconstruction methods for image-guided interventions. His past research includes automatic image-world registration in surgical navigation, integrating C-Arm cone-beam CT with real-time tracking in seamless workflow. Other work includes intraoperative registration update methods for robotic skull drilling and novel similarity metrics and saliency-based hierarchy models for accurate 3D-3D image registration.

Grace Gang is a PhD student working on the development of mathematical models of image quality for advanced x-ray imaging systems. Her graduate work involves cascaded systems analysis of tomosynthesis and cone-beam CT - theoretical models combining 3D Fourier metrics (noise-equivalent quanta) with mathematical descriptions of anatomical background and imaging task. Her undergraduate work included deformable registration using mutual information in a dual-energy chest radiography. Her groundbreaking work: demonstrating agreement of theoretical models for 3D detectability with real observer preformance in tomosynthesis and cone-beam CT.

Sajendra (Saj) Nithiananthan is a Ph.D. student in the Department of Biomedical Engineering at Hopkins. His research interests include intraoperative imaging, image analysis, and image-guided surgery with a focus on deformable image registration for cone-beam CT-guided surgical procedures. His thesis involves the development and validation of deformable registration techniques for high-quality C-arm cone-beam CT guidance, including: a fast morphological pyramid implementation of the Demons algorithm for 3D-3D registration within time constraints consistent with intraoperative use; CT-to-CBCT registration accounting for image intensity errors; the effect of tissue resection on deformable registration; translation of methods to preclinical studies in image-guided surgery.

Sureerat ("Ja") Reaungamornrat is a Ph.D. student in the Department of Computer Science at John Hopkins University and a recipient of the Royal Thai Government Scholarship. Her current research involves the development of piecewise-rigid deformable image registration for image-guided spine surgery. Her previous work at Hopkins included the development of the registration framework for cone-beam CT (CBCT)-guided transoral robotic surgery, integrating Gaussian mixture and Demons deformable registration. She received her M.Sc degree from the Department of Computer Science at John Hopkins University in 2011 on the topic of surgical guidance using CBCT. She received her B.Eng degree from King Monkut’s Institute of Technology, Bangkok, Thailand in 2007, and she worked as a research assistant at the Department of Biomedical Engineering, Mahidol University, Bangkok, Thailand in 2008, where her research included surgical navigation and autonomous rescue robots.

Ali Uneri in a PhD student in Computer Science at Hopkins and works on the development and integration of new surgical navigation tools for use in image-guided procedures. His thesis includes the the design and development of the TREK software architecture for intraoperative imaging and surgical guidance, combining open-source 3D Slicer and CISST libraries for surgical navigation based on intraoperative cone-beam CT. His core research includes the development of fast 3D-2D registration and high-quality 3D image reconstruction methods for surgical guidance. He also works on novel surgical tracker configurations, real-time thoracoscopic video augmentation, and methods for deformable image registration in thoracic surgery. His previous experience includes the development of surgical robotics for knee and hip replacement procedures.

Jen Xu is a PhD student in Biomedical Engineering at Hopkins. Her PhD project involves the development, characterization, and modeling of photon counting detectors and new methods for photon counting spectral (dual-energy) CT. She previously worked on the technical assessment of a new cone-beam CT scanning system for ENT and maxillofacial imaging undergoing trials at Johns Hopkins Hospital. Her work includes modeling and expermientation of single-energy and spectral cone-beam CT image quality on both the flat-panel CBCT Imaging Bench and photon counting CT bench, helping to standardize methods for characterization of the CBCT noise-power spectrum (NPS), noise-equivalent quanta (NEQ), and dosimetry for volumetric beams.

Zhe Zhao is a PhD student research assistant from Tianjin University. As a graduate student in the College of Precision Instrument and Opto-Electronic Engineering, she combines a knowledge of biomedical sensors, electronics, and signal processing in developing new forms of high-quality 3D image reconstruction. Her work at Johns Hopkins includes the development of a robust penalized likelihood (PL) framework for cone-beam CT, including high-speed implementations on GPU, incorporation of prior image data (including deformable registration of priors), and analysis of low-dose limits of image quality in PL model-based reconstruction.

I-STAR COLLABORATORS

Dr. John Carrino is Section Chief of Musculoskeletal Radiology at Johns Hopkins University. He received his MD from Geoge Washington University and MPH from the Harvard School of Public Health. His core interests include spine imaging, novel MR imaging techniques, health services research, and radiology informatics. He is involved in a number of collaborative projects, notably in the field of musculoskeletal diagnostic imaging. He collaborates closely with the I-STAR Lab in the development of a dedicated cone-beam CT system for extremities imaging, a system for high-quality portable dual-energy imaging for the ICU, and in image quality analysis, ROC studies, and CT dosimetry.

More information: Hopkins Radiology/~carrino

Dr. Gregory Hager is Professor and Chair of the Department of Computer Science at Johns Hopkins University. His principal areas of research are computer vision and robotics, and his application interests are in the area of medical devices and human-machine systems. He directs the Computational Interaction and Robotics Lab (CIRL). He is also the Deputy Director of the NSF Engineering Research Center for Computer-Integrated Surgical Systems and Technology (ERC-CISST). He was elected a Fellow of the IEEE in 2006 for his contributions to computer vision and robotics. He collaborates with the I-STAR Lab in the development of high-precision video-CT registration for C-arm cone-beam CT-guided head and neck / skull base surgery.

More information: http://www.cs.jhu.edu/~hager

Dr. Junghoon ('Daniel') Lee is faculty in the Department of Electrical and Computer Engineering (ECE) and the Engineering Research Center for Computer-Integrated Surgical Systems and Technology (ERC-CISST) at Hopkins. His interests include statistical signal/image processing and computer-assisted interventions. His work includes modeling of 3D image quality in tomosynthesis and cone-beam CT and the development of novel 3D image reconstruction techniques, particularly incorporating prior information (e.g., preoperative image and/or statistical atlas models) in 3D reconstruction from sparse and/or short-scan data. His background includes research in image-guided neurosurgery, virtual simulation in cardiac surgery, simultaneous 3-D reconstruction and classification of viruses in electron microscopy, ASIC design, and telemetry for the total artifical heart.

Dr. Jerry Prince joined the faculty at Johns Hopkins University in 1989, where he is the William B. Kouwenhoven Professor of Electrical and Computer Engineering. He holds joint appointments in the Departments of Radiology and Biomedical Engineering and a secondary appointment in Applied Mathematics and Statistics. He is also Associate Director for Research of the Engineering Research Center for Computer Integrated Surgical Systems and Technology (ERC-CISST). His research interests are in image processing and computer vision with application to medical imaging. He collaborates with the I-STAR Lab on image quality models, observer performance, image registration, and advanced reconstruction techniques.

More information: http://www.iacl.ece.jhu.edu/Prince

Dr. Jeremy Richmon is head and neck surgeon and expert in robotic-assisted surgery. He has helped to pioneer new approaches in minimally invasive, robotic-assisted thyroidectomy and base of tongue surgery. His clinical expertise includes head and neck cancer, microsvascular reconstruction, and tumors of the oral cavity, salivary glands, pharynx, larynx, sinuses, and skull base. Collaboration with I-STAR includes the development of advanced image-guidance and image registration techniques for integration in trans-oral robotic-assisted surgery.

More information: Hopkins Otolaryngology-HNS

Dr. Russ Taylor is the Director of the NSF Engineering Research Center for Computer-Integrated Surgical Systems and Technology (ERC-CISST). His work focuses on robotics in medicine, image-guided interventions, medical imaging and modeling, and integration of advanced interventional systems. The theme underlying a broad spectrum of research in his laboratories is the basic insight that information-based technologies can have similar impact in computer-integrated medicine as they have had on computer-integrated manufacturing techniques. He collaborates closely with the I-STAR Lab on topics of image-guided interventions and advanced image reconstruction and modeling techniques.

More information: http://www.cs.jhu.edu/~rht/

Research Administration

Tom Judy is a research administrator for the Department of Biomedical Engineering and primary point of contact for the I-STAR Lab on matters pertaining to budget, purchasing, and general administration. An administrator and research manager by day, Tom is also the Captain of the Baltimore Ravens cheerleaders stunt team! Go Ravens!

The I-STAR Laboratory
Department of Biomedical Engineering | Johns Hopkins University
Traylor Building, Room 726 | 720 Rutland Avenue | Baltimore, MD 21205