Management of carotid artery disease, towards preventing strokes, currently relies on a simple algorithm, which has proved insufficient for a large number of mostly asymptomatic subjects, posing a significant clinical challenge. Ultrasound imaging in combination with image analysis hold promise for addressing this challenge, through the in vivo estimation of morphological, mechanical and anatomical features of the carotid artery, the artery that takes blood to the brain.
This presentation highlights various advanced image analysis techniques applied on carotid ultrasound, in an attempt to identify novel risk markers and optimise disease management. Texture features, estimated from static images, describe different patterns of tissue allocation, presumably as a consequence of exerted stresses. Mechanical features, estimated from temporal image sequences, characterise tissue elasticity and are more sensitive to early tissue changes due to ageing or disease. Anatomical features, including arterial diameters, wall thickness and lesion size, can be automatically extracted using segmentation tools. These methodologies, along with biochemical and clinical indices, are integrated in a web-based platform, which relies on a semantically-aided architecture and allows for intelligent archival and retrieval of data, thus facilitating and enhancing the entire diagnostic procedure.
In view of the valuable information on lesion composition and stability revealed by ultrasound-image-based features, and the noninvasiveness and low-cost of ultrasound imaging, these approaches are directed towards improved risk stratification, increased patient safety and cost-efficiency. Their clinical usefulness remains to be demonstrated in large trials.
Spyretta Golemati is Assistant Professor in Biomedical Engineering and a member of the First Intensive Care Unit of the Medical School of the University of Athens.
Dr Golemati holds a Diploma in Mechanical Engineering from the National Technical University of Athens, Greece, and a M.Sc. and a Ph.D. degree in Bioengineering from Imperial College London, UK.
Her research interests include (a) medical image analysis, with emphasis on vascular ultrasound image analysis, (b) biosignal processing, and (c) vascular physiology and pathophysiology. She has co-authored 32 papers published in international scientific peer-reviewed journals, 12 book chapters, and 44 papers published in international scientific peer-reviewed conference proceedings. She has participated in 7 funded national and international research projects (in one, as co-ordinator). Dr Golemati has acted as reviewer of national and international research proposals as well as of papers submitted to international scientific journals and conferences. She is a member of the Institute of Electrical and Electronic Engineers [Engineering in Medicine and Biology Society (IEEE-EMBS), Ultrasonics, Ferroelectrics and Frequency Control (IEEE-UFFC)], the Technical Chamber of Greece, and the Hellenic Atherosclerosis Society. She is Associate Editor of the journal Ultrasonics. She is a grantee of the Fulbright Foundation-Greece for the academic year 2016-2017.
Thanksgiving Break – no seminar
Catheters play a key role in diagnosing and treating cardiac arrhythmia. Intracardiac echo (ICE) catheters enable real-time 2D ultrasound image acquisition from within the heart, however, manually steering ICE catheters inside a beating heart is a complex and time consuming task. The clinical use of ICE catheters is therefore limited to only a few critical tasks, such as septal puncture. At the Harvard Biorobotics Lab, we built a robotic system that can automatically steer four degree-of-freedom catheters, enabling real-time tracking of instruments within the heart and 3D visualization of cardiac tissue. In this talk, I will walk you through the design process in preparing our system for in vivo trials, and present results from our latest live animal experiment. I will describe the control strategies we employed to accurately steer these flexible manipulators in the presence of external disturbances (e.g. respiratory motion) and unmodeled motion of the catheter body. Finally, I will describe the GPU-accelerated image processing pipeline we used to generate 3D volumetric images of the heart in real-time from the 2D images acquired by the ICE catheter.
Alperen Degirmenci is a PhD candidate in Engineering Sciences at the Harvard John A. Paulson School of Engineering and Applied Sciences. He has been working in the BioRobotics Laboratory since 2012 under the supervision of Prof. Robert D. Howe. Alperen earned his M.S. degree from Harvard University in 2015, and a B.S. degree in Mechanical Engineering from the Johns Hopkins University in 2012, with minors in mathematics, computer science, robotics, and computer-integrated surgery. Alperen’s research at Harvard focuses on real-time, high-performance algorithm development for medical ultrasound image processing and robotic procedure guidance in catheter-based cardiac interventions.
Patients with peripheral field loss complain of colliding with other pedestrians in open-space environments such as shopping malls. Field expansion devices (e.g., prisms) can create artificial peripheral islands of vision. We investigated the visual angle at which these islands can be most effective for avoiding pedestrian collisions, by modeling the collision risk density as a function of bearing angle of pedestrians relative to the patient. Pedestrians at all possible locations were assumed to be moving in all directions with equal probability within a reasonable range of walking speeds. The risk density was found to be highly anisotropic. It peaked at ≈ 45° eccentricity. Increasing pedestrian speed range shifted the risk to higher eccentricities. The risk density is independent of time to collision. The model results were compared to the binocular residual peripheral island locations of 42 patients with forms of retinitis pigmentosa. The natural residual island prevalence also peaked at about 45° nasally but at about 80° temporally. This asymmetry results in a complementary coverage of the binocular field of view. Field expansion prism devices will be most effective if they can create artificial peripheral islands at about 45° eccentricities. The collision risk and residual island findings raise interesting questions about normal visual development.
Dr. Eli Peli earned a BSc in Electrical Engineering and an MSc in Biomedical Engineering from the Technion Israel Institute of Technology. He then came to Boston where he received his OD degree from the New England College of Optometry. Currently Dr. Peli is the Moakley Scholar in Aging Eye Research at Schepens Eye Research Institute, Massachusetts Eye and Ear, and Professor of Ophthalmology at Harvard Medical School. He also serves as Adjunct Professor of Ophthalmology at Tufts University School of Medicine. Since 1983 he has been caring for visually impaired patients as the director of the Vision Rehabilitation Service at the New England Medical Center Hospitals (now Tufts-Medical Center). Dr. Peli is a Fellow of the American Academy of Optometry, a Fellow of the Optical Society of America, a Fellow of the SID (Society for Information Display), and a Fellow of the SPIE (The International Society of Optical Engineering). He was presented the 2001 Glenn A. Fry Lecture Award and the 2009 William Feinbloom Award by the American Academy of Optometry, the 2004 Alfred W. Bressler Prize in Vision Science (shared with Dr. R. Massof) by the Jewish Guild for the Blind, the 2006 Pisart Vision Award by the Lighthouse International, the 2009 Alcon Research Institute award (shared with Dr. R. Massof), the 2010 Otto Schade Prize from the SID (Society for Information Display) and the 2010 Edwin H Land Medal awarded jointly by the Optical Society of America and the Society for Imaging Science and Technology. He was awarded an Honorary Degree of Master in Medicine by Harvard Medical School in 2002 and an Honorary Doctor of Science Degree from the State University of New York (SUNY) in 2006. Dr. Peli’s principal research interests are image processing in relation to visual function and clinical psychophysics in low vision rehabilitation, image understanding and evaluation of display-vision interaction. He also maintains an interest in oculomotor control and binocular vision. Dr. Peli is a consultant to many companies in the ophthalmic instrumentation area and to manufacturers of head mounted displays (HMD). He served as a consultant on many national committees, including the National Institutes of Health, NASA AOS, Aviation Operations Systems advisory committee, US Air Force, Department of Veterans Affairs, US Navy Postdoctoral Fellowships Program, US Army Research Labs, and US Department of Transportation, Federal Motor Carrier Safety Administration. Dr. Peli has published more than 200 peer reviewed scientific papers and has been awarded 9 US Patents. He edited a book entitled Visual Models for Target Detection with special emphasis on military applications and co-authored a book entitled Driving with Confidence: A Practical Guide to Driving with Low Vision.
This talk proposes a low-cost balloon observation system for sustained (week-long), broadly distributed, in-situ observation of hurricane development. The high-quality, high-density (in both space and time) measurements to be made available by such a system should be instrumental in significantly improving our ability to forecast such extreme and dangerous atmospheric events. Scientific challenges in this over-arching problem, which is of acute societal relevance, include:
Thomas R Bewley (BS/MS, Caltech, 1989; diploma, von Karman Institute for Fluid Dynamics, 1990; PhD, Stanford, 1998) directs the UCSD Flow Control and Coordinated Robotics Labs, which collaborate closely on interdisciplinary projects. The Flow Control Lab investigates a range of questions ranging from theoretical to applied, including the development of advanced analysis tools and numerical methods to better understand, optimize, estimate, forecast, and control fluid systems. The Coordinated Robotics Lab investigates the mobility and coordination of small multi-modal robotic vehicles, leveraging dynamic models and feedback control, with prototypes built using cellphone-grade electronics, custom PCBs, and 3D printing; the team has also worked with a number of commercial partners to design and bring successful consumer and educational-focused robotics products to market.
To Attend: email Rose Chase email@example.com
Location: 107 Malone Hall
Louis Whitcomb (JHU) and Thomas Bewley (UCSD)
This is an informal workshop and discussion session on the topic of
Linux-based robotics in education, with a focus on low-cost robots that
are easy and relatively inexpensive to deploy to students. UCSD’s
Professor Thomas Bewley will lead the discussion with a description of
the EduMIP, a ~$150 self-balancing two-wheeled robot that runs Linux,
and how he employs these robots in his classes. JHU’s Louis Whitcomb
will discuss his nascent use of the EduMIP with the RObot Operating
System (ROS) for his graduate course in robot systems programming.
There will be demonstrations.
Participants are invited to present a brief informal discussion of how
they use Linux-based robots in their curriculum.
Homepage for Tom Bewley’s MAE144 – Embedded Control & Robotics at UCSD
Homepage for Louis Whitcomb’s 530.707 Robot Systems Programming at JHU
Image-guided interventional systems rely on accurate device tracking technologies, such as optical or electromagnetic (EM) systems to navigate tools with high resolution diagnostic imaging modalities, such as CT/MRI/PET and facilitate the targeting of specific tissue within the body. However for MR-guided procedures such as Magnetic Resonance Navigation (MRN) which exploits the high magnetic field of an MRI scanner to steer magnetic nanoparticles embedded in drug-eluting beads (DEB), traditional tracking methods are not suitable to visualize catheters inside the patient’s vascular network. This talk will focus on the development of optical shape sensing devices which overcome the limitations associated with these past approaches with the ability to be integrated into sub-millimeter size tools. We present two MR-compatible solutions, using distributed fiber Bragg gratings (FBG) sensors and ultraviolet curing for optical frequency domain reflectometry (OFDR) measuring strain applied to a fiber triplet inserted in a tool and reconstruct the 3D shape during navigation. Recent phantom and ex-vivo experiments compare the accuracy to EM tracking and demonstrate the insensitivity towards external magnetic fields, illustrating the potential of these approaches for image guidance.
Samuel Kadoury is an associate professor in the Computer and Software Engineering Department at Polytechnique Montreal, member of the Biomedical Engineering Institute at the University of Montreal and researcher at the CHUM Research Center. He currently holds the Canada Research Chair in Medical Imaging and Assisted Interventions at Polytechnique Montreal. He obtained his Masters in Electrical Engineering from McGill University in 2005. After a one-year period at Siemens Corporate Research in Princeton, NJ, he returned to Montreal to complete his Ph.D. in biomedical engineering, focusing on orthopaedic imaging. He completed a post-doctoral fellowship at Ecole Centrale de Paris and worked as a clinical research scientist for Philips Research North America at the National Institutes of Health in Bethesda, MD from 2010 to 2012, developing image-guided systems for liver and prostate cancer. Prof. Kadoury has published over 100 peer-reviewed papers in leading journals and conferences in fields such as biomedical imaging, computer vision, radiology and neuroimaging. He holds 5 US patents in the field of image-guided interventions, has participated in the technological transfer of multiple research projects to commercial products, and was awarded the NIH merit award for his work on prostate cancer, as well as the Cum Laude Award from the RSNA for his work in artificial intelligence for liver cancer detection.