Jing Ren, PhD
Associate Professor, Department of Electrical, Computer and Software Engineering, Faculty of Engineering and Applied Science | University of Ontario Institute of Technology
Oshawa, ON, CANADA
Developing novel image registration methods for treatment planning to improve surgical outcomes
Biography
Advanced surgical techniques are creating new opportunities for minimally invasive surgeries which reduce trauma to the body and promote earlier patient recovery. Still, these surgeries pose greater challenges for surgeons since the surgical site is not visible. Image registration, the alignment and matching of similar features of multimodality images, is critical to improving patient outcomes.
Organs such as the lungs, liver and kidneys have few notable landmarks for image registration, yet blood vessels are clearly visible using CT and MRI scans, and provide useful features for these schemes. Jing Ren, PhD, Associate Professor in the Department of Electrical, Computer and Software Engineering, Faculty of Engineering and Applied Science, is exploring a vessel-based approach to improve image registration quality, and provide doctors with clearer, more accurate CT and MRI images to advance diagnosis and treatment planning for minimally invasive procedures. Her research will segment the blood vessels from the surrounding structures and tissues; and use extracted vessels to identify major landmarks in the organs for vessel-based image registration.
Dr. Ren has developed novel registration methods which combine feature-based and intensity based registration techniques to achieve fast registration speed. Along those lines, she is also developing fast deformable image registration methods since soft tissues and organs are often deformed in two images acquired at different conditions.
Already making major strides in her field, she has established a method for mapping the haptic rendering to the beating heart. In her lab, Dr. Ren simulated embedding a tumour under the skin of the heart, and using haptic force guidance, she removed it without damaging the heart or critical tissues or organs.
Intrigued by China’s early use of televisions and radios, Dr. Ren grew up with a keen interest in repairing circuits and earned her Bachelor of Electrical and Computer Engineering from Shandong University in Jinan, China in 1993, her Master and Doctorate of Electrical Engineering from the University of Western Ontario in 2003 and 2005, respectively. She joined UOIT in July 2006, following a postdoctoral fellowship at Imaging Research Laboratories, Robarts Research Institute in London, Ontario where her interest in medical imaging research was born.
Industry Expertise (4)
Education/Learning
Electrical Engineering
Information Technology and Services
Research
Areas of Expertise (13)
Advanced Control Systems
Advanced Image Processing
Electric Circuits
Intelligent Control Systems
Computer Architecture
Fuzzy Control Systems
Haptics and Virtual Reality
Imaging Processing
Soft Computing
Discrete Mathematics
Robotics
Introductory Electronics
Circuit Design
Accomplishments (1)
Natural Sciences and Engineering Research Council of Canada (NSERC) University Faculty Award (professional)
2006-01-01
Awarded $200,000 between 2006 and 2011 to conduct groundbreaking research to improve image registration for minimally invasive procedures.
Education (3)
University of Western Ontario: PhD, Electrical Engineering 2005
University of Western Ontario: MSc, Electrical Engineering 2003
Shandong University: BSc, Electrical Engineering 1993
Affiliations (2)
- Professional Engineers Ontario
- Institute of Electrical and Electronics Engineers
Languages (2)
- English
- Chinese
Media Appearances (2)
Research award puts $200,000 into heart of UOIT professor's cardiac research
University of Ontario Institute of Technology online
2006-09-21
Canada's Natural Sciences and Engineering Research Council (NSERC) has awarded Dr. Jing Ren, an assistant professor with UOIT's Faculty of Engineering and Applied Science, a $200,000 University Faculty Award (UFA) to further her research into improving technology that facilitates the use of computer-generated controls to minimize the invasiveness of cardiac surgeries. The NSERC UFA program enhances the recruitment, retention and early career progression of women and Aboriginal people in tenure-track faculty positions in science and engineering at Canadian universities by providing opportunities for them to establish a strong research record...
Research award hits Durham university in the heart
Oshawa This Week print
2006-09-26
To assist with cardiac research, Dr. Jing Ren has been awarded a $200,000 University Faculty Award from Canada's Natural Sciences and Engineering Research Council. The money will help Dr. Ren further her research on improving technology that facilitates the use of computer-generated controls to minimize the invasiveness of cardiac surgeries.
Event Appearances (4)
Accurate Seed Points Classification Using Invariant Moments & Neural Network
The 28th Canadian Conference on Electrical and Computer Engineering (CCECE) Halifax, Nova Scotia
2015-05-03
Adaptive Deformable Image Registration of Inhomogeneous Tissues
SPIE Medical Imaging Orlando, Florida
2015-02-21
Segmentation of the Liver from Abdominal MR Images: a Level-Set Approach
SPIE Medical Imagining Orlando, Florida
2015-02-21
Automatic Surface Reconstruction for Endoscopy-MR Image Fusion in Image Guided Procedures
26th Annual IEEE CCECE Regina, Saskatchewan
2013-05-05
Patents (2)
A Neuro-Fuzzy System for Estimation
CA Patent No. 2477919
2013-01-08
COCOMO, an algorithmic software cost estimation model is widely used by companies to predict project time and effort. When combined with Dr. Ren’s neuro-fuzzy inference system, predication accuracy improves significantly to 80 per cent.
System and Method for Software Estimation
U.S. Patent No. 7328202
2008-02-05
COCOMO, an algorithmic software cost estimation model is widely used by companies to predict project time and effort. When combined with Dr. Ren’s neuro-fuzzy inference system, predication accuracy improves significantly to 80 per cent.
Research Grants (2)
Vessel-Based Multi-Modality Deformable Image Processing
NSERC Discovery Grant $110000
2015-09-01
The long-term goal of this research is to design and develop a real-time, non-rigid, vessel-based treatment planning framework with minimum or no user interaction for soft moving organs such as the liver, the lungs and the kidneys. Over the next five years, Dr. Ren will develop fast deformable registration methods for minimally invasive therapeutic procedures; establish fast and accurate vessel segmentation techniques; investigate automatic fault detection and correction in image registration; and create ground truth datasets for evaluation.
Dynamic 3D Haptic Virtual Fixtures for Minimally Invasive Beating Heart Surgery
NSERC Discovery Grant $108000
2006-01-01
During this six year research project, Dr. Ren developed innovative segmentation techniques and extracted point features from stereo endoscopic images for 3D surface construction of the heart.
Courses (6)
Articles (5)
Dynamics Analysis of Car-Trailer Systems with Active Trailer Differential Braking Strategies
SAE International
2014-04-01
To date, various control strategies based on linear vehicle models have been researched and developed for improving lateral stability of car-trailer (CT) systems. Is a linear-model-based controller applicable to active safety systems for CT systems under emergency operating conditions, such as an evasive maneuver at high lateral accelerations? In order to answer the question, the applicability of an active trailer differential braking (ATDB) controller designed using a linear CT model is tested and evaluated, while the controller being applied to a CT system represented by a linear and a nonlinear CT model.
3D Surface Reconstruction of Stereo Endoscopic Images for Minimally Invasive Surgery
Biomedical Engineering Letters
2013-10-09
Surface to surface registration of MR and endoscopic images is the key to MR and endoscopic image fusion, which will provide the surgeon with better 3D context of the surgical site in minimally invasive procedures. However, accurate reconstruction of 3D surface from stereo endoscopic images is still a challenging task especially for the surgical site with few features. In this paper, we propose a new method to reconstruct 3D surface from stereo endoscopic images.
Endoscopy-MR Image Fusion for Image Guided Procedures
International Journal of Biomedical Imaging
2013-05-01
In this paper, we propose a rapid and accurate method to align intraoperative stereo endoscopic images of the surgical site with preoperative Magnetic Resonance (MR) images. Gridline light pattern is projected on the surgical site to facilitate the registration. The purpose of this surface-based registration is to provide 3D context of the surgical site to the endoscopic view. We have validated the proposed method on a liver phantom and achieved the surface registration error of 0.76 ± 0.11 mm.
A Comparative Study of Car-Trailer Dynamics Models
SAE International
2013-04-08
The paper examines typical vehicle dynamics models used for the design of car-trailer active safety systems, including active trailer braking and steering. A linear 3 degree-of-freedom (DOF), a nonlinear 4 DOF and a nonlinear 6 DOF car-trailer model are generated. Then, these models are compared with a car-trailer model developed with the commercial software package, CarSim.
Lateral Stability Improvement of Car-Trailer Systems Using Active Trailer Braking Control
Journal of Mechanics Engineering and Automation
2012-09-25
An active trailer braking controller to improve the lateral stability of car-trailer systems is presented. The special and complex structures of these types of vehicles exhibit unique unstable motion behavior, such as the trailer swing, jack-knifing and rollover. These unstable motion modes may lead to fatal accidents. The effects of passive mechanical parameters on the stability of car-trailer systems have been thoroughly investigated. Some of the passive parameters, such as the center of gravity of the trailer, may be drastically varied during various operating conditions.