Ongoing Research
The following is a list of ongoing research projects in the Laboratory for Enabling Technologies in Medical Ultrasound
Fourth Generation Portable Ultrasound Scanner
We are in the process of developing the fourth generation of a versatile, mobile ultrasound system, while the third generation system is undergoing clinical testing. Both systems are lightweight self-contained diagnostic ultrasound system, intended for use in a helicopter, an ambulance, at disaster and triage sites and in rural clinics. They are based on the Terason t3000 PC based ultrasound scanner system.
Quantitative 3D Freehand Ultrasound Imaging by use of Integrated Tracking System
Three-D imaging is widely used in MRI and CT imaging, and is gaining importance in medical ultrasound imaging as well, especially in obstetrics. The goal of the research is to develop a 3D imaging system with a position and orientation tracking sensor build into the transducer housing. This combines the flexibility of freehand 3D ultrasound with the accuracy of 2D matrix array transducer scanning. The work is carried out by Abraham (Bram) Goldsmith, MS student in Electrical and Computer Engineering.
3D Medical Ultrasound Image Segmentation
The goal of this research is to develop a robust automated system for the segmentation (boundary identification) of targets in 3D medical ultrasound images. Target structures include the prostate (cancer), free fluid volumes (such as abdominal bleeding), and cysts and lesions. Accurate and fast segmentation will allow doctors in the field to visualize 3D models of internal structures and fluid volumes as well as calculate statistics such as shape, volume, or track those statistics over time for a patient, giving the clinician additional diagnostic tools. The work is carried out by John David Quartararo, MS student in Electrical and Computer Engineering.
Wireless Transmission of Streaming Ultrasound through H.264 Compression
As part of the effort towards making ultrasound images available anywhere, we are developing real time video streaming capabilities of ultrasound images. Specifically, we are implementing this on our mobile ultrasound system, to operate on wireless networks, such as wireless LANs, 3G mobile phones, and satellite phone systems. Given the limited data rate (bandwidth), effective image compression is needed, such as H.264 (MPEG-4) compression is needed. The work is carried out by Naveen Mareddy and Aravind Krishman, MS students in Electrical and Computer Engineering.
Performance Metrics for Wireless Image Transmission
In order to assess the expected performance of various wireless data options for the portable ultrasound machine, such as wireless LANs, 3G mobile phones, and satellite phone, a testing protocol must be developed to accurately compare the performance under different options. The ultimate goal is to be able to accurately predict what level of performance can be expected from each data option given a specific application. The work is carried out by Brett Dickson, MS student in Electrical and Computer Engineering.
Virtual Interactive Training System for Trauma
This research deals with the development of an inexpensive, interactive ultrasound training system (ultrasound simulator) for EMS personnel (emergency department physicians and first responders), with the goal of training them to use diagnostic ultrasound effectively and quickly. The value of training simulators is well-known, and this training system can make imaging services more widely available in pre-hospital and emergency care and for rural medicine, leading to earlier detection and more effective treatment. The system can be used at clinics, hospitals, teaching centers, even at a physician's home. Although the system is specifically developed for EMS personnel, the concept is fully applicable to any field of medicine that can benefit from diagnostic ultrasound. The work is carried out by Christian Banker, MS student in Electrical and Computer Engineering.
Intelligent Algorithms – Detection of Pericardial Effusion
Intelligent Algorithms refers to image analysis software for assisting individual with modest training in medical ultrasound in making correct diagnostic decisions, in particular in screening and trauma situations. Examples of Intelligent Algorithms include automated detection of pneumothorax (collapsed lung) to be used for trauma situations; detection of pericardial effusion (fluid around the heart), to be used both in emergency medicine and for ICUs; assessment of the Left Ventricular Ejection Fraction (LVEF), to be used both in emergency medicine and for ICUs. The work up to now has been carried out by Oloruntomi (Tomi) Lasaki, MS student in Electrical and Computer Engineering.
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