Impedance tomography for cardiac imaging: high speed tomography

Summary

This project will involve the development of a high speed 3D Electrical Impedance Tomography device for chest imaging to determine pulmonary and cardiac function.

Supervisor(s)

Professor Alistair McEwan, Associate Professor Craig Jin, Professor Philip Leong

Research Location

Electrical and Information Engineering

Program Type

Masters/PHD

Synopsis

Electrical Impedance Tomography is a relatively new imaging method that traditionally uses a ring of external electrodes to image impedance changes in 2D within the body. The technology has recently
been described as being on the verge of clinical application for pulmonary monitoring with medical device manufactures offering 2D imaging systems for trial (Bodenstein et al, Critical Care Medicine,
2009). There is also clinical need to image the heart in intensive care but physicians find echocardiograms difficult due to the presence of bone and the ventilated state of the lungs.   The resolution of EIT is limited by the number of measurements, electrode location and the 2D nature of acquisition.  For providing the optimum information on cardiac function it is important to measure a sufficient number of frames within a single cardiac cycle.  In collaboration with clinicians at Westmead hospital this project will aim to increase the measurement speed, use of internal electrodes and other methods to improve image resolution.

Keywords

Biomedical Instrumentation, Signal Processing, Medical Electronics, Cardiology

Opportunity ID

The opportunity ID for this research opportunity is: 949

Other opportunities with Professor Alistair McEwan

• Medical diagnostics for neonates in the developing world
• Electrical Impedance Tomography for stroke, biophysical monitoring and medical device design
• Novel Electrodes for rapid electrophysiological recording
• Implant electrode optimisation and neurolinguistics
• Subdivided electrodes to improve defibrillators and physiological measurements
• Electrical impedance modelling for implants
• Magnetic resonance electrical impedance tomography
• Development of a microwave catheter for cardiac ablation to treat ventricular tachycardia
• Resuscitation monitors for the neonatal intensive care uni (NICU)
• ARTIFICIAL INTELLIGENCE/MACHINE LEARNING ASSISTED NEWBORN CRITICAL CARE (VIRTUAL CRITICAL CARE MODELING)
• Mapping 2D Images to 3D Shape
• New technique for studying human brain activity
• Next Generation Audio Coding
• Spherical multi-modal scene analysis
• Statistical models of ear shape and ear acoustics
• FPGA-based Low Latency Trading
• Floating Point FPGA Architectures
• Placement-aware Hardware Description Languages
• Scalable vision machines
• Modelling Parkinson's disease using control models
• Binaural signal processing algorithms for hearing aids
• FPGA-based low latency machine learning

Other opportunities with Associate Professor Craig Jin

• Pattern analysis techniques for sound synthesis
• Interpolation of binaural impulse responses for virtual auditory displays
• Sound field recording and recreation
• Beamforming with acoustic vector sensors - Multiple acoustic source localisation using acoustic vector sensor arrays
• Speech separation and localisation using particle filtering
• Mapping 2D Images to 3D Shape
• New technique for studying human brain activity
• Next Generation Audio Coding
• Spherical multi-modal scene analysis
• Statistical models of ear shape and ear acoustics
• Binaural signal processing algorithms for hearing aids
• Electrical Impedance Tomography for stroke, biophysical monitoring and medical device design
• Medical diagnostics for neonates in the developing world
• FPGA-based Low Latency Trading
• Floating Point FPGA Architectures
• Placement-aware Hardware Description Languages
• Scalable vision machines
• Modelling Parkinson's disease using control models
• Novel Electrodes for rapid electrophysiological recording
• FPGA-based low latency machine learning

Other opportunities with Professor Philip Leong

• other research opportunities available at Faculty of Engineering
• FPGA-based Low Latency Trading
• Floating Point FPGA Architectures
• Placement-aware Hardware Description Languages
• Domain-specific Languages for GPU-based Computing
• Scalable vision machines
• Modelling Parkinson's disease using control models
• FPGA-based low latency machine learning
• FPGA control of photonic systems
• Test
• Mapping 2D Images to 3D Shape
• New technique for studying human brain activity
• Next Generation Audio Coding
• Spherical multi-modal scene analysis
• Statistical models of ear shape and ear acoustics
• Medical diagnostics for neonates in the developing world
• Electrical Impedance Tomography for stroke, biophysical monitoring and medical device design
• Novel Electrodes for rapid electrophysiological recording
• Binaural signal processing algorithms for hearing aids