Joint projects with the Brain & Mind Research Institute
BMRI contacts: Prof. Steven Meikle (steven.meikle@sydney.edu.au); Prof. Roger Fulton
(roger.fulton@sydney.edu.au); Dr Will Ryder (will.ryder@sydney.edu.au); Dr Andre Kyme
(andre.kyme@sydney.edu.au).
EIE contacts: Assoc. Prof. Philip Leong (philip.leong@sydney.edu.au); Dr Alistair McEwan
(alistair.mcewan@sydney.edu.au).
Overview and Significance
The medical imaging physics and bio-modelling group, located at the Brain and Mind Research
Institute in Mallet St, Camperdown, develops novel instrumentation and computational
methods for imaging the structure and function of organs in humans and animals using
radiation. Research focuses on several tomographic (cross-sectional) imaging techniques –
positron emission tomography (PET), single photon emission tomography (SPECT), and
computed tomography (CT). The technologies and methods developed by our group ultimately
lead to an improved understanding of the brain and the causes and treatment of disease. We
rely on a multidisciplinary team of researchers (physicists, engineers, computer scientists) using
a wide variety of research tools: from Monte Carlo simulation, modelling, programming, sensor
development and signal processing through to experiments with phantoms and live animal and
human subjects.
Note: It is not required that students have a background in biology/chemistry/biomedical
science for these projects.
Summary of projects
BMRI_01 – Photon attenuation in PET brain imaging of freely moving animals
BMRI_02 – Partial volume effect in PET brain imaging of freely moving animals
BMRI_03 – Simulating novel systems for PET imaging of freely moving animals
BMRI_04 – Optimised design for a simultaneous PET/MRI brain imaging system
BMRI_05 – Development of a novel scanner for breast cancer detection
BMRI_06 – Software development for PET scanner performance testing
BMRI_07 – Data-driven motion tracking of head motion in CT
BMRI_08 – Human head motion tracking in medical imaging using the Microsoft Kinect®
BMRI_09 – Markerless motion tracking for human PET imaging
Project descriptions
BMRI_01 – Photon attenuation in positron emission tomography (PET) brain imaging of freely
moving animals (1 student)
(Contact: Prof. Steven Meikle steven.meikle@sydney.edu.au)
Project description: We have developed a system that enables the brain of an awake, freely moving
rat to be imaged while we simultaneously study its behaviour (in response to environmental or drug
stimuli, for example). The system is based on a commercial microPET scanner, an animal enclosure
under robot control, and an optical motion tracking system. However, we still lack an understanding
of the impact that attenuation of the photons emitted by the radiopharmaceutical within the brain
has on the measurements and images obtained using this system. In this project, the student will
simulate microPET measurements from a moving rat and investigate the impact of photon
attenuation on biological parameters of interest (e.g. receptor binding). This project will establish
the necessary methodology for making unbiased measures of brain function during simultaneous
PET/behavioural studies. This important development will aid the study of complex brain disorders
such as anxiety, depression, drug addiction and psychosis.
This project would suit an honours or Masters level student (with possible extension to PhD) with a
background in physics, biomedical engineering or computer science.
BMRI_02 – Impact of partial volume in positron emission tomography (PET) brain imaging of freely
moving animals (1 student)
(Contact: Prof. Steven Meikle steven.meikle@sydney.edu.au)
Project description: We have developed a system that enables the brain of an awake, freely moving
rat to be imaged while we simultaneously study its behaviour (in response to environmental or drug
stimuli, for example). The system is based on a commercial microPET scanner, an animal enclosure
under robot control, and an optical motion tracking system. Unfortunately, the so-called partial
volume effect (PVE) causes underestimation of regional brain radiopharmaceutical concentration
due to the finite point spread function (PSF) of the reconstructed brain images. In this project, the
student will investigate the effect of the temporal and spatially varying PSF on brain measurements
during imaging studies where the animal is awake and free to move. This important development
will aid the study of complex brain disorders such as anxiety, depression, drug addiction and
psychosis.
This project would suit an honours or Masters level student (with possible extension to PhD) with a
background in physics, biomedical engineering or computer science.
BMRI_03 – Monte Carlo simulation of novel systems for simultaneous brain PET and behavioural
studies of freely moving animals (1 student)
(Contact: Prof. Steven Meikle steven.meikle@sydney.edu.au)
Project description: Preclinical positron emission tomography (PET) scanners are designed to image
a motionless rodent under anaesthesia and are typically configured as a vertically oriented ring of
detectors. Using such a system, we have shown that it is possible to image the brain of an awake,
freely moving rat using optical motion tracking and a modified image reconstruction algorithm that
accounts for the animal motion. However, the method results in a significant loss of data when the
animal moves outside the field of view of the detectors and it also suffers from non-uniform spatial
resolution due to parallax error at the edges of the scanner ring. In this project, the student will
conduct Monte Carlo simulations to investigate novel designs for a PET system specifically intended
for awake animal imaging which overcomes the limitations of the current system. The outcome will
be one or more tomograph designs that optimise data acquisition during awake animal imaging,
including minimising data loss and parallax error. The project will therefore feed into a larger project
to develop the world’s first dedicated awake animal PET imaging system.
This project would suit an honours or Masters level student (with possible extension to PhD) with a
background in physics, biomedical engineering or computer science.
BMRI_04 – Optimised design for a simultaneous PET/MRI brain imaging system (1 student)
(Contact: Dr Will Ryder will.ryder@sydney.edu.au or Prof. Steven Meikle
steven.meikle@sydney.edu.au)
Project description: Simultaneous positron emission tomography (PET) and magnetic resonance
imaging (MRI) (termed “PET-MRI”) of the brain will allow functional, anatomical and physiological
images to be acquired at the same time. The PET component of the brain scanner would need to
have a high spatial resolution and sensitivity. Ideally, the image resolution would be less than
1.5mm. In this project, the student will conduct Monte Carlo simulations with different detector
combinations and geometries to optimise the design parameters. This will involve investigation of
detector configurations and estimation of the depth of photon interaction to allow a uniform
resolution across the field of view. The simulations will be used in the development a proof of
concept magnetic resonance compatible PET brain scanner.
This project would suit an honours or Masters level student (with possible extension to PhD) with a
background in physics, biomedical engineering or computer science.
BMRI_05 – Development of a novel PEM-MR prototype scanner for breast cancer detection (1
student)
(Contact: Dr Will Ryder will.ryder@sydney.edu.au or Prof. Steven Meikle
steven.meikle@sydney.edu.au)
Project description: Breast cancer is one of the biggest killers of women worldwide. Positron emission
tomography (PET) is widely used to detect and localise malignancies in the body. However, the use of a
dedicated Positron Emission Mammography (PEM) scanner has been shown to outperform whole-body PET
scanners in mammography investigations. Magnetic resonance imaging (MRI) is more sensitive then PEM at
detecting lesions and better for determining the need for mastectomy. On the other hand, PEM has greater
specificity than MRI. Therefore, due to their complementary strengths we hypothesize that integration of PEM
and MRI in a single imaging device will improve diagnostic performance for cancer detection. In this project,
the student will investigate the performance of a prototype PEM system, making comparisons between
theoretical and experimental performance of detector configurations. This information will be used to
develop a Monte Carlo simulation to predict the optimal detector configuration for an MR compatible PEM
scanner, with target spatial resolution of 1-2mm.
This project would suit an honours or Masters level student (with possible extension to PhD) with a
background in physics, biomedical engineering or computer science.
BMRI_06 – Development and validation of software for NEMA-compliant PET performance testing (1
student)
(Contact: Prof. Roger Fulton roger.fulton@sydney.edu.au)
Project description: An international software project has been established on sourceforge.net
(http://sourceforge.net/projects/pet-accept) with the aim of developing open source software for
the measurement of positron emission tomography (PET) scanner performance parameters such as
spatial resolution, sensitivity and count rate capability. The student will contribute to the
development of image analysis programs to measure these parameters in conformance with the
NEMA 2007 standard, which specifies procedures for acquisition and analysis of the test data. As a
contributor to the project the student will be listed on the project website and may have an
opportunity to contribute to a peer reviewed publication about the project.
This project will suit an honours or Masters level student with some prior exposure to programming
in a language such as IDL, Matlab, Java or C.
BMRI_07 – Data-driven motion tracking of rigid head motion in CT (1 student)
(Contact: Prof. Roger Fulton roger.fulton@sydney.edu.au)
Project description: Head motion is a very common problem in computed tomography (CT) imaging,
causing blur and distortion of the reconstructed image. Researchers at the University of Sydney have
developed an effective motion correction method, which uses optical motion tracking to measure
the rigid motion of the head during the CT scan. The method would be even more useful in the
clinical situation if the motion data could be obtained by examination of the CT projection images
themselves, rather than requiring an external motion tracking system. The general approach would
be to analyse projection-to-projection changes in the appearance of the object in successive
projection views obtained as the gantry rotates, and compare these with the changes that would be
expected as a result of gantry rotation alone, in order to estimate object motion. This method has
been investigated previously in single photon emission computed tomography. The student will
survey previous work on data-driven motion estimation, and conduct a preliminary study of its
feasibility in CT using real CT data sets, where the true motion will be known from optical tracking.
This project would suit an honours or Masters level student (with possible extension to PhD) with
some prior exposure to programming in a language such as IDL, Matlab, Java or C.
BMRI_08 – Head motion tracking of humans using Microsoft Kinect® (1 student)
(Contact: Prof. Roger Fulton roger.fulton@sydney.edu.au or Dr Andre Kyme
andre.kyme@sydeny.edu.au)
Project description: Head motion is a very common problem in tomographic imaging (e.g. PET,
SPECT, CT and MRI), causing blur and distortion of the reconstructed 3D images. Researchers at the
University of Sydney are developing effective motion correction methods for these various
modalities – so that patients and animals can be effectively imaged while moving. All of these
methods require accurate and rapidly-sampled head pose information which are synchronised with
the scan data. In this project, the student will investigate the feasibility of using Microsoft Kinect® to
obtain this head pose information for human imaging. Microsoft Kinect® is a relatively recent
product from Microsoft Research comprising the sensor unit from the X Box 360 together with a
powerful SDK for processing the input from the three cameras. The SDK functionality includes face
recognition, skeleton modelling and depth perception. The student will gain hands-on experience
with Microsoft Kinect to assess its suitability for motion tracking in a medical imaging context. If the
system proves useful, the project will lead into implementing the system clinically for phantom and
patient evaluation.
This project would suit an honours or Masters level student with a background in physics, biomedical
engineering or computer science.
BMRI_09 – Adapting markerless motion tracking to human PET imaging (1 student)
(Contact: Prof. Roger Fulton roger.fulton@sydney.edu.au or Dr Andre Kyme
andre.kyme@sydeny.edu.au)
Project description: Head motion is a very common problem in tomographic imaging (e.g. PET,
SPECT, CT and MRI), causing blur and distortion of the reconstructed 3D images. Humans and
animals can be imaged while moving provided the motion is measured and accounted for in the
image reconstruction. Researchers at the University of Sydney have developed a promising way of
estimating the motion without the need to attach any markers to body. Instead, it uses stereo
matching between highly distinctive native features on the object, viewed by multiple cameras.
Currently this method has not been tested on humans. In this project, the student will analyse the
feature detection for human faces and compare motion measurements with marker-based tracking.
This will lead into implementing the tracking with a PET scanner designed for human imaging,
performing an initial validation study using phantoms and volunteers.
This project would suit an honours or Masters level student (with possible extension to PhD) with a
background in physics, biomedical engineering or computer science.