MSc Projects 2014-15

Here is a list of projects being offered for MSc students in the Department.
For details of deadlines and for registering submissions, see the Moodle page. Full instructions are available here.

Monitoring cognitive brain functional activation using novel optical instrumentation.

Supervisors: Ilias Tachtsidis and Antonia Hamilton

Near infrared spectroscopy (NIRS) is a non-invasive optical technique which can be used to monitor the oxygenation and haemodynamic response following neuronal activation in specific regions of the brain. The concentration of some tissue absorbers, such as water, melanin, remain virtually constant. However, the absorption of oxygenated-haemoglobin (HbO2) and deoxygenated-haemoglobin (HHb) is dependent on the tissue oxygenation and haemodynamics, which can change during brain functional activation. This project is part of an exciting collaboration between the Biomedical Optics Research Laboratory and the Institute of Cognitive Neuroscience at UCL that aims to deliver novel measurements to investigate brain cognitive function through the use of optical (near infrared) technologies. We have recently acquired a novel wireless NIRS device that allows remote monitoring of brain function during cognitive tasks. For example, participants might be asked to do a social decision making task or a hand action task while brain activity in prefrontal cortex is recorded with NIRS. The main aims of this MSc project are to (1) assist in experimental data collection that will involve brain functional activation experiments in healthy volunteers; and (2) to analyse oxygenation and haemodynamic data from these experiments. The student will learn how to operate the optical instrument and use novel software tools that will allow quantification of the optical measurements and then will focus on analysing. The larger scope of the analysis is to investigate the use of NIRS technology to monitor brain function during cognitive tasks. This project would be suitable for a student with an interest in neuroscience; and will involve data collection, data processing and some statistical analysis.

Student: (Project available)

Exploration of the implementation of combined magnetic resonance and optical methods for assessment of brain metabolism and haemodynamics: application to a preclinical model of birth asphyxia.

Supervisors: Ilias Tachtsidis and Pardis Kaynezhad

Perinatal cerebral hypoxic-ischemia (HI) is a condition resulting from reduced oxygen delivery or/and blood flow occurring either in utero or during delivery. It occurs in 1 to 2 per 1000 live births and can result in physical or sensoreal handicap or fatality. Although there are significant advances in the treatment of asphyxiated babies, little is known about the effects of these neuroprotection strategies on brain blood perfusion and metabolism following HI. This project is part of an exciting collaboration between the Perinatal-Brain Magnetic-Resonance Group at UCH and the Biomedical Optics Research Laboratory at UCL that aims to deliver novel measurements to investigate the effects of brain neuroprotection through combination of magnetic resonance and optical (near infrared) technologies. The main aims of this MSc project are to (1) assist in experimental data collection; and (2) to analyse imaging, perfusion and metabolic data, from the optical instruments, obtained from piglet brains in-vivo after HI. The student will learn how to operate the optical instrument and use novel software tools that will allow quantification of the optical measurements and then will focus on analysing those in conjunction with the magnetic resonance imaging & spectroscopy measurements. The larger scope of the analysis is to investigate the benefits of implementing treatment in birth asphyxiated infants. This project would be suitable for a student with an interest in optical technologies, physiology/pathophysiology, brain tissue biochemistry; and will involve data collection, data processing and some statistical analysis.

Student: (Project available)

Investigation of the optical measurements of oxygenation and haemodynamic changes in neonatal injury.

Supervisors: Ilias Tachtsidis and Gemma Bale

Neonatal encephalopathy (NE) is the clinical presentation of disordered neonatal brain function. The incidence of hypoxic-ischaemic encephalopathy (HIE) is 1-3 per 1000 live births1 - with a term birth rate of 750,000 births in the UK, the number of affected term infants is estimated to be 750-1125 infants annually in the UK. The chain of events leading to NE is complex and multifactorial. There is a need to improve understanding of the timing and evolution of neonatal brain tissue’s response to injury using non-invasive bedside tools, which can provide robust markers of injury. Near-infrared spectroscopy (NIRS) is a promising optical tool for neuromonitoring, which has been applied widely to assess cerebral perfusion and oxygenation in the newborn. In particular NIRS measures in brain tissue changes in the oxidation state of cytochrome c oxidase (oxCCO), oxy- and deoxy- haemoglobin concentrations (HbO2, HHb) and cerebral tissue oxygen saturation. As part of a collaboration between the Biomedical Optics Research Laboratory and UCLH studies have already performed in injured and pre-term babies and they are on-going. The student will require to analyse the data and investigate the relationship between the optical brain tissue measurements and systemic variation (such as blood pressure, arterial oxygen saturation). This project is a mixture of signal and statistical analysis. This project will take place at both (i) the Biomedical Optics Research Laboratory at UCL the UK’s leading research group in biomedical optics, which offers expertise and facilities in optical instrumentation and methodologies and (ii) the UCLH where patient’s recruitment will be done.

Student: (Project available)

Reconstruction techniques in quantitative susceptibility mapping.

Supervisors: Enrico Kaden and Daniel Alexander

Magnetic susceptibility quantifies the degree to which a sample is magnetised after placing it in a magnetic field. Susceptibility weighting imaging (SWI) is an MRI technique able to measure this material property noninvasively. As different types of tissue may give rise to different susceptibilities, image contrast is generated that enables us to discriminate between brain structures based on their physico-chemical composition. In particular, this imaging technique can detect excessive iron deposition, which is an important marker for neurodegenerative diseases, has shown potential to track demyelinating disorders like multiple sclerosis, and allows the in-vivo quantification of cerebral microbleeds and intracranial calcification. This project aims to develop reconstruction techniques for the estimation of susceptibility-related tissue features in the human brain, which typically cannot be observed directly from the measured signals. Rather, we need to solve an ill-posed inverse problem which links the MR measurements to the underlying tissue material. These quantitative mapping methods include phase unwrapping, background field removal, and dipole inversion in order to recover the magnetic susceptibility in the cerebral white matter. A solid background in mathematics and physics as well as working knowledge in MATLAB, C/C++, or a similar programming environment are required.

Student: (Project available)

Anaysis of edge-illumination based x-ray phase contrast images of breast tumours

Supervisors: Alessandro Olivo and Paul C. Diemoz

X-ray phase contrast imaging is a new imaging modality not based on x-ray attenuation, in which all details in an image are made more evident by intense edge-enhancing fringes running along their borders. This also results in making classically undetectable objects (as they oppose non absorption to x-rays) visible in the image. This method produced unprecedented results in the imaging of breast tissues, where it proved it could visualize lesions previously undetectable (or at a stage at which they are not yet detected by conventional methods). This result was obtained at synchrotrons, huge, complicated and very expensive facilities – only approximately 50 of which exist in the world. This notwithstanding, the above result was so revolutionary that it triggered the construction of the first facility for in vivo x-ray phase contrast mammography at a synchrotron in Italy, despite the very limited number of patients it can handle. More recently, the UCL team has developed a method that could make similar results achievable with conventional sources. This could make the above result widely available in hospitals and clinics across the world, allowing an earlier detection of breast tumours and consequently a reduction in the mortality rate. The team is currently using the method to image a large number of breast tissue samples containing tumours to achieve statistical significance. The student would participate in the data analysis by comparing absorption and phase contrast images of the same breast tissue sample, and quantitatively assessing the improvements brought by the latter. If time allows, synchrotron images would also be provided to allow a comparison of the UCL images against the “gold standard”. The student will gain skills in data and especially image analysis, and familiarize with some of the basic concepts of medical imaging. Basic computing skills are required.

Student: (Project available)

Characterization of detector performance for x-ray phase contrast imaging

Supervisors: Marco Endrizzi and Alessandro Olivo

X-ray phase contrast imaging is a new imaging modality which exploits interference and refraction effects instead of x-ray absorption. As a consequence, it has the potential to radically transform all applications of x-ray imaging (first and foremost diagnostic radiology), as it increases the visibility of all details in an image and it enables the detection of features classically considered x-ray invisible. For many years, this modality was considered to be restricted to very specialized facilities called synchrotrons, but our group has recently developed a method which makes it work with conventional x-ray sources, thus potentially enabling its clinical translation. This method however is highly affected by the performance of the used x-ray detector. Not only does this include classic parameters like noise, spatial resolution and detector response as a function of energy, but also more sophisticated and method-specific ones like signal spill-out between adjacent pixels. The student will be required to thoroughly characterize the available x-ray detectors (especially a state-of-the-art direct conversion flat panel detector based on amorphous selenium), and assess the impact of the extracted parameters on the phase contrast performance of the devices. The skills the student will gain go beyond phase contrast imaging and also cover many aspects of x-ray detector technology and characterization, which are relevant to diagnostic radiology in general.

Student: (Project available)

Exploring the limits of the quantitative retrieval of x-ray phase

Supervisors: Paul C. Diemoz and Alessandro Olivo

X-ray phase-contrast imaging (XPCi) allows the generation of images with highly improved contrast compared to conventional X-ray imaging techniques. While the latter are based on measuring the attenuation of a photon beam when passing through different parts of the sample, XPCi exploits the interference/refraction effects experienced by the photons. Until recently, XPCi has been mostly limited to specialized and expensive synchrotron facilities, due to the need of using photon beams of very high coherence and flux. Our group, however, developed a new implementation of XPCi, the “coded apertures” (CA) technique, which was proven to work efficiently even with standard x-ray sources and laboratory equipment. It has therefore great potential for applications in many fields of x-ray investigation, such as materials science, biomedical and clinical imaging. Recently, we have developed an algorithm to extract quantitative sample information from experimental CA XPCi images. This algorithm is, however, based on some simplifying assumptions that are likely to not be valid for all samples and experimental conditions that could be encountered in practice. This project will consist in studying how the method’s accuracy varies for different sets of experimental parameters and different types of samples. To this aim, the student will make use of a simulation code developed within our group, and use it to test the quantitative values provided by the algorithm against theoretically predicted ones. The ultimate goal of this study is to find some simple rules that describe which parameters are the most important in determining the method’s quantitative accuracy and under which experimental conditions the algorithms provides satisfying results. The student will gain skills in simulation methods, data analysis, and familiarize with the basic concepts of optics. A solid physics background is required.

Student: (Project available)

Comparison of iterative algorithms for x-ray phase contrast CT reconstructions

Supervisors: Charlotte Hagen and Alessandro Olivo

X-ray Phase Contrast imaging (XPCi) stands for a class of radiographic imaging techniques, which, in addition to x-ray attenuation, are sensitive to phase and refraction effects. XPCi techniques are especially important for the imaging of weakly attenuating biological samples and are investigated by an increasing number of groups worldwide, including the phase contrast group at UCL.
Edge Illumination (EI) XPCi - a novel method developed at UCL – can measure the refraction angle of x-rays as they pass an object. EI XPCi has recently been implemented as tomographic modality. By rotating the object over an angular range of at least 180 degrees and acquiring images at every rotation angle it is possible to reconstruct volumetric maps of the refractive index distribution within the object. While until now all tomographic reconstructions were carried out using filtered back projection, the next step is to explore the benefit of iterative algorithms for the reconstruction of these maps. The student would be given several experimental EI XPCi datasets on which different iterative reconstruction algorithms can be tested. The student would define metrics that can be used for a comparison and eventually decide which algorithm is most suited to the reconstruction problem at hand.
Besides being involved in the development of a new imaging method, the student would get familiar with the basic concepts of computed tomography and image reconstruction. The project requires mathematics and some experience in Matlab programming. Existing software packages (e.g. the ASTRA toolbox) can be used.

Student: Ben Cockburn

Magnetic stimulation of the human motor cortex: exploring sources of variability in motor evoked potentials

Supervisors: Ricci Hannah and John Rothwell

Transcranial magnetic stimulation (TMS) is a non-invasive brain stimulation technique which is used to investigate human motor cortex physiology in vivo. The response, a motor evoked potential (MEP), can be detected using electromyography, and its amplitude reflects the excitability of the corticospinal tract. Stimulus-response curves, describing the input-output relation of the corticospinal tract, are a common outcome measure in motor learning and neuro-rehabilitation research. The curves are obtained by delivering multiple stimuli at a range of intensities, in a randomised order. The MEP amplitudes are then fitted with a Boltzmann-like model. There are, however, a couple of practical problems which affect obtaining and analysing such data. The first is that the curves take a long time to obtain (~10 minutes) and thus may be affected by waning attention and alertness of the participant. The second is the variability in MEP amplitudes from stimulus-to-stimulus, and the fact that the distribution of amplitudes varies across different stimulus strengths thus violating the assumptions of traditional regression models. A novel model incorporating two sources of variability better describes the input-output characteristics of MEPs. The aim of this project is to examine the variability and it sources under different conditions (e.g. different muscles, rest versus contraction), since this may provide insight into the physiologic site and signalling-related mechanisms of variability. Key to achieving this will be the reducing the data acquisition time, by decreasing the interval between stimuli, and an examining how this affects the variability. This project is a mixture of programming, experimentation and modelling, and will specifically involve: (1) writing a short piece of code in specialist data acquisition software to deliver stimuli of random intensities across a range of inter-stimulus intervals; (2) recruiting healthy human participants; (3) using magnetic brain stimulation and electromyography to collect neurophysiological data (MEP stimulus-response curves); (4) processing and analysing the data. The work will take place within the Transcranial Magnetic Stimulation laboratories of the UCL Institute of Neurology in Queen Square.

Student: (Project available)

Embedded PC

Supervisors: Nick Donaldson and TBC

We are developing a new exercise machine for patients with spinal cord injury. To maximise recovery, we want to use the latent plasticity of the spinal cord by combining electrical stimulation of the paralysed muscles with a system that encourages voluntary effort to drive the pedals while cycling. The voluntary effort is encouraged by the patient participating in a virtual race in which their speed depends on the crank shaft torque without stimulation. The virtual race uses software from the company Tacx that runs on a laptop.
However, for this system to be of widespread use, it must be used by patients at home, which often will be a small flat and they may not be confident computer-users. Therefore an important step is to embed the PC inside the machine so that the program boots up as soon as the power is switched on. Also, to minimise the number of cables, a wireless link to a large display will be preferable. The Tacx software comes on a CD disc but uses an internet connection while running if one is available.
The aim of this project is to investigate the way the Tacx software works and decide whether it can run on embedded hardware, and, specifically, choose a low-cost system. A method for installing the software must be possible and ideally, the system should be set up with many courses, from which races can be chosen, without internet access. An input device that serves as a mouse will be necessary and this must be made part of the small controller that the patient holds while exercising.

Student: (Project available)

Development of a setup that controls Parylene C deposition onto implants via diffusion-limitation

Supervisors: Tim Boretius and Nick Donaldson

Electrodes for neuroprosthetic applications are designed to be implanted into specific body tissues and to restore or enhance lost functions via (e.g.) electrical stimulation. To do so, such electrodes are in need of an encapsulation to protect the electrical circuits from body fluids and the associated risk of corrosion, which would ultimately cause failure of the implanted device. Silicone rubber and parylene C are common encapsulants in use whereas parylene is especially suitable when thin (~10-20µm) and conformal coatings are needed.
Within our new project CANDO, we are developing brain probes for epilepsy treatment, which need a coating of parylene on their tips but not on their base. Since parylene is deposited from the vapour phase, a diffusion-limited approach seems feasible. Thus, the main aims for this project are (1) to develop a setup that limits the diffusion of parylene onto the probe tips and (2) to characterise the resulting taper. The prospective student will learn about biomedical encapsulants, diffusion control, CAD software usage, and laser processing. Strong practical skills are required since most of the work will be done in the lab.

Student: (Project available)

EIT perfusion imaging.

Supervisors: Rebecca Yerworth and Adam Gibson

Electrical Impedance Tomography (EIT) creates images of the internal impedance changes related to physiological function using a series of surface electrodes measurements placed on the surface of the body in real-time. It is increasingly being used as a bedside tool for monitoring regional lung ventilation. However surprisingly little is published on perfusion (blood distribution)/flow. This may be because most clinical systems use serial data collection which, if uncorrected, results in image distortion, and may be obscuring the cardiac signal. This project aim is to see if the application of a recently developed data correction technique enables the cardiac related signal to be visualised and would involve creating simulations and reanalysing previously collected data.

Student: (Project available)

Deformable Registration of Paired Breath-Hold CT Lung Images for the Assessment of the Stage and Severity of Chronic Obstructive Pulmonary Disease.

Supervisors: Jamie McClelland and Felix Bragman

Chronic Obstructive Pulmonary Disease (COPD) is a common disease, which has been identified as the fourth leading cause of mortality and morbidity within the USA with projected global numbers rising to the fifth and third most common cause of morbidity and mortality, respectively, by the year 2020. It is a progressive non-reversible disease, which is characterised by airflow limitation and obstruction. It is a highly complex, multi-dimensional disease consisting of three main subtypes; chronic bronchitis, chronic bronchiolitis and emphysema. Spirometry is the current accepted gold standard for the assessment and staging of COPD. However, a limitation of spirometry is that it produces a single, global measure, which ignores the complexities and the underlying spatial progression of COPD. This is motivating the use of imaging techniques and the development of novel quantitative tools for the analysis of COPD. Deformable image registration is the process of finding the transformation, which aligns two images into the same reference frame. Registration of chest images is a challenging task. This is due to the large non-linear deformation seen during the respiration process, the sliding motion of the lung with respect to the ribcage in addition to the local intensity changes resulting from to the variation of tissue density as a result of the breathing process. Registration of the lung sees various clinical applications notably in radiotherapy and more recently in the study of COPD. The main aim of this project lies in the investigation and development of state of the art techniques for achieving accurate lung registration. Work will build upon recent developments at the Centre for Medical Image Computing and will be based on the NiftyReg registration package. Various routes may be undertaken to improve the registration. This includes investigating the limits and optimal parameters of the current algorithm, employing a feature-based step to guide the deformable registration and investigating new regularisation schemes to deal with the sliding boundary conditions. This project will requires strong mathematical, computing and programming skills, in addition to a willingness to learn about registration algorithms and the underlying mathematics. This project may lead to a conference publication upon successful completion.

Student: (Project available)

Critical Assessment of Low-Cost MRI Solutions in Africa

Supervisors: Karin Shmueli and Priti Parikh

Magnetic Resonance Imaging (MRI) has been in clinical use for over 20 years in the most developed countries in the world. The aims of this project are to investigate the prevalence and clinical use of MRI in African countries. Many clinical settings in these countries are resource challenged, underscoring a need for the development of low-cost MRI solutions. Do these exist? Are they local and sustainable? What is the level of demand for clinical MRI? Which companies, if any, are working in this sector in Africa? Is there sufficient local training of skilled technicians and operators? The student will be expected to investigate these and related questions. Ideally they will critically assess the advantages and disadvantages of potential low-cost MRI solutions using medical physics (and development) principles. The student will be expected to communicate effectively with international contacts to gather information.

Student: (Project available)

Characterising and Modelling Susceptibility Artifacts in Mouse Brain MRI at 9.4 Tesla

Supervisors: Karin Shmueli and Simon Walker-Samuel

Magnetic Resonance Imaging (MRI) at high magnetic field strengths (e.g. 9.4 Tesla) is advantageous as it provides greater signal. However, image artifacts due to air-tissue magnetic susceptibility differences worsen as the field strength increases. Geometric distortion and signal drop-out artifacts caused by large magnetic field inhomogeneities around the ear-canals are a particular problem for gradient-echo MRI of the mouse brain at 9.4 Tesla.
This project will focus on characterising these susceptibility artifacts and modelling their sources with the goal of improving preclinical MRI in mouse models. Susceptibility artifacts can be characterised using MRI by mapping the local magnetic fields in the mouse brain and analysing the field inhomogeneities (i.e. field gradients). MRI magnetic field maps have been acquired in several mice and one aim is to combine these to create an ‘average’ field map to allow us to predict common susceptibility artifacts. We may also be able to gain insight into the source of these artifacts by building a map of the underlying soft tissue and bone susceptibilities that contribute to the non-uniform magnetic field distribution and modelling the resulting magnetic field distribution. Comparing the modelled field map with the ‘average’ measured field map will improve our understanding of susceptibility artifacts in the mouse.
You will use Matlab (or other software) to analyse MRI data acquired on the 9.4 Tesla MRI system at the Centre for Advanced Biomedical Imaging (CABI). You will calculate, process and simulate magnetic susceptibility and field maps as well as comparing measured and modelled field maps. Insights from this work will provide a valuable foundation for developing techniques to reduce susceptibility artifacts in the mouse brain at 9.4 T.

Student: Rosie Goodburn

Assessment of dose in diffraction imaging

Supervisors: Jennifer Griffiths and Yi Zheng

X-ray diffraction has the ability to differentiate between healthy and diseased breast tissues. This could lead to more accurate and faster diagnosis of breast cancer. In order to further it’s translation into the clinic, two key questions must be addressed:
1. What is the additional dose to the patient?
2. What are the structures in the tissue that the diffraction is identifying?
These questions form the basis of two student projects in radiation physics.
This project will involve modeling the dose to the patient expected if x-ray diffraction were to be used in addition to standard x-ray mammography. You will need to understand the physics of coherent scatter to accurately model the scatter created in a patient, and consider the dose needed to create a signal suitable for diagnosis. A survey of detectors that could be used for x-ray diffraction and the signal to noise ratio of the data will need to be taken into account.
This project would suit a student with confidence in coding – your first job will be to identify the most suitable way to model the system.
Simple experiments in the laboratory can be used to validate your model.

Student: (Project available)

The role of collagen types and structures in breast tissue

Supervisors: Jennifer Griffiths and Yi Zheng

X-ray diffraction has the ability to differentiate between healthy and diseased breast tissues. This could lead to more accurate and faster diagnosis of breast cancer. In order to further it’s translation into the clinic, two key questions must be addressed:
1. What is the additional dose to the patient?
2. What are the structures in the tissue that the diffraction is identifying?
These questions form the basis of two student projects in radiation physics.
This project will involve a thorough survey of the types of tissues, especially collagen, found in healthy and diseased tissues, and their structures. You will need to assess the literature to find out the expected diffraction signals from the tissue types. You will produce a thorough review of the tissue types, particularly different collagens, and their signals before designing the ideal diffraction geometry required to measure these diffraction signals.

Student: (Project available)