In search of relevant things: A novel approach for image analysis

In search of relevant things: A novel approach for image analysis

Programs Available

MRes Yr 2 + PhD 

Reference Number

20201276 

Opening Date

01 Jan 2020 12am AEDT 

Closing Date

01 May 2020 12am AEST 

Scholarship available to

Domestic 

Description

This project aims to investigate how experts’ cognitive processes may be transferred to computers for the automatic recognition of visual features. By merging computer and brain sciences, the project will characterise the way the brains of experts understand what is seen, in order to translate such a process in a new computer vision tool. This should provide significant benefits, such as automatic detection in diagnostic imaging, mainly in neuroradiology, among other applications. For the first time, the combination of how a computer analyses an image and how an expert interprets it will be used as a common language to enable machines to process visual information in a manner that mimics the way human brains do.

The candidate will be involved in the computational analysis of the images as well as the visual tracking map, with the special task of contributing to creating the machine learning algorithm for the computerised analysis of the regions of interest. Fractal-based computational modelling and Artificial Intelligence tools will be used to characterise images, with the aim to translate the results of the neurocognitive part of the project into computer science tools, in order to improve features extraction and pattern recognition for machine-based automatic detection of salient features in images. It will suit a student with background and/or interest in computer science and AI.

The project is part of an Australian Research Council (ARC) Future Fellowship project, granted to Prof Di Ieva in the period 2020-2023 (FT190100623).

The project will be conducted within the research frame of the Computational NeuroSurgery (CNS) Lab at Macquarie University, led by Prof Antonio Di Ieva, neurosurgeon, neuroanatomist and computational neuroscientist.

https://www.mq.edu.au/research/research-centres-groups-and-facilities/groups/computational-neurosurgery-lab

The student will be supervised by Prof. Di Ieva and co-supervised by collaborators within the Faculty of Medicine and Health Sciences (including Department of Clinical Medicine and Macquarie Medical Imaging), Centre for Health Informatics, Department of Cognitive Sciences, Department of Computing, and the Centre for Elite Performance, Expertise and Training (CEPET). This multidisciplinary environment will provide a dynamic background for the candidate’s translational research.

This scholarship is available to eligible domestic candidates to undertake a direct entry 3-year PhD or MRes Year 2 + PhD (total 4 years).

Availability

This scholarship is available to eligible candidates to undertake an MRes Year 2 (1-year) + PhD (3-year) program.

Scholarship Components

The scholarship is comprised of a Tuition Fee Offset and a Living Allowance Stipend. The value and tenure of the scholarship is a “MQRES” full-time stipend rate of $28,092 per annum (in 2020 tax exempt - indexed annually).

Contact Details

Name: Prof Antonio Di Ieva
Email: antonio.diieva@mq.edu.au
Phone: 02 9812 3821

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