Dr Mira Park
|Work Phone||(02) 4985 4518|
Mira Park graduated with a PhD in Computer Science Engineering from the University of New South Wales in 2003. During 2004~2005, she worked as a research fellow in the Computer Science and Software Engineering department at the University of Melbourne. She is a research fellow in the school of Design, Communication and IT at the University of Newcastle. Her research interests are Computer Vision, Pattern Recognition, and Medical Imaging.
- PhD, University of New South Wales, 2003
- Digital Image Processing
- Health informatics
- Medical image processing
- Pattern Recognition
- Complex data management (3D volumes medical images)
- Concept-based image retrieval
- Pattern recognition
- Intelligent computer aided diagnosis using incremental knowledge acquisition
- Machine learning, Data mining
- Medical image analysis (Chest Radiography, Intracranial CT angiography, CT colonography)
- Generic image processing algorithms (segmentation, edge detection, texture analysis)
- Health informatics
- Concept-based image retrieval
- Medical image analysis
- Computer aided polyp detection in the Colon Computed Tomography: The main objective of this project is to provide the proof of concept for computer aided polyp detection imaging system. The function of this system is to apply sophisticated image software and computer algorithms to assist radiologists and radiographers in the detection of regions of interest (ROI) or suspicious regions, which may relate to cancer risk or prognosis. It has been reported that in the United States alone, colon caner is the second leading cause of cancer deaths, contributing to the order of 60,000 deaths per year. It has been shown that the early detection and removal of polyps can reduce the risk of colon cancer, thus acting as a deterrent to colorectal.
- Computer aided aneurysm detection in the intracranial Computed Tomographic Angiography: The project aims to develop a new generation of computer aided detection (CAD) system that caters for the emerging needs of scientists, radiologists and industries in assisting the detection and characterisation of intracranial aneurysms through computer tomography angiography (CAT). Increased accuracy and reduced time in the detection of intracranial aneurysms on CTA can facilitate earlier detection with the potential to save lives and function. The CAD system will employ sophisticated image processing algorithms for assisting radiologists in the detection of suspicious regions which may represent aneurysms. The regions then are characterised by stochastic and machine learning methods.
- Intelligent archiving and retrieving of clinic laboratory records in pathology/radiology informatics study: Since 80% of the critical decisions made in medicine involve a pathology test or radiology examination, Pathology/radiology Informatics has emerged as an arm for developing next-generation pathology/radiology reporting methods, databases, imagery, and diagnostics. Current archiving systems are very primitive, restricting any sophisticated use of the reports. This proposal aims to collaborate with IntelliRAD in developing an innovative pathology/radiology report archiving system capable of automatically extracting useful information. This system will make a smart use of pathology/radiology data and open a new way to extend current tests and examinations from being disease-focussed to being wellness focussed.
- PhD project: My research topic was Intelligent Computer Aided Diagnosis for Chest Radiography. The research was carried out at CSIRO Telecommunication and Industrial Physics. The aim of this research was to produce an efficient method for the interpretation of chest radiographs using computer vision perception of objects and patterns. I have also built an intelligent computer aided diagnosis system for merging the radiological findings of the extracted features into an intelligent diagnosis using machine leaning scheme. This project was supported by a Faculty of Engineering Research Scholarship in University of New South Wales.
- Automatic optic disc detection in a retinal image: The optic nerve is one of the most important organs in the human retina. The detection of the optic disc (OD) is an essential step in the automatic analysis of digital colour fundus images.
I undertook my PhD thesis on 'Intelligent Computer Aided Diagnosis System for Chest Radiography', performing research in partnership with the CSIRO eHealth Research Centre. This project was primarily concerned with developing computer systems which use more effective image processing algorithms in combination with artificial intelligence and machine learning technologies to detect and accurately identify abnormal features in chest radiograph images.
Since completing my PhD I have continued my contribution to the field of computer aided diagnosis, working as a Research Fellow for the University of Newcastle in collaboration with IntelliRAD and other partners in the development and implementation of a Biotechnology Innovation Fund project, titled Computer Aided Detection System, to assist in early risk assessment, prognosis, and diagnosis of colon cancer. The new technology, known as Computer Aided Polyp Detection in Colon CT, to which I contributed key research and development, is predicted to produce considerable increases in the early detection and treatment of cancer and other conditions. The system enhances the ability of radiologists to identify colonic polyps and cranial aneurysms with the use of medical imaging technologies, minimising the need to utilise surgery and other invasive techniques (such as colonoscopies) as a diagnostic tool. Due to this innovation it is hypothesised that greater numbers of patients will consent to checks for colonic polyps, increasing the rates of early detection. The system utilises an innovative algorithm, which is able to identify polyps and other abnormal features of all shapes and sizes.
Fields of Research
|080100||Artificial Intelligence And Image Processing||55|
|080200||Computation Theory And Mathematics||30|
Committee/Associations (relevant to research).
- Academic Member - IEEE
The University of Melbourne (Australia)
|01/01/2004 - 01/12/2005|
The University of Newcastle (Australia)
Best Student Paper Award
visual information processing conference (Australia)
best student paper award
Best student paper award
Visual information processing conference (Australia)
I am able to contribute to the administrative work through my experiences in part time work as an office worker at the education consulting and the travel agency. I am also able to contribute effectively to the administrative work using my knowledge gained from two certificates as follows.
7377 Certificate in Bookkeeping and Financial Skills 1998
South Western Sydney Institute, Granville College
Areas of study
- Bookkeeping (Accounts Receivable, Accounts Payable, General Ledger)
- Financial Source Documents
- Computerised, MYOP (Accounts Receivable, Accounts Payable, General Ledger)
- Cash records, Cash book, Payroll, Bank deposits, Petty cash
- Spreadsheet, Word processing
National Technical Qualification Certificate for Information Processing 1990
Republic of Korea
Registration No.: 90202100094Z
Class No.: 1320
Class Name: Information Process Engineer
- Data Structure
- Image processing
- Systems analysis
- Lecture & Tutorial: INFT1004 (Visual Programming), INFT2008 (Information system programming), INFT2009(System and software development), INFT3009(Web database interfacing), INFT3201 (Multimedia Transmission, Storage & Management)
- Tutor (2000~2002, COMP1021 Computer Programming, The University of New South Wales)
- Instructor (1990~1991, Han-Kook Computer Institution in South Korea)
- 1st qualified field to lecture: Digital Image processing and Multimedia: My main background subjects for PhD research were digital image processing and multimedia. Therefore,
- Graphics and Computation
- Modeling, Analysis and Visualisation
- Computer Vision and Image Processing
- 2nd qualified field to lecture: Computer Languages, Computer Architecture, Data Structure and Algorithms: I have teaching experiences as a private instructor and a tutor in computer languages such as C/C++, Fortran, Pascal, Java etc., computer data structure and algorithms (Details in CV). Therefore,
- Introduction to Programming - Advanced
- Algorithmic Problem Solving - Advanced
- Introduction to Programming
- Algorithm Problem Solving
- Algorithms and Data Structures
- 3rd qualified field to lecture: Databases, Artificial Intelligent and Soft Engineering: I have research experiences through Master and PhD courses on Databases, Artificial Intelligent and Soft Engineering. Therefore,
- Software Design
- Artificial Intelligence
- Operating Systems
- Database Systems
- Programming Language Implementation