Cognitive image computing the next step for medical imaging Thursday, 21 April 2016

Research into medical image engineering has the potential to drastically change our health care system and the health of our communities. Local academic, Dr Danchi Jiang, Chair of Computer Systems Engineering at the School of Engineering and ICT of University of Tasmania is currently focusing on research in this field, in particular, cognitive image computing. We caught up with Dr Jiang to find out more about this career and his research.

Tell us about your career so far.
After completing my PhD in Systems Engineering at Australian National University (ANU), I spent two years at The Chinese University of Hong Kong as a Research Fellow, then five years in Toronto in the ICT system consulting and development industry. The pleasant climate lured me back to Australia as I joined National ICT Australia (NICTA) as a researcher and a PhD supervisor at ANU. I enjoyed this balance of research and teaching, so I then applied to a University of Tasmania (UTas) faculty opportunity and tenured here.

What inspired you to become an engineer and an academic?
I started my tertiary education in math. However, as I always try to relate what I learn to the real world, I became interested in engineering. After completing a Masters in control systems and a PhD in systems engineering, I became an engineering academic naturally. 

What do you enjoy most about your work?
What I enjoy most about my work is that I can have the freedom to research something new. I discover many potential improvements to problems in the real world quite easily. These thoughts then become the basis for my research as it takes big efforts to realise these ideas into practice.

Do you have any advice for young engineers just starting their career?
Engineering is about making something work by proper application of math, science, and technology. The desire to try something different and make it work is essential to build engineering skills.  

What project are you currently working on?
Recently I have spent a significant amount of time on the research of medical image engineering.

In particular, cognitive image computing to combine big data processing and cognitive abstraction, and apply this method to medical images.

This project includes many small sub-projects, each with its focus either on one particular set of techniques or on a particular type of medical applications; for example 3D MRI image fusion for precise knee cartilage measurement for arthritis diagnosis.

Tell us more about this project:
Nowadays medical imaging is an indispensable tool for pathological analysis and clinical diagnosis. However, doctors can only make use of a small portion of the information contained in those medical images, either because of the large amount of data beyond what human can effectively process or details that are difficult to capture visually.

The cognitive image computing project aims to imitate the way doctors process medical images using computing devices automatically.

To some aspects we can describe such a system as a virtual doctor with a super capability in data and irregular patterns processing at the scale far beyond what we can see visually.

This is a long-term project that is divided into many small sub-projects focused on particular aspect so that we can be more specific and achieve an outcome within a reasonable time period.

We collaborate with experts at Menzies Institute of UTAS on some subtopic and are also seeking industry partners and investors to work with us.   

Why did you decide to pursue this research?
Microprocessors and communication networks are so powerful nowadays that basically everything can be connected. However, the information collected can be beneficial only if they can be processed correctly, appropriately, and efficiently.

I have been working on intelligent signal processing for most of my research career. Recently, I have decided to focus on cognitive image processing because of its potential value to the health improvement of communities and our health care system.

What impact on the future will this research have?
There are many medical image processing techniques considered standard practice. However, new techniques and systems are still expected to provide better analysis and diagnosis assistance to doctors. Our research demonstrates our efforts in this direction.

The project is also closely related to other applications of ICT technology in the medical and healthcare industries for information collection and effective use. Such systems are predicted to have a multi-billion market value in the coming years.     

Any other interesting facts about the project?
Surprisingly, we have never applied our research outcomes to our own medical images. In fact, the value of our research or any other medical research is usually neglected when we are heathy.

To find out more about Dr Jiang and his research, visit the University of Tasmania website.