ELECTRICAL AND ROBOTICS ENGINEERING
26
Quantitative Image Analysis of Medical Images : Assisting Radiologists in Their Medical Decision-Making Processes
ELECTRICAL AND ROBOTICS ENGINEERING
Dr Maxine Tan Senior Lecturer MEng , PhD , CPEng , PEng
Research expertise : Quantitative Medical Image Analysis , Deep Learning , Radiomics , Biomedical Image Analysis , Computer-Aided Diagnosis ( CAD ), Machine Learning , Feature Classification and Modeling , Evolutionary Algorithms
E : maxine . tan @ monash . edu T : + 603 5515 9702
Quantitative image analysis and Computer-Aided Diagnosis ( CAD ) are broad concepts that integrate image processing , computer vision and artificial intelligence ( AI ) -based methods into computerized techniques that assist radiologists in their medical decision-making processes . These techniques include the detection of disease and anatomic structures of interest , classification of lesions , and risk assessment . We , along with colleagues and collaborators in other institutions , are conceptualising and developing novel deep learning , CAD , radiomics and quantitative image analysis-based methodologies . Active research projects span different imaging modalities
( including mammography , computed tomography , and digital breast tomosynthesis ) across a range of anatomic systems ( including lungs , breast , and brain ). The techniques we develop produce objective , quantitative computations of the numeric imaging data . These objective computations serve to augment the radiologists ’ subjective , qualitative interpretation of the displayed images . Unlike the radiologists ’ interpretation that may be prone to human error and fatigue as well as to inter-or intraobserver variabilities , deep learning and CAD schemes produce an objective and consistent reading / result to complement the radiologists ’ readings .
Cardiac Arrhythmias : Understanding and Controlling
Dr Liang , Shiuan-Ni Lecturer PhD
Research expertise : Biophysics , Biomedical Engineering , Nonlinear Physics
E : liang . shiuan-ni @ monash . edu T : + 603 5514 4991
Cardiac arrhythmia is a condition where heartbeats are abnormal . Every year , millions of people worldwide experience arrhythmias and many of them can return to their normal lives if the arrhythmias are treated at early stages and properly . However , many arrhythmias are dangerous and may lead to sudden cardiac death . In a healthy heart , when the cardiac cells are stimulated by electrical impulses , action potentials can be initiated and propagate as electrical waves through the heart . At normal heart rhythm , the action potential duration ( APD ) is almost identical from beat to beat . When pacing becomes faster , cardiac alternans can be developed . Cardiac alternans is clinically important because prolonged untreated alternans may lead to ventricular fibrillation ( VF ), a lethal arrhythmia which is the leading cause of sudden cardiac death . Our research focuses on understanding the mechanism of these cardiac arrhythmias , including alternans , ventricular tachycardia and VF , by using mathematical models and finding effective ways of controlling them . These projects are carried out in collaboration with partners from Taiwan and Vietnam .
Quantitative image and texturebased analysis for the detection of breast lesions and for cancer risk assessment
Computer-Aided Diagnosis ( CAD ) schemes for lung cancer detection and classification
APD alternans before control ( first four beats ) and after control ( last four beats )
Time sequence of APD with APD alternans is successfully controlled at beat number 741
RESEARCHER PROFILE 2025 / 2026