My current research interests include medical image analysis and mathematical modeling. My current focus is on the developing pixel based machine learning techniques, such as artificial immune based algorithm to automate the detection pulmonary nodules on Computed Tomography (CT) scans and brain lesions on Magnetic Resonance Imaging (MRI).
I trained uses a combination of mathematical modelling and bioimage analysis tools to study the detection of pulmonary nodules. Lung nodules are either considered noncancerous or cancerous. A noncancerous nodule is called benign, and a cancerous lung nodule is referred to as malignant. Growths that are larger than 3 centimeters are usually called lung masses and typically have a higher chance of being cancerous. It is hope that the proposed approaches to identify potential malignant and to alert the clinicians through the computer aided system, which can eventually increase the survival rate.
I collaborate extensively with the clinician and I welcome inquiries about collaborations regarding mathematical modelling and medical image analysis.
My current research is supported by funding from the Ministry of Education Malaysia and a research grant- potential academic staff(PAS) by Universiti Teknologi Malaysia.
Hang See-Pheng, Ph.D., (Senior Lecturer)
Address: Level 3, C10-337, Department of Mathematical Sciences, Faculty of Science, Universiti Teknologi Malaysia.
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