Research
My research agenda aims to develop cutting-edge medical data analytic and human computer interaction techniques to unlock the value of big medical image data, obtain new insights, generate actionable guidance, and facilitate clinical decision making.
Algorithm development
Super resolution and artifacts removal for coronary imaging
We are developing a deep learning-based framework to enhance optical and digital resolution of optical coherence tomography (OCT) system. We develop a sparse representation-based method to removal saturation artifacts in OCT images.
Object detections
We developed region proposal network to identify diseased region in human coronary and football player in sports data analysis.
Image segmentation
We developed robust deep learning network to segment tissue regions within medical images.
Image denoising
We developed denoising framework to denoise MRI images and ultrasound images.
Biomedical application
Cardiac characterization
Cervical collagen fiber image analysis and image informatics to better understanding of preterm birth
Breast cancer identification for surgical margin detection
