Professional AssociationsProfessional Associations: IEEE Member | IEEE Women in Engineering | SPIE -- International Society of Optical Engineering | The Association for Research in Vision and Ophthalmology
Bhavna Antony is a research scientist at IBM Research - Melbourne, Australia. She received her PhD in Computer Engineering from the University of Iowa in 2013. Her research is focussed on the automated analysis of medical images, with a specific focus on the identification and extraction of clinically relevant parameters. She has worked extensively in the field of ophthamology and analysed retinal scans acquired using optical coherence tomography (OCT). Her contributions in this field include some of the earliest publications on the automated analysis of volumetric scans using a graph-theoretic approach that leveraged spatial context in 3-D. Her work also focussed on the incorporation of machine learning techniques that not only made the analytics more robust but also made it easily adaptable to animal models and images of varying resolution and noise characteristics. Using these techniques, she was able to extract relevant structures in images acquired from human patients as well as animal models (murine, canine and chick eyes).
While her research began in glaucoma, she has sought to learn and contribute to other areas of vision science as well. As as postdoctoral researcher at the University of California, Berkeley, she worked on the analysis of age-related macular degeneration images acquried from patients using a novel protocol - directional OCT - that allowed for the careful study of structures associated with the disease. She also collaborated with researchers to help with the analysis of chick models of myopia.
At Johns Hopkins University, she began to study multiple sclerosis and its manifestations in the retina. There she worked on using machine learning and novel graph-based frameworks for the analysis of retinal scans from human patients as well as mouse models of the disease. She also worked on developing registration methods that enabled the statistical analysis of retinal scans acquired from healthy and diseased cohorts of patients.
At IBM, her work continues to be focussed on ophthalmic applications of machine learning and artificial intelligence.