Antony, Bhavna (Prof)

Bhavna Antony

Position:Professor, Information Technology
Discipline:Information Technology
Phone:03 8780 5742
Email:b.antony@federation.edu.au

Qualifications

  • PhD, Dept. of Electrical & Computer Engineering, University of Iowa
  • MSc, Dept. of Electrical & Computer Engineering, University of Iowa
  • B.E., Medical Electronics, Visvesvaraya Technological University, Belgaum, India

Teaching area

  • Machine Learning & AI
  • Research Methods & Communication

Professional associations

  • IEEE, Senior Member
  • Association of Research in Vision & Ophthalmology (ARVO)

Research interests

  • Deep-learning for medical image analytics
  • Ophthalmic data analytics, disease detection, personalised disease prognostication

Publications

  • (Abbasi, Antony, et al., 2023; Abbasi, Monadjemi, et al., 2023; Al-Aswad et al., 2022; Chorev et al., 2023; Gowrisankaran et al., 2023; Schuman et al., 2022)
  • Abbasi, A., Antony, B. J., Gowrisankaran, S., Wollstein, G., Schuman, J. S., & Ishikawa, H. (2023). Can Glaucoma Suspect Data Help to Improve the Performance of Glaucoma Diagnosis? Translational Vision Science & Technology, 12(8), 6-6.
  • Abbasi, A., Monadjemi, A., Fang, L., Rabbani, H., Antony, B. J., & Ishikawa, H. (2023). Mixed multiscale BM4D for three-dimensional optical coherence tomography denoising. Computers in Biology and Medicine, 155, 106658.
  • Al-Aswad, L. A., Ramachandran, R., Schuman, J. S., Medeiros, F., Eydelman, M. B., Abramoff, M. D., . . . Chiang, M. (2022). Artificial intelligence for glaucoma: creating and implementing artificial intelligence for disease detection and progression. Ophthalmology Glaucoma, 5(5), e16-e25.
  • Chorev, M., Haderlein, J., Chandra, S., Menon, G., Burton, B. J., Pearce, I., . . . Chandak, S. (2023). A Multi-Modal AI-Driven Cohort Selection Tool to Predict Suboptimal Non-Responders to Aflibercept Loading-Phase for Neovascular Age-Related Macular Degeneration: PRECISE Study Report 1. Journal of Clinical Medicine, 12(8), 3013.
  • Gowrisankaran, S., Song, X., Wollstein, G., Schuman, J. S., Antony, B. J., & Ishikawa, H. (2023). OCT Image Classification of Glaucoma Using AutoML–A Code-Free Deep Learning Platform. In Review
  • Schuman, J. S., Cadena, M. D. L. A. R., McGee, R., Al-Aswad, L. A., Medeiros, F. A., Abramoff, M., . . . Eydelman, M. (2022). A case for the use of artificial intelligence in glaucoma assessment. Ophthalmology Glaucoma, 5(3), e3-e13.