Computer Vision News 44 Deep Learning for the Eyes by Christina Bornberg @datascEYEnce Hello everyone! We are back for another datascEYEnce story focusing on researchers who work in deep learning applied to ophthalmology! I am Christina and this time I want to introduce you to Wenke, whom I met at the German Conference on Medical Image Computing (BVM workshop) last month. Her presented poster "3D Deep Learning-based Boundary Regression of an Age-Related Retinal Biomarker in HighResolution OCT," caught my attention, and I knew it would be a perfect fit for RSIP Vision’s Computer Vision News magazine. That's why I reached out to her for an interview! In search for ocular imaging biomarkers with inconsistent labels featuring Wenke Karbole Wenke started her journey in deep learning for ophthalmology with a Bachelor’s degree in medical engineering at the TU Ilmenau. She found herself fascinated by a deep learning module and, therefore decided to enroll in as many courses as possible in this direction. During her Bachelor's Thesis at Siemens Healthineers, Wenke worked on deep learning applications for CT images. Transitioning to ophthalmology was a natural step forward while pursuing a double degree in medical engineering and AI at FriedrichAlexander-Universität Erlangen-Nürnberg (FAU), merging her passion for deep learning with her interest in photography and optical systems.
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