Papers
5
Total Citations
29
H-Index
3
About
Blanca Flores is a leading researcher at the intersection of ophthalmic imaging, computer vision, and robotic surgery, whose work is critical to advancing regenerative therapies for sight restoration. Her primary research focuses on enhancing intra-operative Optical Coherence Tomography (iOCT) image quality and enabling real-time retinal tracking for robotic-assisted subretinal delivery. Flores’s major contributions include developing a supervised deep convolutional neural network that jointly predicts semantic segmentation and optical flow of the retina, achieving dense, learned optical flow for intra-operative tracking of the retinal fundus—a foundational paper with 12 citations. She has also pioneered super-resolution techniques for iOCT, leveraging high-quality pre-operative scans and contrastive learning to improve real-time retinal layer visualization, with her 2021 work on iOCT image quality enhancement garnering 8 citations. Her notable achievements include a two-stage methodology for iOCT super-resolution and an unpaired video super-resolution approach using contrastive learning (2023, 3 citations). With a cumulative impact of over 29 citations, Flores’s innovations are paving the way for precise, robotically delivered regenerative therapies, making her a key figure in advancing surgical biomicroscopy-guided imaging and automated ophthalmic interventions.
Research Focus
Key Achievements
Top Papers
- 1Learned optical flow for intra-operative tracking of the retinal fundus12 citations · 2020
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