Rania Helal

Papers

Total Citations

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About

Rania Helal is a biomedical engineer whose research focuses on the intersection of medical image processing and otology, specifically targeting the cochlea. Her primary contributions lie in developing automated, atlas-based segmentation methods for 3D multimodal images of the inner ear. Her most-cited work, "Automatic cochlear multimodal 3D image segmentation and analysis using atlas–model-based method" (2023, 10 citations), introduces a fast, automated technique for estimating cochlear length and volume from clinical scans. This innovation has direct clinical relevance, aiding in the selection of cochlear implant types, surgical planning, and the advancement of robotic cochlear surgeries. Her earlier foundational paper, "Automatic Cochlear Length and Volume Size Estimation" (2018, 5 citations), established the core methodology. By replacing manual, time-consuming measurements with a reliable automated pipeline, Helal’s work addresses a critical bottleneck in personalized cochlear implantation. Her research is notable for its translational impact, bridging computational image analysis with tangible surgical outcomes, and her methods hold promise for improving the precision and efficiency of hearing restoration procedures.