Abstract #3762

A-Eye: Towards a large-scale MRI-based model of the complete eye

Jaime Barranco^1,2, Hamza Kebiri^1,2, Óscar Esteban³, Raphael Sznitman⁴, Oliver Stachs⁵, Sönke Langner^6,7, Benedetta Franceschiello^8,9,10, and Meritxell Bach Cuadra^1,2,10

¹CIBM Center for Biomedical Imaging, Lausanne, Switzerland, ²Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland, ³Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland, ⁴ARTORG Center for Biomedical Engineering, University of Bern, Bern, Switzerland, ⁵Ophthalmology, Rostock University Medical Center, Rostock, Germany, ⁶Institute for Diagnostic and Interventional Radiology, Rostock University Medical Center, Rostock, Germany, ⁷Diagnostic Radiology and Neuroradiology, University of Greifswald, Greifswald, Germany, ⁸School of Engineering, Institute of Systems Engineering, HES-SO Valais-Wallis, Sion, Switzerland, ⁹The Sense Innovation and Research Center, Lausanne and Sion, Switzerland, ¹⁰These authors provided equal last-authorship contribution, Lausanne, Switzerland

Synopsis

Keywords: Segmentation, Neuro, Eye, ophthalmologyThis work comparatively evaluates two approaches for the automated segmentation of eye structures from 3D T1-weighted MRI data of the whole human head (N=1210). Quantitative results on a validation sub-set with manual annotations provide accurate results for lens and globe and set the first median Dice (DSC) benchmarks for optic-nerve (0.91), muscles (0.58 to 0.76) and fat (0.67 and 0.75). The ability of our framework to automatically extract state-of-the-art measurements, such as the axial length, paves the way to accurately identify and compute new biomarkers of the eye via MRI.

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