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Updated: Jul 19, 2026

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography
Published on: November 30, 2022
Extraocular muscle quantification using mathematical morphology: a semi-automatic method for analyzing muscle
André Domingos Araújo Souza1, Evandro Eduardo Seron Ruiz, Antonio Augusto Velasco Cruz
1Medical Image Processing Group, Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA.
Abstract:
Mathematical morphology was used to quantify the dimensions of the human extraocular muscles in computed tomography orbital scans. Coronal images of 28 patients with Graves orbitopathy and 5 controls (218 orbital scans) were analyzed with an algorithm for extraocular muscle segmentation. The results showed that measurements of extraocular muscle area obtained with semi-automatic segmentation are highly correlated with manual tracing and provides a simple method to quantify orbital structures including the extraocular muscles.
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