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Updated: Jul 14, 2026

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography
Published on: November 30, 2022
Assessment of the volume of intraorbital structures using the numerical segmentation image technique (NSI): the
Agata Majos1, Piotr Grzelak, Wojciech Młynarczyk
1Department of Radiology, Medical University of Łódź, Łódź. egnys@poczta.onet.pl
Introduction:
In recent years the use of computer systems has allowed numerical analysis of medical images to be introduced and has speeded up the conversion of numerical data into clinically valuable information. The creation of a software application that could almost automatically calculate the volume of anatomical structures imaged by MRI has seemed possible. The aim of our study was to determine the clinical usefulness of an numerical segmentation image technique (NSI) software application in estimating the volume of extraocular muscles.
Material And Methods:
The study group was formed of 45 patients (90 orbits). All the patients underwent MRI examinations of the orbits by a 1.5 T scanner using a head coil. The degree of exophthalmos was determined clinically and radiologically in relation to the interzygomatic line. The quantitative assessment of all eye muscles was carried out using the NSI application, a new software program introduced by the authors.
Results:
A close correlation between muscle volume and the degree of exophthalmos was revealed and confirmed by statistical analysis (r = 0.543, p = 3.13396E-08) in agreement with other papers.
Conclusions:
The NSI software program is an application which offers a reliable and precise estimation of eye muscle volume. It is therefore useful in the diagnosis of the pathological processes leading to exophthalmos. It has special clinical value for monitoring discrete volume changes of muscles during treatment.
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