Search engine for discovering works of Art, research articles, and books related to Art and Culture
ShareThis
Javascript must be enabled to continue!

Eyeball segmentation and measurement in MRI images of myopic children

View through CrossRef
Abstract Myopia occurs when the light beam stops before entering the retinal layer, resulting in blurred long-distance vision. Myopia in children is very common nowadays, requiring prompt intervention and effective treatment. Thus, research on myopia among children is aggressively conducted to propose better treatment technology. One of the aspects of myopia research is to analyse the shape of the eyeball and its association with this abnormality. Eyeball imaging is commonly conducted via magnetic resonance imaging (MRI). Thus, this paper presents eyeball segmentation in MRI images of myopic children based on the Chan-Vese Level Set method. MRI eye images of 35 myopic children were used. The measurement of pertinent lines was also done. The accuracy of the lines’ measurement was compared with the manual measurement. An average difference of 0.2825 mm (std 0.2386mm) for the left eye and 0.2677 mm (std 0.2526 mm) for the right eye were obtained. Also, statistical t-test evaluation showed that both measurements were statistically similar, confirming the agreement between the two. In conclusion, the process of segmentation and measurement of the eyeball is important to furnish the need for myopia treatment research and study on any treatment efficacy.
Title: Eyeball segmentation and measurement in MRI images of myopic children
Description:
Abstract Myopia occurs when the light beam stops before entering the retinal layer, resulting in blurred long-distance vision.
Myopia in children is very common nowadays, requiring prompt intervention and effective treatment.
Thus, research on myopia among children is aggressively conducted to propose better treatment technology.
One of the aspects of myopia research is to analyse the shape of the eyeball and its association with this abnormality.
Eyeball imaging is commonly conducted via magnetic resonance imaging (MRI).
Thus, this paper presents eyeball segmentation in MRI images of myopic children based on the Chan-Vese Level Set method.
MRI eye images of 35 myopic children were used.
The measurement of pertinent lines was also done.
The accuracy of the lines’ measurement was compared with the manual measurement.
An average difference of 0.
2825 mm (std 0.
2386mm) for the left eye and 0.
2677 mm (std 0.
2526 mm) for the right eye were obtained.
Also, statistical t-test evaluation showed that both measurements were statistically similar, confirming the agreement between the two.
In conclusion, the process of segmentation and measurement of the eyeball is important to furnish the need for myopia treatment research and study on any treatment efficacy.

Related Results

Hydatid Disease of The Brain Parenchyma: A Systematic Review
Hydatid Disease of The Brain Parenchyma: A Systematic Review
Abstarct Introduction Isolated brain hydatid disease (BHD) is an extremely rare form of echinococcosis. A prompt and timely diagnosis is a crucial step in disease management. This ...
Extended numerical analysis of an eyeball injury under direct impact
Extended numerical analysis of an eyeball injury under direct impact
Abstract The objective of this study was to develop a numerical model of the eyeball and orbit to simulate a blunt injury to the eyeball leading to its rupture, as ...
IMPACT OF POSITIVE AND NEGATIVE LENS-INDUCED DEFOCUS ON CONTRAST SENSITIVITY IN MYOPIC AND NON-MYOPIC ADULTS
IMPACT OF POSITIVE AND NEGATIVE LENS-INDUCED DEFOCUS ON CONTRAST SENSITIVITY IN MYOPIC AND NON-MYOPIC ADULTS
Background: Lens-induced defocus (LID) alters contrast sensitivity (CS), a key determinant of visual performance, affecting both myopic and non-myopic individuals. Myopia, a preval...
AI‐enabled precise brain tumor segmentation by integrating Refinenet and contour‐constrained features in MRI images
AI‐enabled precise brain tumor segmentation by integrating Refinenet and contour‐constrained features in MRI images
AbstractBackgroundMedical image segmentation is a fundamental task in medical image analysis and has been widely applied in multiple medical fields. The latest transformer‐based de...
Seeing beyond vision: A comparative study of intelligence, academics, and lifestyle in myopic and non-myopic medical students.
Seeing beyond vision: A comparative study of intelligence, academics, and lifestyle in myopic and non-myopic medical students.
Objective: To compare intelligence (IQ), academic performance, and lifestyle factors between myopic and non-myopic undergraduate medical students, while also evaluating demographic...
Multiple surface segmentation using novel deep learning and graph based methods
Multiple surface segmentation using novel deep learning and graph based methods
<p>The task of automatically segmenting 3-D surfaces representing object boundaries is important in quantitative analysis of volumetric images, which plays a vital role in nu...
A Novel Brain MRI Image Segmentation Method Using an Improved Multi-View Fuzzy c-Means Clustering Algorithm
A Novel Brain MRI Image Segmentation Method Using an Improved Multi-View Fuzzy c-Means Clustering Algorithm
Background: The brain magnetic resonance imaging (MRI) image segmentation method mainly refers to the division of brain tissue, which can be divided into tissue parts such as white...

Back to Top