matlab based graphical user interface for the monitoring and early detection of keratoconus

Q3 Engineering

Journal of Applied Research and Technology Pub Date : 2024-02-29 DOI:10.22201/icat.24486736e.2024.22.1.2103

I. Kallel Fourati, S. Kammoun

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引用次数: 0

Abstract

The rapid and extensive growth in medical imaging modalities and their applications is creating a pressing need for computers and computing in image processing, visualization, archival, and analysis. In this article, a Matlab-based graphical user interface (GUI) program is proposed for the monitoring and early detection of keratoconus. The findings show the efficiency of the proposed to detect the early stage of keratoconus. The proposed neural network model produces accuracy, ranging from 96% to 92%. It considers, respectively, 2 classes (normal cornea and keratoconus) and 3 classes (keratoconus, suspected keratoconus or normal) which will increase to 99% with respect to the 2 classes of keratoconus and 94% to the 3 classes when combining topography parameters with OCT image corneal pachymetry measurements and clinical judgments. The compatibility of the graphical interface components with common medical data and image analysis tools facilitates the involvement of the ophthalmologist in the digitization of the medical records, the image processing and the conception of multimodal artificial intelligence applications for medical imaging.

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基于 Matlab 的监控和早期检测角膜病的图形用户界面

医学成像模式及其应用的快速而广泛的增长，对图像处理、可视化、存档和分析方面的计算机和计算产生了迫切的需求。本文提出了一种基于 Matlab 的图形用户界面 (GUI) 程序，用于监测和早期检测角膜病。研究结果表明，该程序能有效检测早期角膜病。所提出的神经网络模型的准确率在 96% 到 92% 之间。在结合地形图参数、OCT 图像角膜厚度测量和临床判断后，2 类角膜（正常角膜和角膜屈光不正）和 3 类角膜（角膜屈光不正、疑似角膜屈光不正或正常角膜）的准确率将提高到 99%，3 类角膜的准确率将提高到 94%。图形界面组件与常用医疗数据和图像分析工具的兼容性为眼科医生参与医疗记录数字化、图像处理和医疗成像多模态人工智能应用的构思提供了便利。

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来源期刊

Journal of Applied Research and Technology 工程技术-工程：电子与电气

CiteScore

1.50

自引率

0.00%

发文量

审稿时长

6-12 weeks

期刊介绍： The Journal of Applied Research and Technology (JART) is a bimonthly open access journal that publishes papers on innovative applications, development of new technologies and efficient solutions in engineering, computing and scientific research. JART publishes manuscripts describing original research, with significant results based on experimental, theoretical and numerical work. The journal does not charge for submission, processing, publication of manuscripts or for color reproduction of photographs. JART classifies research into the following main fields: -Material Science: Biomaterials, carbon, ceramics, composite, metals, polymers, thin films, functional materials and semiconductors. -Computer Science: Computer graphics and visualization, programming, human-computer interaction, neural networks, image processing and software engineering. -Industrial Engineering: Operations research, systems engineering, management science, complex systems and cybernetics applications and information technologies -Electronic Engineering: Solid-state physics, radio engineering, telecommunications, control systems, signal processing, power electronics, electronic devices and circuits and automation. -Instrumentation engineering and science: Measurement devices (pressure, temperature, flow, voltage, frequency etc.), precision engineering, medical devices, instrumentation for education (devices and software), sensor technology, mechatronics and robotics.