人工智能在斑点的特征和检测原因中的实用性:基于光谱域OCT的算法研究
Amal Alzu'bi1, Sondos Momany1, Abdelwahab Aleshawi2
1Department of Computer Information Systems, Faculty of Computer and Information Technology, Jordan University of Science and Technology, P. O. Box 3030, Irbid, 22110, Jordan.
Experimental eye research
|September 1, 2025
概括
这项研究开发了一个深度学习框架,使用光学连贯断层扫描 (OCT) 图像准确分类糖尿病黄斑胀 (DME) 和与年龄相关的黄斑退化 (AMD),提高诊断能力.
科学领域:
- 眼科和人工智能
- 医学成像分析
- 医疗保健中的深度学习
背景情况:
- 黄斑胀 (ME) 是导致视力丧失的主要原因,通常源于糖尿病黄斑胀 (DME) 或与年龄相关的黄斑退化 (AMD).
- 精确区分 ME 病因对于有效治疗至关重要,
- 需要使用光学连贯断层扫描 (OCT) 图像进行ME的自动分类来弥补这一差距.
研究的目的:
- 开发和评估用于DME,AMD和正常视网膜疾病的自动分类的深度学习框架.
- 评估不同卷积神经网络 (CNN) 架构用于OCT图像分析的性能.
- 整合可解释的AI (XAI) 技术,以提高诊断预测的可解释性.
主要方法:
- 使用了来自国王阿卜杜拉大学医院 (KAUH) 的1040张OCT图像的回顾数据集和公共数据集.
- 应用预处理,增强和模拟细分来优化模型性能.
- 测试并评估了三个预先训练的CNN:ResNet152,InceptionV3和MobileNetV2,其中包括XAI的Grad-CAM.
主要成果:
- 在这两组数据中,InceptionV3和ResNet152的准确度高 (95%-98%).
- 在公共数据集 (97%) 中,MobileNetV2表现出强的表现,在KAUH数据集 (89%) 中表现出中等的准确性.
- 根据注释数据验证的Grad-CAM可视化证实了模型的可解释性.
结论:
- 深度学习模型,特别是像InceptionV3和ResNet152这样的CNN显示出精确ME分类的巨大潜力.
- 通过将CNN与XAI技术整合,可以提高眼科诊断的准确性.
- 这种框架可以帮助临床决策,例如DME和AMD.
更多相关视频
07:18Evaluation of Capillary and Other Vessel Contribution to Macular Perfusion Density Measured with Optical Coherence Tomography Angiography
Published on: February 18, 2022
1.9K
08:54Author Spotlight: Understanding Age-Related Macular Degeneration Pathophysiology with QAF Workflow
Published on: May 26, 2023
1.7K
相关概念视频
01:18Imaging Biological Samples with Optical Microscopy
12.3K
Optical microscopy uses optic principles to provide detailed images of samples. Antonie van Leeuwenhoek designed the first compound optical microscope in the 17th century to visualize blood cells, bacteria, and yeast cells. In 1830, Joseph Jackson Lister created an essentially modern light microscope. The 20th century saw the development of microscopes with enhanced magnification and resolution.
In optical microscopy, the specimen to be viewed is placed on a glass slide and clipped on the stage...
In optical microscopy, the specimen to be viewed is placed on a glass slide and clipped on the stage...
12.3K
01:10Computed Tomography
9.7K
Tomography refers to imaging by sections. Computed tomography (CT) is a non-invasive imaging technique that uses computers to analyze several cross-sectional X-rays to reveal minute details about structures in the body.
The technique was invented in the 1970s and is based on the principle that as X-rays pass through the body, they are absorbed or reflected at different levels. In the technique, a patient lies on a motorized platform while a computerized axial tomography (CAT) scanner rotates...
The technique was invented in the 1970s and is based on the principle that as X-rays pass through the body, they are absorbed or reflected at different levels. In the technique, a patient lies on a motorized platform while a computerized axial tomography (CAT) scanner rotates...
9.7K