检索结果-南通市图书馆

Vision rehabilitation using microperimetric biofeedback training in age-related macular degeneration

International Journal of Ophthalmology(English edition) 2023年第6期16卷 933-938页

作者： Sri Hudaya Widihastha Erwin Iskandar Karmelita Satari Irawati Irfani Rova Virgana Primawita Oktarima Amiruddin Department of Ophthalmology Faculty of MedicineUniversitas PadjadjaranBandung 40117Indonesia National Eye Center Cicendo Hospital Bandung 40117Indonesia

·AIM: To determine the impact of microperimetric biofeedback training(MBFT) on the quality of vision in patients with age-related macular degeneration(AMD).·METHODS: This study was a prospective, interventional, comparative study with subjects of patients diagnosed with AMD in the National Eye Center Cicendo Eye Hospital, Indonesia. Patients were randomly divided into two groups, intervention and non-intervention with 18 patients in each group. The intervention group would receive six MBFT training sessions of 10-minute time duration each.·RESULTS: A statistically significant improvement of best corrected visual acuity(BCVA) was found after the intervention, from 1.24±0.416 to 0.83±0.242(log MAR;P<0.001). A statistically significant improvement for near vision acuity(NVA) was also observed, from 1.02±0.307 log MAR to 0.69±0.278 log MAR(P<0.001). In addition, reading rate increased, from 40.83±30.411 to 65.06±31.598 words/min(P<0.001). Similarly, a comparison of changes in BCVA, NVA, and reading rate between intervention and non-intervention groups showed a significant difference(P<0.001).·CONCLUSION: MBFT significantly and positively impacts visual acuity, NVA, and reading rate in patients with AMD.

关键词： microperimetric biofeedback training agerelated macular degeneration vision rehabilitation

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Comparative Study of Transfer Learning Models for Retinal Disease Diagnosis from Fundus Images

引用

Computers, Materials & Continua 2022年第3期70卷 5821-5834页

作者： Kuntha Pin Jee Ho Chang Yunyoung Nam Department of ICT Convergence Soonchunhyang UniversityAsan31538Korea Department of Ophthalmology Soonchunhyang University Bucheon HospitalSoonchunhyang University College of MedicineBucheon420-767Korea Department of Computer Science and Engineering Soonchunhyang UniversityAsan31538Korea

While the usage of digital ocular fundus image has been widespread in ophthalmology practice,the interpretation of the image has been still on the hands of the ophthalmologists which are quite *** explored a robust deep learning system that detects three major ocular diseases:diabetic retinopathy(DR),glaucoma(GLC),and age-related macular degeneration(AMD).The proposed method is composed of two ***,an initial quality evaluation in the classification system is proposed to filter out poorquality images to enhance its performance,a technique that has not been explored ***,the transfer learning technique is used with various convolutional neural networks(CNN)models that automatically learn a thousand features in the digital retinal image,and are based on those features for diagnosing eye *** performance of many models is conducted to find the optimal model which fits with fundus *** the different CNN models,DenseNet-201 outperforms others with an area under the receiver operating characteristic curve of ***,the corresponding specificities for healthy,DR,GLC,andAMDpatients are found to be 89.52%,96.69%,89.58%,and 100%,*** results demonstrate that the proposed method can reduce the time-consumption by automatically diagnosing multiple eye diseases using computer-aided assistance tools.

关键词： Multiclass classification deep neural networks glaucoma agerelated macular degeneration diabetic retinopathy transfer learning quality evaluation

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

欢迎您,

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

请选择保存的检索档案：

请选择收藏分类：

通借通还

欢迎您,

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：