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Computer-Based Image Analysis for Plus Disease Diagnosis in Retinopathy of Prematurity: Performance of the i-ROP System and Image Features Associated With Expert Diagnosis

机译：基于计算机的图像分析用于早产儿视网膜病变的正病诊断： i-ROP系统的性能和与专家诊断相关的图像特征

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摘要

PurposeWe developed and evaluated the performance of a novel computer-based image analysis system for grading plus disease in retinopathy of prematurity (ROP), and identified the image features, shapes, and sizes that best correlate with expert diagnosis.

机译：目的我们开发并评估了一种新型的基于计算机的图像分析系统的性能，该系统可用于对早产儿视网膜病变（ROP）进行分级和疾病分析，并确定与专家诊断最相关的图像特征，形状和大小。

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期刊名称 Translational Vision Science Technology
作者
Esra Ataer-Cansizoglu; Veronica Bolon-Canedo; J. Peter Campbell; Alican Bozkurt; Deniz Erdogmus; Jayashree Kalpathy-Cramer; Samir Patel; Karyn Jonas; R. V. Paul Chan; Susan Ostmo; Michael F. Chiang;
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年(卷),期 -1(4),6
年度 -1
页码 5
总页数 12
原文格式 PDF
正文语种
中图分类眼科学;
关键词
computer-based image analysis retinopathy of prematurity machine learning;

机译：基于计算机的图像分析;早产儿视网膜病变;机器学习;

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专利

1. Expert Diagnosis of Plus Disease in Retinopathy of Prematurity From Computer-Based Image Analysis [J] . Campbell J. Peter, Ataer-Cansizoglu Esra, Bolon-Canedo Veronica, JAMA ophthalmology . 2016,第6期

机译：基于计算机图像分析的早产儿视网膜病变加病的专家诊断
2. Computer-based image analysis for plus disease diagnosis in retinopathy of prematurity [J] . WittenbergL.A., JonssonN.J., PaulChanR.V., Journal of pediatric ophthalmology and strabismus . 2012,第1期

机译：基于计算机的图像分析，用于早产儿视网膜病变的正病诊断
3. Artificial intelligence in retinopathy of prematurity: clinical validation of a fully automated deep learning system (i-ROP DL) for plus disease diagnosis [J] . Campbell J. Peter, Brown James M., Ostmo Susan, Investigative ophthalmology & visual science . 2018,第9期

机译：治疗视网膜病变的人工智能：全自动深度学习系统（I-ROP DL）的临床验证加上疾病诊断
4. Computer-aided Diagnosis of Retinopathy of Prematurity via Analysis of the Vascular Architecture in Retinal Fundus Images of Preterm Infants [C] . Faraz Oloumi, Rangaraj M. Rangayyan, Anna L. Ells Doctoral Consortium . 2014

机译：通过分析早产儿血管基底图像血管结构的血管结构视网膜病变的计算机辅助诊断
5. Medical imaging: Requirements analysis for automating diabetic retinopathy monitoring and diagnosis. [D] . Kornechuk, Thomas Daniel. 2003

机译：医学影像：糖尿病视网膜病变自动化监测和诊断的需求分析。
6. Expert diagnosis of plus disease in retinopathy of prematurity from computer-based image analysis [O] . J. Peter Campbell, Esra Ataer-Cansizoglu, Veronica Bolon-Canedo, -1

机译：基于计算机图像分析的早产儿视网膜病变加病的专家诊断
7. ABSTRACT Various body parts or organs can be analysed to identify the different diseases in the human body. Fingernail analysis is one of the ways to identify disease in the human body. Nails are the body part which are farthest from the heart and therefore receive oxygen at last. As a result the nails are the first who show the symptoms of a disease in the human body. Fingernails can be easily captured for diagnosis and there are no heavy equipment or no specific conditions required to use nail image for disease diagnosis, like in other tests and scanning processes. Human nails deliver beneficial information about complaints or any nutritive imbalances in the human body depending upon their shape, texture and colour. In human beings, numerous systemic and skin diseases can be easily analyzed through careful examination of nails of both the limbs. A lot of nail illnesses have been found to be primary signs of numerous underlying systemic illnesses. The colour, texture or shape changes in nails are signs of many diseases mainly affecting nails. Considering all these properties of nails a system is proposed that uses digital image processing (DIP) methods for identifying such changes in the human nail to get more precise results and predict numerous diseases effortlessly. With the emerging Internet of Things (IOT) concept the generated report is made available remotely, this will help users to reduce transportation efforts. As the system has to deal with large and private data, the security of data must be ensured. To keep the data confidential, the Blockchain concept which is one of the most emerging concepts in the field of data management is used. The paper contains the implementation of the digital image processing for feature extraction of nail images, usage of IOT (ThingSpeak cloud) for data storage and implementation of Blockchain to keep the system secured and theft free. KEY WORDS: Int ernet of thin gs (IOT), Image proc essin g, Thin gSpeak, RG B vavalues, Mean pi xel vavalues, Bloc kchain , Hash key. Disease Diagnostic System: Abnormalities in Human Nail [O] . Pranav S. Wazarkar 2020

机译：摘要的各个身体部位或器官可被分析以识别在人体内的不同的疾病。指甲分析来识别人体疾病的方法之一。指甲是身体一部分是离心脏最远，因此在最后接受氧气。作为结果，指甲是第一谁表现出人体疾病的症状。指甲可以容易地捕获用于诊断和没有重装或需要使用指甲图像用于疾病诊断，比如在其他测试和扫描过程没有特定的条件。人的指甲提供有关投诉或取决于它们的形状，纹理和色彩在人体内的任何营养失衡有益的信息。在人类中，许多全身性皮肤疾病是可以很容易地通过两个四肢指甲的仔细检查分析。很多指甲病已发现众多潜在系统性疾病的主要症状。在指甲的颜色，质地和形状的变化是许多疾病主要影响指甲的迹象。考虑到所有的指甲的这些性能的系统被提出，用于识别人指甲这样的变化以获得更精确的结果，并毫不费力预测许多疾病用途的数字图像处理（DIP）方法。随着物联网（IOT）的概念，新兴的互联网将生成的报告提供远程，这将帮助用户降低运输工作。由于系统必须处理大量的私人数据，数据的安全性必须得到保证。为了保持数据的机密性，使用Blockchain的概念，它是在数据管理领域的大多数新兴的概念之一。本文包含了数字图像处理的指甲图像，IOT（ThingSpeak云）的使用为数据存储和执行Blockchain的特征提取的执行，以保持固定的系统和盗窃免费。关键词：诠释薄GS（IOT），图像的ERNET PROC essin克，薄型gSpeak，RG乙vavalues，平均数PI XEL vavalues，阵营kchain，哈希密钥。疾病诊断系统：在人类指甲异常

Computer-Based Image Analysis for Plus Disease Diagnosis in Retinopathy of Prematurity: Performance of the i-ROP System and Image Features Associated With Expert Diagnosis

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