首页> 外文会议>International Workshop on Ophthalmic Medical Image Analysis;International Conference on Medical Image Computing and Computer-Assisted Intervention >An Automated Aggressive Posterior Retinopathy of Prematurity Diagnosis System by Squeeze and Excitation Hierarchical Bilinear Pooling Network
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An Automated Aggressive Posterior Retinopathy of Prematurity Diagnosis System by Squeeze and Excitation Hierarchical Bilinear Pooling Network

机译:挤压和激励等级双线性汇集网络自动侵袭性后视网膜疗效

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Aggressive Posterior Retinopathy of Prematurity (AP-ROP) is a special type of Retinopathy of Prematurity (ROP), which is one of the most common childhood blindness that occurs in premature infants. AP-ROP is uncommon, atypical, progresses rapidly and prone to misdiagnosis. If it is not detected and treated timely, it will rapidly progress to the fifth stage of ROP that causes easily retinal detachment and blindness. Early diagnosis of AP-ROP is the key to reduce the blindness rate of the disease. In this paper, we apply computer-aided methods for early AP-ROP diagnosis. The proposed method utilizes a Squeeze and Excitation Hierarchical Bilinear Pooling (SE-HBP) network to complete early diagnosis of AP-ROP. Specifically, the SE module can automatically obtain the important information of the channel, where the useless features are suppressed and the useful features are emphasized to enhance the feature extraction capability of the network. The HBP module can complement the information of the feature layers to capture the feature relationship between the layers so that the representation ability of the model can be enhanced. Finally, in order to solve the imbalance problem of AP-ROP fundus image data, we use a focal loss function, which can effectively alleviate the accuracy reduction that caused by the data imbalance. The experimental results show that our system can effectively distinguish AP-ROP with the fundus images, which has a potential application in assisting the ophthalmologists to determine the AP-ROP.
机译:早产儿(AP-ROP)的侵略性后视网膜病变是一种特殊类型的早产儿(ROP),是在早产儿发生的最常见的儿童失明之一。 AP-ROP罕见,非典型,迅速发展,易于误诊。如果未检测到并及时对待,它将迅速进入ROP的第五阶段,导致容易视网膜脱离和失明。 AP-ROP的早期诊断是降低疾病失明率的关键。在本文中,我们应用了用于早期AP-ROP诊断的计算机辅助方法。所提出的方法利用挤压和激发分层双线性汇集(SE-HBP)网络来完成AP-ROP的早期诊断。具体地,SE模块可以自动获得信道的重要信息,其中抑制无用特征,并且强调有用的特征以增强网络的特征提取能力。 HBP模块可以补充特征层的信息以捕获层之间的特征关系,以便可以增强模型的表示能力。最后,为了解决AP-ROP USPUS图像数据的不平衡问题,我们使用焦损函数,可以有效缓解由数据不平衡引起的精度降低。实验结果表明,我们的系统可以有效地将AP-ROP与眼底图像区分开,这在辅助眼科医生确定AP-ROP方面具有潜在的应用。

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