An Automated Aggressive Posterior Retinopathy of Prematurity Diagnosis System by Squeeze and Excitation Hierarchical Bilinear Pooling Network

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.