@inproceedings{678c2042984a4704a769fbc578c73108,
title = "Network Pruning for OCT Image Classification",
abstract = "Convolutional neural network (CNN) has expanded rapidly, and has been widely used in medical image classification. The large number of parameters in a neural network makes CNN models computationally expensive. This leads to slow inference speed, especially for 3D data such as optical coherence tomography (OCT) for retinal images. A volume OCT scan of retina often contains hundreds of 2D images which needs to be analyzed sequentially in a local computer with limited computational resources. We introduce network pruning to OCT images classification and propose an algorithm to prune networks. We compress the popular classification models, such as ResNet and VGG. For example, within 1% accuracy loss, we compress ResNet-18 from 44.8 MB to 69 KB and VGG-16 from 537.1 MB to 194 KB. These pruned models are much smaller and easier to deploy on the OCT devices. As for the inference speed, the pruned models are 10 to 20 times faster than original models for ResNet and VGG in CPU.",
keywords = "Classification, Network pruning, OCT",
author = "Bing Yang and Yi Zhang and Jun Cheng and Jin Zhang and Lei Mou and Huaying Hao and Yitian Zhao and Jiang Liu",
note = "Publisher Copyright: {\textcopyright} Springer Nature Switzerland AG 2019.; 6th International Workshop on Ophthalmic Medical Image Analysis, OMIA 2019, held in conjunction with the 22nd International Conference on Medical Imaging Computing and Computer-Assisted Intervention, MICCAI 2019 ; Conference date: 17-10-2019 Through 17-10-2019",
year = "2019",
doi = "10.1007/978-3-030-32956-3_15",
language = "English",
isbn = "9783030329556",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer",
pages = "121--129",
editor = "Huazhu Fu and Garvin, {Mona K.} and Tom MacGillivray and Yanwu Xu and Yalin Zheng",
booktitle = "Ophthalmic Medical Image Analysis - 6th International Workshop, OMIA 2019, Held in Conjunction with MICCAI 2019, Proceedings",
}