作者
Ruwan Tennakoon, Amirali K Gostar, Reza Hoseinnezhad, Alireza Bab-Hadiashar
发表日期
2018/4/4
研讨会论文
2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018)
页码范围
1436-1440
出版商
IEEE
简介
This paper proposes a novel method in order to obtain voxel-level segmentation for three fluid lesion types (IR-F/SRF/PED) in OCT images provided by the ReTOUCH challenge [1]. The method is based on a deep neural network consisting of encoding and de-coding blocks connected with skip-connections which was trained using a combined cost function comprising of cross-entropy, dice and adversarial loss terms. The segmentation results on a held-out validation set shows that the network architecture and the loss functions used has resulted in improved retinal fluid segmentation. Our method was ranked fourth in the ReTOUCH challenge.
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R Tennakoon, AK Gostar, R Hoseinnezhad… - 2018 IEEE 15th International Symposium on …, 2018