An Inception Inspired Deep Network to Analyse Fundus Images
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Dosyalar
Tarih
2019
Yazarlar
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Yayıncı
Ieee
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
A fundus image usually contains the optic disc, pathologies and other structures in addition to vessels to be segmented. This study proposes a deep network for vessel segmentation, whose architecture is inspired by inception modules. The network contains three sub-networks, each with a different filter size, which are connected in the last layer of the proposed network. According to experiments conducted in the DRIVE and IOSTAR, the performance of our network is found to be better than or comparable to that of the previous methods. We also observe that the sub-networks pay attention to different parts of an input image when producing an output map in the last layer of the proposed network; though, training of the proposed network is not constrained for this purpose.
Açıklama
11th International Conference on Electrical and Electronics Engineering (ELECO) -- NOV 28-30, 2019 -- Bursa, TURKEY
Anahtar Kelimeler
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Kaynak
2019 11Th International Conference On Electrical And Electronics Engineering (Eleco 2019)
WoS Q Değeri
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Scopus Q Değeri
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