Guided Adversarial Adaptation Network for Retinal and Choroidal Layer Segmentation
暂无分享,去创建一个
Jiang Liu | Yitian Zhao | Yalin Zheng | Jingyu Zhao | Jiong Zhang | Bin Deng | Ran Song | Jiang Liu | Yitian Zhao | Yalin Zheng | Jiong Zhang | Ran Song | Bin Deng | Jingyu Zhao
[1] Se Woong Kang,et al. Choroidal thickness in polypoidal choroidal vasculopathy and exudative age-related macular degeneration. , 2011, Ophthalmology.
[2] Thomas Brox,et al. U-Net: Convolutional Networks for Biomedical Image Segmentation , 2015, MICCAI.
[3] F. Lu,et al. Macular Thickness Profiles of Intraretinal Layers in Myopia Evaluated by Ultrahigh-Resolution Optical Coherence Tomography. , 2015, American journal of ophthalmology.
[4] Paul Babyn,et al. Generative Adversarial Network in Medical Imaging: A Review , 2018, Medical Image Anal..
[5] D. Mackey,et al. Age-dependent regional retinal nerve fibre changes in SIX1/SIX6 polymorphism , 2020, Scientific Reports.
[6] J. Jonas,et al. Choroidal vessel diameter in central serous chorioretinopathy , 2013, Acta ophthalmologica.
[7] L. Zangwill,et al. The retinal nerve fiber layer thickness in ocular hypertensive, normal, and glaucomatous eyes with optical coherence tomography. , 2000, Archives of ophthalmology.
[8] Alejandro F. Frangi,et al. CS-Net: Channel and Spatial Attention Network for Curvilinear Structure Segmentation , 2019, MICCAI.
[9] Alejandro F. Frangi,et al. CS2-Net: Deep Learning Segmentation of Curvilinear Structures in Medical Imaging , 2020, Medical Image Anal..
[10] James Bailey,et al. Understanding Adversarial Attacks on Deep Learning Based Medical Image Analysis Systems , 2019, Pattern Recognit..