Comparative Analysis of Deep Learning Architectures for Macular Hole Segmentation in OCT Images: A Performance Evaluation of U-Net Variants

This study presents a comprehensive comparison of U-Net variants with different backbone architectures for Macular Hole (MH) segmentation in optical coherence tomography (OCT) images. We evaluated eleven architectures, including U-Net combined with InceptionNetV4, VGG16, VGG19, ResNet152, DenseNet12...

全面介紹

書目詳細資料

發表在:	Journal of Imaging
Main Authors:	H. M. S. S. Herath, S. L. P. Yasakethu, Nuwan Madusanka, Myunggi Yi, Byeong-Il Lee
格式:	Article
語言:	英语
出版:	MDPI AG 2025-02-01
主題:	optical coherence tomography segmentation convolutional neural networks macular hole
在線閱讀:	https://www.mdpi.com/2313-433X/11/2/53