تقرير
Pathological OCT Retinal Layer Segmentation using Branch Residual U-shape Networks
| العنوان: | Pathological OCT Retinal Layer Segmentation using Branch Residual U-shape Networks |
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| المؤلفون: | Apostolopoulos, Stefanos, De Zanet, Sandro, Ciller, Carlos, Wolf, Sebastian, Sznitman, Raphael |
| سنة النشر: | 2017 |
| المجموعة: | Computer Science |
| مصطلحات موضوعية: | Computer Science - Computer Vision and Pattern Recognition |
| الوصف: | The automatic segmentation of retinal layer structures enables clinically-relevant quantification and monitoring of eye disorders over time in OCT imaging. Eyes with late-stage diseases are particularly challenging to segment, as their shape is highly warped due to pathological biomarkers. In this context, we propose a novel fully Convolutional Neural Network (CNN) architecture which combines dilated residual blocks in an asymmetric U-shape configuration, and can segment multiple layers of highly pathological eyes in one shot. We validate our approach on a dataset of late-stage AMD patients and demonstrate lower computational costs and higher performance compared to other state-of-the-art methods. Comment: 9 pages, 5 figures, MICCAI 2017 |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/1707.04931 |
| رقم الأكسشن: | edsarx.1707.04931 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |