کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6854754 | 1437594 | 2018 | 59 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Retinal vessel segmentation based on Fully Convolutional Neural Networks
ترجمه فارسی عنوان
تقسیم عروق شبکیه بر اساس شبکه های عصبی کاملا متقارن
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کلمات کلیدی
شبکه عصبی کاملا انعطاف پذیر، تبدیل ثابت موجک، تصویر پایه شبکیه تقسیم بندی قایق، یادگیری عمیق،
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
چکیده انگلیسی
The retinal vascular condition is a reliable biomarker of several ophthalmologic and cardiovascular diseases, so automatic vessel segmentation may be crucial to diagnose and monitor them. In this paper, we propose a novel method that combines the multiscale analysis provided by the Stationary Wavelet Transform with a multiscale Fully Convolutional Neural Network to cope with the varying width and direction of the vessel structure in the retina. Our proposal uses rotation operations as the basis of a joint strategy for both data augmentation and prediction, which allows us to explore the information learned during training to refine the segmentation. The method was evaluated on three publicly available databases, achieving an average accuracy of 0.9576, 0.9694, and 0.9653, and average area under the ROC curve of 0.9821, 0.9905, and 0.9855 on the DRIVE, STARE, and CHASE_DB1 databases, respectively. It also appears to be robust to the training set and to the inter-rater variability, which shows its potential for real-world applications.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Expert Systems with Applications - Volume 112, 1 December 2018, Pages 229-242
Journal: Expert Systems with Applications - Volume 112, 1 December 2018, Pages 229-242
نویسندگان
Américo Oliveira, Sérgio Pereira, Carlos A. Silva,