Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4958315 | Computer Methods and Programs in Biomedicine | 2016 | 24 Pages |
Abstract
As manually segmenting and counting exudate areas is a tedious task, having a reliable automated output, such as automated segmentation using convolutional neural networks in combination with other landmark detectors, is an important step in creating automated screening programs for early detection of diabetic retinopathy.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science (General)
Authors
Pavle PrentaÅ¡iÄ, Sven LonÄariÄ,