Enhanced Optic Disk and Cup Segmentation with Glaucoma Screening from Fundus Images using Position encoded CNNs

09/14/2018
by   Vismay Agrawal, et al.
0

In this manuscript, we present a robust method for glaucoma screening from fundus images using an ensemble of convolutional neural networks (CNNs). The pipeline comprises of first segmenting the optic disk and optic cup from the fundus image, then extracting a patch centered around the optic disk and subsequently feeding to the classification network to differentiate the image as diseased or healthy. In the segmentation network, apart from the image, we make use of spatial co-ordinate (X & Y) space so as to learn the structure of interest better. The classification network is composed of a DenseNet201 and a ResNet18 which were pre-trained on a large cohort of natural images. On the REFUGE validation data (n=400), the segmentation network achieved a dice score of 0.88 and 0.64 for optic disc and optic cup respectively. For the tasking differentiating images affected with glaucoma from healthy images, the area under the ROC curve was observed to be 0.85.

READ FULL TEXT

page 6

page 7

research
09/12/2018

Ensemble of Convolutional Neural Networks for Automatic Grading of Diabetic Retinopathy and Macular Edema

In this manuscript, we automate the procedure of grading of diabetic ret...
research
11/17/2015

Classifying and Segmenting Microscopy Images Using Convolutional Multiple Instance Learning

Convolutional neural networks (CNN) have achieved state of the art perfo...
research
08/24/2021

A QuadTree Image Representation for Computational Pathology

The field of computational pathology presents many challenges for comput...
research
06/13/2017

Identifying Spatial Relations in Images using Convolutional Neural Networks

Traditional approaches to building a large scale knowledge graph have us...
research
12/17/2020

A Contrast Synthesized Thalamic Nuclei Segmentation Scheme using Convolutional Neural Networks

Thalamic nuclei have been implicated in several neurological diseases. W...
research
02/19/2020

Towards a Complete Pipeline for Segmenting Nuclei in Feulgen-Stained Images

Cervical cancer is the second most common cancer type in women around th...

Please sign up or login with your details

Forgot password? Click here to reset