Dynamic region proposal networks for semantic segmentation in automated glaucoma screening

05/19/2021
by   Shivam Shah, et al.
2

Screening for the diagnosis of glaucoma through a fundus image can be determined by the optic cup to disc diameter ratio (CDR), which requires the segmentation of the cup and disc regions. In this paper, we propose two novel approaches, namely Parameter-Shared Branched Network (PSBN) andWeak Region of Interest Model-based segmentation (WRoIM) to identify disc and cup boundaries. Unlike the previous approaches, the proposed methods are trained end-to-end through a single neural network architecture and use dynamic cropping instead of manual or traditional computer vision-based cropping. We are able to achieve similar performance as that of state-of-the-art approaches with less number of network parameters. Our experiments include comparison with different best known methods on publicly available Drishti-GS1 and RIM-ONE v3 datasets. With 7.8 × 10^6 parameters our approach achieves a Dice score of 0.96/0.89 for disc/cup segmentation on Drishti-GS1 data whereas the existing state-of-the-art approach uses 19.8× 10^6 parameters to achieve a dice score of 0.97/0.89.

READ FULL TEXT

page 1

page 3

page 4

research
06/14/2017

LinkNet: Exploiting Encoder Representations for Efficient Semantic Segmentation

Pixel-wise semantic segmentation for visual scene understanding not only...
research
04/04/2017

Optic Disc and Cup Segmentation Methods for Glaucoma Detection with Modification of U-Net Convolutional Neural Network

Glaucoma is the second leading cause of blindness all over the world, wi...
research
06/07/2016

ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation

The ability to perform pixel-wise semantic segmentation in real-time is ...
research
04/06/2022

PlutoNet: An Efficient Polyp Segmentation Network

Polyps in the colon can turn into cancerous cells if not removed with ea...
research
09/16/2021

Automated risk classification of colon biopsies based on semantic segmentation of histopathology images

Artificial Intelligence (AI) can potentially support histopathologists i...
research
03/15/2022

CaRTS: Causality-driven Robot Tool Segmentation from Vision and Kinematics Data

Vision-based segmentation of the robotic tool during robot-assisted surg...
research
10/03/2022

Automatic Assessment of Functional Movement Screening Exercises with Deep Learning Architectures

(1) Background: The success of physiotherapy depends on the regular and ...

Please sign up or login with your details

Forgot password? Click here to reset