The Channel Attention based Context Encoder Network for Inner Limiting Membrane Detection

08/09/2019
by   Hao Qiu, et al.
2

The optic disc segmentation is an important step for retinal image-based disease diagnosis such as glaucoma. The inner limiting membrane (ILM) is the first boundary in the OCT, which can help to extract the retinal pigment epithelium (RPE) through gradient edge information to locate the boundary of the optic disc. Thus, the ILM layer segmentation is of great importance for optic disc localization. In this paper, we build a new optic disc centered dataset from 20 volunteers and manually annotated the ILM boundary in each OCT scan as ground-truth. We also propose a channel attention based context encoder network modified from the CE-Net to segment the optic disc. It mainly contains three phases: the encoder module, the channel attention based context encoder module, and the decoder module. Finally, we demonstrate that our proposed method achieves state-of-the-art disc segmentation performance on our dataset mentioned above.

READ FULL TEXT

page 2

page 7

research
02/01/2022

A generalizable approach based on U-Net model for automatic Intra retinal cyst segmentation in SD-OCT images

Intra retinal fluids or Cysts are one of the important symptoms of macul...
research
04/07/2020

SA-UNet: Spatial Attention U-Net for Retinal Vessel Segmentation

The precise segmentation of retinal blood vessel is of great significanc...
research
08/07/2020

NuI-Go: Recursive Non-Local Encoder-Decoder Network for Retinal Image Non-Uniform Illumination Removal

Retinal images have been widely used by clinicians for early diagnosis o...
research
11/01/2020

DeepOpht: Medical Report Generation for Retinal Images via Deep Models and Visual Explanation

In this work, we propose an AI-based method that intends to improve the ...
research
07/23/2022

Orientation and Context Entangled Network for Retinal Vessel Segmentation

Most of the existing deep learning based methods for vessel segmentation...
research
04/08/2021

BEFD: Boundary Enhancement and Feature Denoising for Vessel Segmentation

Blood vessel segmentation is crucial for many diagnostic and research ap...
research
06/17/2022

CTooth: A Fully Annotated 3D Dataset and Benchmark for Tooth Volume Segmentation on Cone Beam Computed Tomography Images

3D tooth segmentation is a prerequisite for computer-aided dental diagno...

Please sign up or login with your details

Forgot password? Click here to reset