IEICE TRANSACTIONS on Fundamentals
Optic Disc Detection Based on Saliency Detection and Attention Convolutional Neural Networks
Summary :
The automatic analysis of retinal fundus images is of great significance in large-scale ocular pathologies screening, of which optic disc (OD) location is a prerequisite step. In this paper, we propose a method based on saliency detection and attention convolutional neural network for OD detection. Firstly, the wavelet transform based saliency detection method is used to detect the OD candidate regions to the maximum extent such that the intensity, edge and texture features of the fundus images are all considered into the OD detection process. Then, the attention mechanism that can emphasize the representation of OD region is combined into the dense network. Finally, it is determined whether the detected candidate regions are OD region or non-OD region. The proposed method is implemented on DIARETDB0, DIARETDB1 and MESSIDOR datasets, the experimental results of which demonstrate its superiority and robustness.
- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E104-A No.9 pp.1370-1374
- Publication Date
- 2021/09/01
- Publicized
- 2021/03/23
- Online ISSN
- 1745-1337
- DOI
- 10.1587/transfun.2020EAL2122
- Type of Manuscript
- LETTER
- Category
- Image
Authors
Ying WANG
Northeastern University
Xiaosheng YU
Northeastern University
Chengdong WU
Northeastern University
Keyword
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Ying WANG, Xiaosheng YU, Chengdong WU, "Optic Disc Detection Based on Saliency Detection and Attention Convolutional Neural Networks" in IEICE TRANSACTIONS on Fundamentals,
vol. E104-A, no. 9, pp. 1370-1374, September 2021, doi: 10.1587/transfun.2020EAL2122.
Abstract: The automatic analysis of retinal fundus images is of great significance in large-scale ocular pathologies screening, of which optic disc (OD) location is a prerequisite step. In this paper, we propose a method based on saliency detection and attention convolutional neural network for OD detection. Firstly, the wavelet transform based saliency detection method is used to detect the OD candidate regions to the maximum extent such that the intensity, edge and texture features of the fundus images are all considered into the OD detection process. Then, the attention mechanism that can emphasize the representation of OD region is combined into the dense network. Finally, it is determined whether the detected candidate regions are OD region or non-OD region. The proposed method is implemented on DIARETDB0, DIARETDB1 and MESSIDOR datasets, the experimental results of which demonstrate its superiority and robustness.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.2020EAL2122/_p
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@ARTICLE{e104-a_9_1370,
author={Ying WANG, Xiaosheng YU, Chengdong WU, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Optic Disc Detection Based on Saliency Detection and Attention Convolutional Neural Networks},
year={2021},
volume={E104-A},
number={9},
pages={1370-1374},
abstract={The automatic analysis of retinal fundus images is of great significance in large-scale ocular pathologies screening, of which optic disc (OD) location is a prerequisite step. In this paper, we propose a method based on saliency detection and attention convolutional neural network for OD detection. Firstly, the wavelet transform based saliency detection method is used to detect the OD candidate regions to the maximum extent such that the intensity, edge and texture features of the fundus images are all considered into the OD detection process. Then, the attention mechanism that can emphasize the representation of OD region is combined into the dense network. Finally, it is determined whether the detected candidate regions are OD region or non-OD region. The proposed method is implemented on DIARETDB0, DIARETDB1 and MESSIDOR datasets, the experimental results of which demonstrate its superiority and robustness.},
keywords={},
doi={10.1587/transfun.2020EAL2122},
ISSN={1745-1337},
month={September},}
Copy
TY - JOUR
TI - Optic Disc Detection Based on Saliency Detection and Attention Convolutional Neural Networks
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 1370
EP - 1374
AU - Ying WANG
AU - Xiaosheng YU
AU - Chengdong WU
PY - 2021
DO - 10.1587/transfun.2020EAL2122
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E104-A
IS - 9
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - September 2021
AB - The automatic analysis of retinal fundus images is of great significance in large-scale ocular pathologies screening, of which optic disc (OD) location is a prerequisite step. In this paper, we propose a method based on saliency detection and attention convolutional neural network for OD detection. Firstly, the wavelet transform based saliency detection method is used to detect the OD candidate regions to the maximum extent such that the intensity, edge and texture features of the fundus images are all considered into the OD detection process. Then, the attention mechanism that can emphasize the representation of OD region is combined into the dense network. Finally, it is determined whether the detected candidate regions are OD region or non-OD region. The proposed method is implemented on DIARETDB0, DIARETDB1 and MESSIDOR datasets, the experimental results of which demonstrate its superiority and robustness.
ER -
English
