Review Article
Volume 11 Issue 2 - 2020
Deep Learning Model for Detection of Retinal Vessels from Digital Fundus Images- A Survey
Md Mohaimenul Islam Hsuan1,2, Tahmina Nasrin Poly1,2, Suleman Atique4, Yu-Chuan (Jack) Li1,2,3 and Hsuan Chia Yang1,2*
1Graduate Institute of Biomedical Informatics, College of Medical Science and Technology, Taipei Medical University, Taipei, Taiwan
2International Center for Health Information Technology (ICHIT), Taipei Medical University, Taipei, Taiwan
3Department of Dermatology, Wan Fang Hospital, Taipei, Taiwan
4Department of Health Informatics, College of Public Health and Health Informatics, University of Hail, Saudi Arabia
*Corresponding Author: Hsuan Chia Yang, Graduate Institute of Biomedical Informatics, College of Medical Science and Technology, Taipei Medical University, Taipei, Taiwan.
Received: October 24, 2019; Published: January 17, 2020




Abstract

Computer-aided detection (CAD) system is a realistic option for physicians to screen fundus images. Automated segmentation of retinal vessel is in fundus important step to identify the retinal disease region. However, identification of the retinal disease region accurately is still challenging due to the varied distribution of blood vessel on noisy and low contrast fundus images. Healthcare system has been changing significantly with the emergence of machine learning (ML), deep learning (DL) and artificial intelligence (AI) in recent year. Retinal vessel detection is one such area of application of deep learning, for improving the accuracy of detection and segmentation and the quality of patient care. Recently, the convolutional neural networks (CNN) have been applied to the detection of the retinal vessel from fundus images and have demonstrated promising results. The range of accuracy of the CNN model was 0.91 - 0.95 and the area under the receiver operating curve was 0.09 - 0.98. Therefore, CNN may play a crucial role in determining the therapeutic methods and detecting the retinal vessel accurately in an individual manner. In this survey, we described the use of CNN in fundus imaging, especially focused on CNN technique, clinical application for retinal vessel detection and future prospective.

Keywords: Computer-Aided Detection; Retinal Vessels; Convolutional Neural Network; Image Detection

References

  1. Jiang Z., et al. “Retinal blood vessel segmentation using fully convolutional network with transfer learning”. Computerized Medical Imaging and Graphics 68 (2018): 1-15.
  2. Hinton G., et al. “Deep neural networks for acoustic modeling in speech recognition”. IEEE Signal Processing Magazine 29 (2012).
  3. Kalinin AA., et al. “Deep learning in pharmacogenomics: from gene regulation to patient stratification”. Pharmacogenomics 19 (2018): 629-650.
  4. Nemati S., et al. “Optimal medication dosing from suboptimal clinical examples: A deep reinforcement learning approach: 2016”. 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), IEEE (2016): 2978-2981. 
  5. Maji D., et al. “Ensemble of deep convolutional neural networks for learning to detect retinal vessels in fundus images”. arXiv (2016): 160304833.
  6. Walczak S. “Neural networks in organizational research: Applying pattern recognition to the analysis of organizational behavior”. Organizational Research Methods 10 (2007): 710.
  7. Guo Y., et al. “A novel retinal vessel detection approach based on multiple deep convolution neural networks”. Computer Methods and Programs in Biomedicine 167 (2018): 43-48.
  8. Oliveira A., et al. “Retinal vessel segmentation based on fully convolutional neural networks”. Expert Systems with Applications 112 (2018): 229-242.
  9. Dasgupta A and Singh S. “A fully convolutional neural network based structured prediction approach towards the retinal vessel segmentation: 2017”. IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017), IEEE (2017): 248-251. 
  10. Şengür A., et al. “A retinal vessel detection approach using convolution neural network: 2017”. International Artificial Intelligence and Data Processing Symposium (IDAP), IEEE (2017): 1-4. 
  11. Li Q., et al. “A cross-modality learning approach for vessel segmentation in retinal images”. IEEE Transactions on Medical Imaging 35 (2015): 109-118.
  12. Lahiri A., et al. “Deep neural ensemble for retinal vessel segmentation in fundus images towards achieving label-free angiography: 2016”. 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), IEEE (2016): 1340-1343. 
  13. Liskowski P and Krawiec K. “Segmenting retinal blood vessels with deep neural networks”. IEEE Transactions on Medical Imaging 35 (2016): 2369-2380.
  14. Fu H., et al. “Retinal vessel segmentation via deep learning network and fully-connected conditional random fields: 2016”. IEEE 13th international symposium on biomedical imaging (ISBI), IEEE (2016): 698-701. 
  15. Fu H., et al. “Deepvessel: Retinal vessel segmentation via deep learning and conditional random field”. International conference on medical image computing and computer-assisted intervention, Springer (2016): 132-139. 
  16. Melinščak M., et al. “Retinal vessel segmentation using deep neural networks”. 10th International Conference on Computer Vision Theory and Applications (VISAPP 2015) (2015). 
Citation: Hsuan Chia Yang., et al. “Deep Learning Model for Detection of Retinal Vessels from Digital Fundus Images- A Survey”. EC Ophthalmology 11.2 (2020): 01-10.

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