A fully automated pipeline of extracting biomarkers to quantify vascular changes in retina-related diseases

ABSTRACT

This paper presents an automated system for extracting retinal vascular biomarkers for early detection of diabetes. The proposed retinal vessel enhancement, segmentation, optic disc (OD) and fovea detection algorithms provide fundamental tools for extracting the vascular network within the predefined region of interest. Based on that, the artery/vein classification, vessel width, tortuosity and fractal dimension measurement tools are used to assess a large number of quantitative vascular biomarkers. We evaluate our pipeline module by module against human annotations. The results indicate that our automated system is robust to the localisation of OD and fovea, segmentation of vessels and classification of arteries/veins. The proposed pipeline helps to increase the effectiveness of the biomarkers extraction and analysis for the early diabetes, and therefore, has the large potential of being further incorporated into a computer-aided diagnosis system.

KEYWORDS:

• Retinal image analysis
• vessel biomarkers
• computer-aided diagnosis
• diabetes

Acknowledgements

This work is part of the NWO-Hé Programme of Innovation Cooperation No. 629.001.003 and the European Foundation for the Study of Diabetes/Chinese Diabetes Society/Lilly project. The authors appreciate the valuable suggestions and comments from the anonymous reviewers.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1. http://www.retinacheck.org/.

Additional information

Funding

This work is part of the NWO-Hé Programme of Innovation Cooperation [No. 629.001.003] and the European Foundation for the Study of Diabetes/Chinese Diabetes Society/Lilly project.

Notes on contributors

Jiong Zhang

Jiong Zhang received the master’s degree in computer science from theNorthwest A&F University, Yangling, China, and the Ph.D. degree fromthe Eindhoven University of Technology, The Netherlands. He then joined as a Post-Doctoral Researcher with the Medical Image Analysis Group, Eindhoven University of Technology, The Netherlands. His research interests include ophthalmologic image analysis, medical image analysis, computer-aided diagnosis, and machine learning.

Behdad Dashtbozorg

Behdad Dashtbozorg received the master’s degree from Yazd University,Iran, and the Ph.D. degree in electrical engineering from the University of Porto, Portugal. He is currently a Post-Doctoral Researcher with the MedicalImage Analysis Group, Eindhoven University of Technology, The Netherlands. His research interests include medical image analysis, image processing, machine learning, and computer vision.

Fan Huang

Fan Huang received the M.Sc. degree in biomedical engineering from theEindhoven University of Technology, The Netherlands, where he is currentlypursuing the Ph.D. degree in biomedical engineering with the BiomedicalImage Analysis Group. His Ph.D. focus is on multiple biomarkers analysisfor diabetes retinopathy using retinal images. His research interest is in digital image analysis, machine learning, and pattern recognition.

Tao Tan

Tao Tan is currently an guest assistant professor with Biomedical Image Analysis (BMIA) at the Department of Biomedical Engineering at the Eindhoven University of Technology, and a consultant of Qview Medical Inc.  Dr. Tan obtained his PhD from Diagnostic Image Analysis Group, Radiology, Radboud University Medical Center.  His main research focuses on ultrasound image analysis including denoising, landmark segmentation, lesion segmentation, registration, computer-aided diagnosis and detection. He has led the development of one FDA approved and one CE approved product in medical imaging. He has served as a committee member, editorial member and reviewer for numerous international conferences and journals in the area of medical imaging.

B. M. ter Haar Romeny

Bart M. ter Haar Romeny received the M.Sc. degree in applied physics fromthe Delft University of Technology in 1979 and the Ph.D. degree from Utrecht University in 1983. He is currently a Professor of medical image analysis with Northeastern University, Shenyang, China, and with the Eindhoven University of Technology, The Netherlands. He is also a Project Leader of the RetinaCheck project. His research interests include brain-inspired medical image analysis and computer-aided diagnosis.