Atrous Fully Convolved Depth Concatenated Neural Network with Enriched Encoder for Retinal Artery–Vein Classification

ABSTRACT

Continuous monitoring of artery and vein vessels in the human eye to prevent the loss of eyesight is essential in the diagnosis of diabetic retinopathy. The progression of diabetic retinopathy is echoed by the internal anatomical changes of the retina, such as changes in the artery vein ratio, formation of fake vessels, tortuosity, lesion formation, etc. Among these symptoms, calculation of the artery vein ratio is still a challenging task since the visibility of the artery and vein changes over different regions in the fundus image. The proposed Atrous Depth Concatenated neural network with the enriched encoder (EEDCFCNN) architecture for artery vein classification is based on the deep semantic segmentation architecture. The proposed architecture can achieve an improved result on the public databases DRIVE, INSPIRE, and IOSTAR.

KEYWORDS:

• Artery
• Classification
• Convolutional layer
• Depth concatenation
• Encoder
• Vein

Acknowledgement

The authors would like to credit their gratitude to the Management and Principal of Mepco Schlenk Engineering College, Sivakasi for providing the essential research facilities to complete this work successfully.

DISCLOSURE STATEMENT

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

V. Sathananthavathi

V Sathananthavathi received her BE degree from MK University and ME degree in communication systems engineering from the Mepco Schlenk Engineering College, Sivakasi, Tamil Nadu, India in 2010, and completed her PhD in retinal image processing. Her research interests include medical image processing and pattern recognition. She is senior grade assistant professor in Mepco Schlenk Engineering College, Sivakasi, Tamil Nadu, India.

G. Indumathi

G Indumathi received her BE degree from Thiagarajar College of Engineering and an ME degree in communication systems engineering from MK University. She completed her PhD on wireless networks from Anna University in 2012. Her research interests include wireless communication networks and image processing and pattern recognition. She currently serves as professor at Mepco Schlenk Engineering College, Sivakasi, Tamil Nadu, India. Email: [email protected]