Details

Autor(en) / Beteiligte

• Sayed, Md. Abu
• Saha, Sajib
• Rahaman, G. M. Atiqur
• Ghosh, Tanmai K.
• Kanagasingam, Yogesan
• Wilk, Szymon
• ten Teije, Annette
• Riaño, David

Titel

A Semi-supervised Approach to Segment Retinal Blood Vessels in Color Fundus Photographs

Ist Teil von

• Artificial Intelligence in Medicine, 2019, p.347-351

Ort / Verlag

Cham: Springer International Publishing

Erscheinungsjahr

2019

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• Segmentation of retinal blood vessels is an important diagnostic procedure in ophthalmology. In this paper we propose an automated blood vessels segmentation method that combines both supervised and un-supervised approaches. A novel descriptor named Local Haar Pattern (LHP) is proposed to describe retinal pixel of interest. The performance of the proposed method has been evaluated on three publicly available DRIVE, STARE and CHASE_DB1 datasets. The proposed method achieves an overall segmentation accuracy of 96%, 96% and 95% respectively on DRIVE, STARE, and CHASE DB1 datasets, which are better than the state-of-the-art methods.