Retinal Mosaicking with Vascular Bifurcations Detected on Vessel Mask by a Convolutional Network
Joint Authors
Yang, Wei
Yun, Zhaoqiang
Gou, Xiaofang
Feng, Xiuxia
Cai, Guangwei
Wang, Wenhui
Source
Journal of Healthcare Engineering
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-01-09
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
Mosaicking of retinal images is potentially useful for ophthalmologists and computer-aided diagnostic schemes.
Vascular bifurcations can be used as features for matching and stitching of retinal images.
A fully convolutional network model is employed to segment vascular structures in retinal images to detect vascular bifurcations.
Then, bifurcations are extracted as feature points on the vascular mask by a robust and efficient approach.
Transformation parameters for stitching can be estimated from the correspondence of vascular bifurcations.
The proposed feature detection and mosaic method is evaluated on retinal images of 14 different eyes, 62 retinal images.
The proposed method achieves a considerably higher average recall rate of matching for paired images compared with speeded-up robust features and scale-invariant feature transform.
The running time of our method was also lower than other methods.
Results produced by the proposed method superior to that of AutoStitch, photomerge function in Photoshop cs6 and ICE, demonstrate that accurate matching of detected vascular bifurcations could lead to high-quality mosaic of retinal images.
American Psychological Association (APA)
Feng, Xiuxia& Cai, Guangwei& Gou, Xiaofang& Yun, Zhaoqiang& Wang, Wenhui& Yang, Wei. 2020. Retinal Mosaicking with Vascular Bifurcations Detected on Vessel Mask by a Convolutional Network. Journal of Healthcare Engineering،Vol. 2020, no. 2020, pp.1-13.
https://search.emarefa.net/detail/BIM-1186365
Modern Language Association (MLA)
Feng, Xiuxia…[et al.]. Retinal Mosaicking with Vascular Bifurcations Detected on Vessel Mask by a Convolutional Network. Journal of Healthcare Engineering No. 2020 (2020), pp.1-13.
https://search.emarefa.net/detail/BIM-1186365
American Medical Association (AMA)
Feng, Xiuxia& Cai, Guangwei& Gou, Xiaofang& Yun, Zhaoqiang& Wang, Wenhui& Yang, Wei. Retinal Mosaicking with Vascular Bifurcations Detected on Vessel Mask by a Convolutional Network. Journal of Healthcare Engineering. 2020. Vol. 2020, no. 2020, pp.1-13.
https://search.emarefa.net/detail/BIM-1186365
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1186365