Sorry, you need to enable JavaScript to visit this website.

facebooktwittermailshare

A segmentation based deep learning framework for multimodal retinal image registration

Abstract: 

Multimodal image registration plays an important role in diagnosing and treating ophthalmologic diseases. In this paper, a deep learning framework for multimodal retinal image registration is proposed. The framework consists of a segmentation network, feature detection and description network, and an outlier rejection network, which focuses only on the globally coarse alignment step using the perspective transformation. We apply the proposed framework to register color fundus images with infrared reflectance images and compare it with the state-of-the-art conventional and learning-based approaches. The proposed framework demonstrates a significant improvement in robustness and accuracy reflected by a higher success rate and Dice coefficient compared to other coarse alignment methods.

up
0 users have voted:

Paper Details

Authors:
Yiqian Wang, Junkang Zhang, Cheolhong An, Melina Cavichini, Mahima Jhingan, Manuel J. Amador-Patarroyo, Christopher P. Long, Dirk-Uwe G. Bartsch, William R. Freeman, Truong Q. Nguyen
Submitted On:
13 May 2020 - 4:42pm
Short Link:
Type:
Presentation Slides
Event:
Presenter's Name:
Yiqian Wang
Document Year:
2020
Cite

Document Files

ICASSP_slides_final.pdf

(49)

Subscribe

[1] Yiqian Wang, Junkang Zhang, Cheolhong An, Melina Cavichini, Mahima Jhingan, Manuel J. Amador-Patarroyo, Christopher P. Long, Dirk-Uwe G. Bartsch, William R. Freeman, Truong Q. Nguyen, "A segmentation based deep learning framework for multimodal retinal image registration", IEEE SigPort, 2020. [Online]. Available: http://sigport.org/5134. Accessed: Sep. 30, 2020.
@article{5134-20,
url = {http://sigport.org/5134},
author = {Yiqian Wang; Junkang Zhang; Cheolhong An; Melina Cavichini; Mahima Jhingan; Manuel J. Amador-Patarroyo; Christopher P. Long; Dirk-Uwe G. Bartsch; William R. Freeman; Truong Q. Nguyen },
publisher = {IEEE SigPort},
title = {A segmentation based deep learning framework for multimodal retinal image registration},
year = {2020} }
TY - EJOUR
T1 - A segmentation based deep learning framework for multimodal retinal image registration
AU - Yiqian Wang; Junkang Zhang; Cheolhong An; Melina Cavichini; Mahima Jhingan; Manuel J. Amador-Patarroyo; Christopher P. Long; Dirk-Uwe G. Bartsch; William R. Freeman; Truong Q. Nguyen
PY - 2020
PB - IEEE SigPort
UR - http://sigport.org/5134
ER -
Yiqian Wang, Junkang Zhang, Cheolhong An, Melina Cavichini, Mahima Jhingan, Manuel J. Amador-Patarroyo, Christopher P. Long, Dirk-Uwe G. Bartsch, William R. Freeman, Truong Q. Nguyen. (2020). A segmentation based deep learning framework for multimodal retinal image registration. IEEE SigPort. http://sigport.org/5134
Yiqian Wang, Junkang Zhang, Cheolhong An, Melina Cavichini, Mahima Jhingan, Manuel J. Amador-Patarroyo, Christopher P. Long, Dirk-Uwe G. Bartsch, William R. Freeman, Truong Q. Nguyen, 2020. A segmentation based deep learning framework for multimodal retinal image registration. Available at: http://sigport.org/5134.
Yiqian Wang, Junkang Zhang, Cheolhong An, Melina Cavichini, Mahima Jhingan, Manuel J. Amador-Patarroyo, Christopher P. Long, Dirk-Uwe G. Bartsch, William R. Freeman, Truong Q. Nguyen. (2020). "A segmentation based deep learning framework for multimodal retinal image registration." Web.
1. Yiqian Wang, Junkang Zhang, Cheolhong An, Melina Cavichini, Mahima Jhingan, Manuel J. Amador-Patarroyo, Christopher P. Long, Dirk-Uwe G. Bartsch, William R. Freeman, Truong Q. Nguyen. A segmentation based deep learning framework for multimodal retinal image registration [Internet]. IEEE SigPort; 2020. Available from : http://sigport.org/5134