TY - GEN
T1 - Multiple ocular diseases detection based on joint sparse multi-task learning
AU - Chen, Xiangyu
AU - Xu, Yanwu
AU - Yin, Fengshou
AU - Zhang, Zhuo
AU - Wong, Damon Wing Kee
AU - Wong, Tien Yin
AU - Liu, Jiang
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/11/4
Y1 - 2015/11/4
N2 - In this paper, we present a multiple ocular diseases detection scheme based on joint sparse multi-task learning. Glaucoma, Pathological Myopia (PM), and Age-related Macular Degeneration (AMD) are three major causes of vision impairment and blindness worldwide. The proposed joint sparse multitask learning framework aims to reconstruct a test fundus image with multiple features from as few training subjects as possible. The linear version of this problem could be casted into a multi-task joint covariate selection model, which can be very efficiently optimized via kernelizable accelerated proximal gradient method. Extensive experiments are conducted in order to validate the proposed framework on the SiMES dataset. From the Area Under Curve (AUC) results in multiple ocular diseases classification, our method is shown to outperform the state-of-the-art algorithms.
AB - In this paper, we present a multiple ocular diseases detection scheme based on joint sparse multi-task learning. Glaucoma, Pathological Myopia (PM), and Age-related Macular Degeneration (AMD) are three major causes of vision impairment and blindness worldwide. The proposed joint sparse multitask learning framework aims to reconstruct a test fundus image with multiple features from as few training subjects as possible. The linear version of this problem could be casted into a multi-task joint covariate selection model, which can be very efficiently optimized via kernelizable accelerated proximal gradient method. Extensive experiments are conducted in order to validate the proposed framework on the SiMES dataset. From the Area Under Curve (AUC) results in multiple ocular diseases classification, our method is shown to outperform the state-of-the-art algorithms.
UR - http://www.scopus.com/inward/record.url?scp=84953214605&partnerID=8YFLogxK
U2 - 10.1109/EMBC.2015.7319578
DO - 10.1109/EMBC.2015.7319578
M3 - Conference contribution
C2 - 26737478
AN - SCOPUS:84953214605
T3 - Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
SP - 5260
EP - 5263
BT - 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015
Y2 - 25 August 2015 through 29 August 2015
ER -
