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Automatic detection and recognition of multiple macular lesions in retinal optical coherence tomography images with multi-instance multilabel learning

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成果类型:
期刊论文
作者:
Fang, Leyuan;Yang, Liumao;Li, Shutao*;Rabbani, Hossein;Liu, Zhimin;...
通讯作者:
Li, Shutao
作者机构:
[Yang, Liumao; Fang, Leyuan; Li, Shutao] Hunan Univ, Coll Elect & Informat Engn, Changsha, Hunan, Peoples R China.
[Rabbani, Hossein] Isfahan Univ Med Sci, Med Image & Signal Proc Res Ctr, Esfahan, Iran.
[Liu, Zhimin; Peng, Qinghua; Chen, Xiangdong] Hunan Univ Chinese Med, Dept Ophthalmol, Affiliated Hosp 1, Changsha, Hunan, Peoples R China.
通讯机构:
[Li, Shutao] H
Hunan Univ, Coll Elect & Informat Engn, Changsha, Hunan, Peoples R China.
语种:
英文
关键词:
optical coherence tomography;image processing;automated detection;macular lesions;multiple labels;Optical coherence tomography;Sensors;Eye
期刊:
Journal of Biomedical Optics
ISSN:
1083-3668
年:
2017
卷:
22
期:
6
页码:
066014
基金类别:
National Natural Science Fund of ChinaNational Natural Science Foundation of China (NSFC) [61325007, 61520106001]; National Natural Science Foundation for Young Scientist of ChinaNational Natural Science Foundation of China (NSFC) [61501180]
机构署名:
本校为其他机构
院系归属:
第一中医临床学院
摘要:
Detection and recognition of macular lesions in optical coherence tomography (OCT) are very important for retinal diseases diagnosis and treatment. As one kind of retinal disease (e.g., diabetic retinopathy) may contain multiple lesions (e.g., edema, exudates, and microaneurysms) and eye patients may suffer from multiple retinal diseases, multiple lesions often coexist within one retinal image. Therefore, one single-lesion-based detector may not support the diagnosis of clinical eye diseases. To address this issue, we propose a multi-instance multilabel-based lesions recognition (MIML-LR) meth...

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