Open-Appositional-Synechial Anterior Chamber Angle Classification in AS-OCT Sequences

Hao，Huaying1,5; Fu，Huazhu2; Xu，Yanwu1; Yang，Jianlong1,5; Li，Fei4,5; Zhang，Xiulan4,5; Liu，Jiang3,5; Zhao，Yitian1,5

10.1007/978-3-030-59722-1_69

2020

0302-9743

1611-3349

LECT NOTES ARTIF INT

12265 LNCS

715-724

Anterior chamber angle (ACA) classification is a key step in the diagnosis of angle-closure glaucoma in Anterior Segment Optical Coherence Tomography (AS-OCT). Existing automated analysis methods focus on a binary classification system (i.e., open angle or angle-closure) in a 2D AS-OCT slice. However, clinical diagnosis requires a more discriminating ACA three-class system (i.e., open, appositional, or synechial angles) for the benefit of clinicians who seek better to understand the progression of the spectrum of angle-closure glaucoma types. To address this, we propose a novel sequence multi-scale aggregation deep network (SMA-Net) for open-appositional-synechial ACA classification based on an AS-OCT sequence. In our method, a Multi-Scale Discriminative Aggregation (MSDA) block is utilized to learn the multi-scale representations at slice level, while a ConvLSTM is introduced to study the temporal dynamics of these representations at sequence level. Finally, a multi-level loss function is used to combine the slice-based and sequence-based losses. The proposed method is evaluated across two AS-OCT datasets. The experimental results show that the proposed method outperforms existing state-of-the-art methods in applicability, effectiveness, and accuracy. We believe this work to be the first attempt to classify ACAs into open, appositional, or synechial types grading using AS-OCT sequences.

Angle-closure glaucoma Anterior chamber angles AS-OCT

其他

英语

EI

20204309372617

Classification (of information) ; Medical computing ; Ophthalmology ; Medical imaging ; Optical tomography ; Computer aided diagnosis

Biomedical Engineering:461.1 ; Medicine and Pharmacology:461.6 ; Information Theory and Signal Processing:716.1 ; Computer Applications:723.5 ; Optical Devices and Systems:741.3 ; Imaging Techniques:746 ; Information Sources and Analysis:903.1

2-s2.0-85092706870

Scopus

1.Cixi Institute of Biomedical Engineering,Ningbo Institute of Materials Technology and Engineering,Chinese Academy of Sciences,Ningbo,China
2.Inception Institute of Artificial Intelligence,Abu Dhabi,United Arab Emirates
3.Department of Computer Science and Engineering,Southern University of Science and Technology,Shenzhen,China
4.State Key Laboratory of Ophthalmology,Zhongshan Ophthalmic Center,Sun Yat-sen University,Guangzhou,China
5.Glaucoma Artificial Intelligence Diagnosis and Imaging Analysis Joint Research Lab,Guangzhou and Ningbo,China

Hao，Huaying,Fu，Huazhu,Xu，Yanwu,et al. Open-Appositional-Synechial Anterior Chamber Angle Classification in AS-OCT Sequences[C],2020:715-724.