Automatic Measurement Method for Corneal Thickness of Optical Coherence Tomography Images

Yang Gao; Zhongliang Li; Jianhua Zhang; Nan Nan; Xuan Wang; Xiangzhao Wang

doi:10.3788/AOS201939.0311003

Acta Optica Sinica, Volume. 39, Issue 3, 0311003(2019)

Automatic Measurement Method for Corneal Thickness of Optical Coherence Tomography Images

Yang Gao^1,2、*, Zhongliang Li^2、*, Jianhua Zhang¹, Nan Nan², Xuan Wang², and Xiangzhao Wang²

Author Affiliations

¹ School of Mechanical Engineering and Automation, Shanghai University, Shanghai 200444, China

² Laboratory of Information Optics and Opto-Electronic Technology, Shanghai Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Shanghai 201800, China

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Figures & Tables(12)

Fig. 1. Flow chart of proposed measurement method of corneal thickness

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Fig. 2. Noise and artifacts in original cornea B scan image

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Fig. 3. A-scan averaged intensity curve

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Fig. 4. Average intensity curves of adjacent rows

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Fig. 5. Effect of corneal B-scan OCT images after pre-treatment. (a) Original corneal B-scan image; (b) corneal B-scan image with adaptive median-filtering; (c) corneal B-scan image with horizontal artifact removal; (d) corneal B-scan image with suppressed central artifact

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Fig. 6. Boundary conditions. (a) Outer boundary condition; (b) hole boundary condition

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Fig. 7. Upper and lower edge fitting results of human corneal OCT B-scan image. (a) High quality original corneal B-scan image; (b) high quality edge fitting corneal B-scan image; (c) original corneal B-scan image with noise and artifacts; (d) edge fitting corneal B-scan image with noise and artifacts

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Fig. 8. Fitting effects of upper and lower edges of human corneal B-scan images obtained by different pre-processing denoising algorithms. (a) No preprocessing denoising. (b) mean filter preprocessing; (c) median filter preprocessing; (d) adaptive median filter preprocessing

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Fig. 9. Results of upper and lower edge fitting of OCT corneal images. (a) Edge detection and random sampling consistency method; (b) proposed method

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Table 1. Average thickness, central thickness and corresponding standard deviations along Y-axis of corneal images with different qualities
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Table 1. Average thickness, central thickness and corresponding standard deviations along Y-axis of corneal images with different qualities
Algorithm type T_a±σ /μm T_c±σ /μm
High quality corneal B-scan image 561.6±1.2 571.6±2.9
Corneal B-scan image with noise and artifacts 562.1±2.3 572.3±3.8

Table 2. Average thickness, central thickness and corresponding standard deviations along Y-axis after treatments with different pretreatment algorithms

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Table 2. Average thickness, central thickness and corresponding standard deviations along Y-axis after treatments with different pretreatment algorithms

Preprocessing algorithm	T_a±σ /μm	T_c±σ /μm
No preprocessing denoising	567.2±5.1	575.3±5.4
Mean filter preprocessing	563.1±4.4	573.9±4.8
Median filter preprocessing	564.6±3.8	573.2±4.5
Adaptive median filter preprocessing	562.1±2.3	572.3±3.8
Manual measurement	561.4±1.4	571.2±2.4

Table 3. Average thickness deviation, corneal center thickness deviation and corresponding standard deviations along Y-axis of corneal by different methods
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Table 3. Average thickness deviation, corneal center thickness deviation and corresponding standard deviations along Y-axis of corneal by different methods
Algorithm type Proposed algorithm (manual measurement) Random sampling consisitency (RANSC) algorithm (manual measurement)
T_a±σ /μm 1.0±0.3 2.3±1.8
T_c±σ /μm 1.2±0.6 5.2±3.9

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Yang Gao, Zhongliang Li, Jianhua Zhang, Nan Nan, Xuan Wang, Xiangzhao Wang. Automatic Measurement Method for Corneal Thickness of Optical Coherence Tomography Images[J]. Acta Optica Sinica, 2019, 39(3): 0311003

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Paper Information

Category: Imaging Systems

Received: Sep. 29, 2018

Accepted: Nov. 8, 2018

Published Online: May. 10, 2019

The Author Email:

DOI:10.3788/AOS201939.0311003

Topics

laser devices and laser physics

Lasers and Laser Optics

Laser physics

laser manufacturing

Instrumentation, Measurement and Metrology

Table 1. Average thickness, central thickness and corresponding standard deviations along Y-axis of corneal images with different qualities

Table 1. Average thickness, central thickness and corresponding standard deviations along Y-axis of corneal images with different qualities

Table 2. Average thickness, central thickness and corresponding standard deviations along Y-axis after treatments with different pretreatment algorithms

Table 2. Average thickness, central thickness and corresponding standard deviations along Y-axis after treatments with different pretreatment algorithms

Table 3. Average thickness deviation, corneal center thickness deviation and corresponding standard deviations along Y-axis of corneal by different methods

Table 3. Average thickness deviation, corneal center thickness deviation and corresponding standard deviations along Y-axis of corneal by different methods