scholarly journals Non-Contact Measurement of Small-Module Gears Using Optical Coherence Tomography

2018 ◽  
Vol 8 (12) ◽  
pp. 2490 ◽  
Author(s):  
Manting Luo ◽  
Shuncong Zhong
Keyword(s):  
Optical Coherence Tomography ◽  
Influencing Factors ◽  
Transmission Conditions ◽  
Small Scale ◽  
Depth Information ◽  
Optical Coherence ◽  
Microscopic Imaging ◽  
Pressure Angle ◽  
Tooth Number ◽  
Visual Imaging

Due to the small size and harsh transmission conditions of small-module gears, it is very difficult to measure gear characteristics with a modulus smaller than 1 mm. We proposed an optical coherence tomography (OCT) method for measuring small-module gears. Testing of a 30-tooth copper gear with a small modulus of 0.5 mm was carried out for the measurement of its modulus, tooth parameter, tooth number, pressure angle, modification coefficient, and tooth thickness by using OCT. In addition, the influencing factors on the measurement were discussed. The whole teeth profile of a 0.2 mm modulus gear was imaged by processing of the data collected from different clamping angles. Compared with the visual imaging without depth information and small-scale microscopic imaging, the OCT method has shown its superiority, and it has potential in the application of the measurement of micro gears with a small modulus of less than 0.2 mm.

scholarly journals A Novel Automatic Method to Estimate Visual Acuity and Analyze the Retinal Vasculature in Retinal Vein Occlusion Using Swept Source Optical Coherence Tomography Angiography

2019 ◽  
Vol 8 (10) ◽  
pp. 1515 ◽  
Author(s):  
Díez-Sotelo ◽  
Díaz ◽  
Abraldes ◽  
Gómez-Ulla ◽  
Penedo ◽  
...  
Keyword(s):  
Optical Coherence Tomography ◽  
Visual Acuity ◽  
Optical Coherence Tomography Angiography ◽  
Foveal Avascular Zone ◽  
Depth Information ◽  
Vascular Density ◽  
Optical Coherence ◽  
Automatic Method ◽  
Correlation Index ◽  
Swept Source

The assessment of vascular biomarkers and their correlation with visual acuity is one of the most important issues in the diagnosis and follow-up of retinal vein occlusions (RVOs). The high workloads of clinical practice make it necessary to have a fast, objective, and automatic method to analyze image features and correlate them with visual function. The aim of this study is to propose a fully automatic system which is capable of estimating visual acuity (VA) in RVO eyes, based only on information obtained from macular optical coherence tomography angiography (OCTA) images. We also propose an automatic methodology to rapidly measure the foveal avascular zone (FAZ) area and the vascular density (VD) in the superficial and deep capillary plexuses in swept-source OCTA images centered on the fovea. The proposed methodology is validated using a representative sample of 133 visits of 50 RVO patients. Our methodology estimates VA with very high precision and is even more accurate when we integrate depth information, providing a high correlation index of 0.869 with the real VA, which outperforms the correlation index of 0.855 obtained when estimating VA from the data obtained by the semiautomatic existing method. In conclusion, the proposed method is the first computational system able to estimate VA in RVO, with the additional benefits of being automatic, less time-consuming, objective and more accurate. Furthermore, the proposed method is able to integrate depth information, a feature which is lacking in the existing method.

In vivo microscopic imaging for diagnosis of fibrotic interstitial lung disease using endobronchial optical coherence tomography

2021 ◽  
Author(s):  
Sreyankar Nandy ◽  
Rebecca A. Israel ◽  
Ashok Muniappan ◽  
Angela Shih ◽  
Benjamin W. Roop ◽  
...  
Keyword(s):  
Optical Coherence Tomography ◽  
Interstitial Lung Disease ◽  
Lung Disease ◽  
Optical Coherence ◽  
Microscopic Imaging

Small scale boiling experiments using two-dimensional imaging with high-speed camera and optical coherence tomography

Kerntechnik ◽  
2013 ◽  
Vol 78 (1) ◽  
pp. 54-56
Author(s):  
C. Schneider ◽  
L. Kirsten ◽  
S. Meissner ◽  
A. Hurtado ◽  
E. Koch ◽  
...  
Keyword(s):  
Optical Coherence Tomography ◽  
High Speed ◽  
Small Scale ◽  
High Speed Camera ◽  
Optical Coherence ◽  
Two Dimensional

scholarly journals Akinetic Swept-Source Master–Slave-Enhanced Optical Coherence Tomography

Photonics ◽  
2021 ◽  
Vol 8 (5) ◽  
pp. 141
Author(s):  
Manuel J. Marques ◽  
Ramona Cernat ◽  
Jason Ensher ◽  
Adrian Bradu ◽  
Adrian Podoleanu
Keyword(s):  
Optical Coherence Tomography ◽  
Sampling Rate ◽  
Calibration Procedure ◽  
Depth Information ◽  
Optical Coherence ◽  
Time Intervals ◽  
Swept Source ◽  
High Sampling Rate ◽  
First Time ◽  
Down Conversion

This paper presents a different approach for processing the signal from interferometers driven by swept sources that exhibit non-linear tuning during stable time intervals. Such sources are, for example, those commercialised by Insight, which are electrically tunable and akinetic. These Insight sources use a calibration procedure to skip frequencies already included in a spectral sweep, i.e., a process of “clearing the spectrum”. For the first time, the suitability of the Master–Slave (MS) procedure is evaluated as an alternative to the conventional calibration procedure for such sources. Here, the MS process is applied to the intact, raw interferogram spectrum delivered by an optical coherence tomography (OCT) system. Two modalities are investigated to implement the MS processing, based on (i) digital generation of the Master signals using the OCT interferometer and (ii) down-conversion using a second interferometer driven by the same swept source. The latter allows near-coherence-limited operation at a large axial range (>80 mm), without the need for a high sampling rate digitiser card to cope with the large frequency spectrum generated, which can exceed several GHz. In both cases, the depth information is recovered with some limitations as described in the text.

scholarly journals Observation of the early blood vessels of cutaneous malignant melanoma using Swept Source Optical Coherence Tomography Angiography (SS-OCTA)

2019 ◽  
Vol 12 (04) ◽  
pp. 1942005 ◽  
Author(s):  
Jingxuan Liu ◽  
Jinyu Fan ◽  
Quan Wang ◽  
Wen He ◽  
Caihua Dong ◽  
...  
Keyword(s):  
Optical Coherence Tomography ◽  
Blood Vessels ◽  
Optical Coherence Tomography Angiography ◽  
Rapid Development ◽  
Small Scale ◽  
Control Group ◽  
Optical Coherence ◽  
Swept Source ◽  
Early Tumor

Melanoma, characterized by high mortality, rapid development and accompanied with angiogenesis is the most typical malignant tumor in skin cancer. Hence, the detection of blood vessels is of much significance. The early vascular network has small scale. If we remove the tumor early and biopsy it, it will increase the spread of the cancer cells and infection and bleeding. In this case, we presented a new angiography method. A high-resolution OCT system for noninvasive angiographic imaging of early skin melanoma — Swept Source Optical Coherence Tomography Angiography (SS-OCTA) is proposed. With a high lateral resolution of 10[Formula: see text][Formula: see text]m in vivo tomographic angiography, SS-OCTA is used to image and identify the morphology of the early tumor blood vessels. In addition, a control group experiment is conducted to observe the growth of melanoma in the process of rupture, malformation of micro-vessels. The results of the analysis and statistical test ([Formula: see text]) are statistically significant.

Measurement of the Optic Disc Vertical Tilt Angle With Spectral-Domain Optical Coherence Tomography and Influencing Factors

2013 ◽  
Vol 156 (4) ◽  
pp. 737-744.e1 ◽  
Author(s):  
Hamid Hosseini ◽  
Nariman Nassiri ◽  
Parham Azarbod ◽  
JoAnn Giaconi ◽  
Tom Chou ◽  
...  
Keyword(s):  
Optical Coherence Tomography ◽  
Optic Disc ◽  
Influencing Factors ◽  
Tilt Angle ◽  
Spectral Domain ◽  
Optical Coherence

scholarly journals Optimized Deep Convolutional Neural Networks for Identification of Macular Diseases from Optical Coherence Tomography Images

Algorithms ◽  
2019 ◽  
Vol 12 (3) ◽  
pp. 51 ◽  
Author(s):  
Qingge Ji ◽  
Jie Huang ◽  
Wenjie He ◽  
Yankui Sun
Keyword(s):  
Neural Networks ◽  
Optical Coherence Tomography ◽  
Large Scale ◽  
Deep Neural Networks ◽  
Natural Images ◽  
Small Scale ◽  
Optical Coherence ◽  
Deep Convolutional Neural Networks ◽  
Macular Diseases ◽  
High Level

Finetuning pre-trained deep neural networks (DNN) delicately designed for large-scale natural images may not be suitable for medical images due to the intrinsic difference between the datasets. We propose a strategy to modify DNNs, which improves their performance on retinal optical coherence tomography (OCT) images. Deep features of pre-trained DNN are high-level features of natural images. These features harm the training of transfer learning. Our strategy is to remove some deep convolutional layers of the state-of-the-art pre-trained networks: GoogLeNet, ResNet and DenseNet. We try to find the optimized deep neural networks on small-scale and large-scale OCT datasets, respectively, in our experiments. Results show that optimized deep neural networks not only reduce computational burden, but also improve classification accuracy.

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