Compressed sensing-enabled phase-sensitive swept-source optical coherence tomography

Ling, Yuye; Meiniel, William; Singh‐Moon, Rajinder P.; Angelini, Elsa D.; Olivo‐Marin, Jean‐Christophe; Hendon, Christine P.

doi:10.1364/oe.27.000855

Cited by 10 publications

(4 citation statements)

References 55 publications

(74 reference statements)

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“…Under incomplete projection data, traditional reconstruction algorithms cannot meet the actual clinical requirements in terms of reconstruction speed and reconstruction accuracy. Compressed sensing theory can provide new research ideas for the reconstruction of incomplete projection data [15]. First of all, the compressed sensing theory does not require the location of information collection, and this theory does not require the amount of image information collected.…”

Section: E Optimized Compressed Sensing Ct Reconstructionmentioning

confidence: 99%

Optimized Reconstruction Algorithm-Processed CT Image in the Diagnosis of Correlation between Epicardial Fat Volume and Coronary Heart Disease

Xue

Jing

2022

Scientific Programming

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This study was to analyze the application value of a reconstruction algorithm in CT images of patients with coronary heart disease and analyze the correlation between epicardial fat volume and coronary heart disease. An optimized reconstruction algorithm was constructed based on compressed sensing theory in this study. Then, the optimized algorithm was applied to the image reconstruction of multislice spiral CT image data after testing its sensitivity, accuracy, and specificity. 60 patients with suspected angina pectoris were divided into lesion group (40 cases) and normal group (20 cases) according to whether there were coronary atherosclerotic plaques in cardiac vessels. The results showed that the sensitivity, specificity, and accuracy of the optimized reconstruction algorithm were 91.78%, 84.27%, and 95.32%, and the running time was (12.18 ± 2.49) s. The CT value of the liver and the CT ratio of the liver and spleen in the lesion group were (53.81 ± 5.91) and (3.88 ± 0.67), respectively. There was no significant difference between the two groups ( P > 0.05 ). The body mass index and epicardial fat volume in the lesion group were (31.93 ± 4.54) kg/m2 and (120.09 ± 22.01) cm3, respectively. The body mass index and fat volume in the lesion group were significantly higher than those in the normal group ( P < 0.05 ). The epicardial fat constitution increased with the increase of the number of coronary arteries involved, and there was a positive correlation between them. Among patients with different coronary atherosclerotic plaques, the epicardial fat volume in patients with mixed plaques was the largest ( P < 0.05 ). In summary, optimizing CT images under compressed a sensing reconstruction algorithm could effectively improve the diagnostic accuracy of doctors. Epicardial fat volume was positively correlated with coronary heart disease. Epicardial fat volume could be used as one of the important indexes to predict coronary heart disease.

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Section: E Optimized Compressed Sensing Ct Reconstructionmentioning

confidence: 99%

Optimized Reconstruction Algorithm-Processed CT Image in the Diagnosis of Correlation between Epicardial Fat Volume and Coronary Heart Disease

Xue

Jing

2022

Scientific Programming

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“…Hence, another issue arises due to the synchronization of the wavelength sweep and acquisition of scans, leading to timing jitters. They are responsible for multiplicative noises, which affect the phase stability 11 . This problem was addressed with the use of calibration curves, by using reference interferometric signal recorded ahead of acquisition 12 .…”

Section: Introductionmentioning

confidence: 99%

WAVE-UNET: Wavelength-based image reconstruction method using attention UNET for OCT images

Viqar,

Sahin,

Madjarova

et al. 2024

Medical Imaging 2024: Physics of Medical Imaging

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In this work, we propose to leverage a deep-learning (DL) based reconstruction framework for high quality Swept-Source Optical Coherence Tomography (SS-OCT) images, by incorporating wavelength (λ) space interferometric fringes. Generally, the SS-OCT captured fringe is linear in wavelength space and if Inverse Discrete Fourier Transform (IDFT) is applied to extract depth-resolved spectral information, the resultant images are blurred due to the broadened Point Spread Function (PSF). Thus, the recorded wavelength space fringe is to be scaled to uniform grid in wavenumber (k) space using k-linearization and calibration involving interpolations which may result in loss of information along with increased system complexity. Another challenge in OCT is the speckle noise, inherent in the low coherence interferometry-based systems. Hence, we propose a systematic design methodology WAVE-UNET to reconstruct the high-quality OCT images directly from the λ-space to reduce the complexity. The novel design paradigm surpasses the linearization procedures and uses DL to enhance the realism and quality of raw λ-space scans. This framework uses modified UNET having attention gating and residual connections, with IDFT processed λ-space fringes as the input. The method consistently outperforms the traditional OCT system by generating good-quality B-scans with highly reduced time-complexity.

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“…This under-sampling process can effectively reduce the measurement time as well as the amount of data [30]. In recent years, CS has been widely studied and applied to synthetic aperture radar (SAR) imaging, magnetic resonance imaging (MRI), OCT and so on [31][32][33][34][35][36]. In theory, CS can not only reduce the amount of data but also denoise since the small coefficients are suppressed in the process of reconstruction [37,38].…”

Section: Introductionmentioning

confidence: 99%

Compressive‐sensing swept‐source optical coherence tomography angiography with reduced noise

Wang

Chen

Zhu

et al. 2022

Journal of Biophotonics

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Optical coherence tomography angiography (OCTA), as a functional extension of optical coherence tomography (OCT), has exhibited a great potential to aid in clinical diagnostics. Currently, OCTA still suffers from motion artifact and noise. Therefore, in this article, we propose to implement compressive sensing (CS) on B‐scans to reduce motion artifact by increasing B‐scan rate. Meanwhile, a noise reduction filter is specially designed by combining CS, Gaussian filter and median filter. Specially, CS filtering is realized by averaging multiple CS repetitions on en‐face OCTA images with varied sampling functions. The method is evaluated on in vivo OCTA images of human skin. The results show that vasculature structures can be reconstructed well through CS on B‐scans with a sampling rate of 70%. Moreover, the noise can be significantly eliminated by the developed filter. This implies that our method has a good potential to expedite OCTA imaging and improve the image quality.

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Compressed sensing-enabled phase-sensitive swept-source optical coherence tomography

Cited by 10 publications

References 55 publications

Optimized Reconstruction Algorithm-Processed CT Image in the Diagnosis of Correlation between Epicardial Fat Volume and Coronary Heart Disease

Optimized Reconstruction Algorithm-Processed CT Image in the Diagnosis of Correlation between Epicardial Fat Volume and Coronary Heart Disease

WAVE-UNET: Wavelength-based image reconstruction method using attention UNET for OCT images

Compressive‐sensing swept‐source optical coherence tomography angiography with reduced noise

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