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Bian H, Wang J, Hong C, Liu L, Ji R, Cao S, Abdalla AN, Chen X. GPU-accelerated image registration algorithm in ophthalmic optical coherence tomography. BIOMEDICAL OPTICS EXPRESS 2023; 14:194-207. [PMID: 36698653 PMCID: PMC9841998 DOI: 10.1364/boe.479343] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/27/2022] [Revised: 11/28/2022] [Accepted: 11/28/2022] [Indexed: 06/17/2023]
Abstract
Limited to the power of the light source in ophthalmic optical coherence tomography (OCT), the signal-to-noise ratio (SNR) of the reconstructed images is usually lower than OCT used in other fields. As a result, improvement of the SNR is required. The traditional method is averaging several images at the same lateral position. However, the image registration average costs too much time, which limits its real-time imaging application. In response to this problem, graphics processing unit (GPU)-side kernel functions are applied to accelerate the reconstruction of the OCT signals in this paper. The SNR of the images reconstructed from different numbers of A-scans and B-scans were compared. The results demonstrated that: 1) There is no need to realize the axial registration with every A-scan. The number of the A-scans used to realize axial registration is suitable to set as ∼25, when the A-line speed was set as ∼12.5kHz. 2) On the basis of ensuring the quality of the reconstructed images, the GPU can achieve 43× speedup compared with CPU.
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Affiliation(s)
- Haiyi Bian
- Faculty of Electronic Information Engineering, Huaiyin Institute of Technology, Huai’an, Jiangsu, 223003, China
| | - Jingtao Wang
- School of Electronic and Information Engineering, Soochow University, 215006, Suzhou, China
| | - Chengjian Hong
- School of Electronic and Information Engineering, Soochow University, 215006, Suzhou, China
| | - Lei Liu
- Faculty of Electronic Information Engineering, Huaiyin Institute of Technology, Huai’an, Jiangsu, 223003, China
| | - Rendong Ji
- Faculty of Electronic Information Engineering, Huaiyin Institute of Technology, Huai’an, Jiangsu, 223003, China
| | - Suqun Cao
- Faculty of Electronic Information Engineering, Huaiyin Institute of Technology, Huai’an, Jiangsu, 223003, China
| | - Ahmed N. Abdalla
- Faculty of Electronic Information Engineering, Huaiyin Institute of Technology, Huai’an, Jiangsu, 223003, China
| | - Xinjian Chen
- Faculty of Electronic Information Engineering, Huaiyin Institute of Technology, Huai’an, Jiangsu, 223003, China
- School of Electronic and Information Engineering, Soochow University, 215006, Suzhou, China
- State Key Laboratory of Radiation Medicine and Protection, Soochow University, 215123, Suzhou, China
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Fang Z, Zhang M. E-Health Ultrasonic Diagnostic Monitoring for Analysis of Cardiac Insufficiency and Neuronal Regulation in Patients with Sepsis in Emergency Department under Image Reconstruction Algorithm. COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE 2022; 2022:9415694. [PMID: 35035528 PMCID: PMC8758304 DOI: 10.1155/2022/9415694] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/14/2021] [Revised: 11/28/2021] [Accepted: 12/08/2021] [Indexed: 12/28/2022]
Abstract
An anisotropic diffusion filtering- (ADF-) ultrasound (ADF-U) for ultrasound reconstruction was constructed based on the ADF to explore the diagnostic application of ultrasound imaging based on electronic health (E-health) for cardiac insufficiency and neuronal regulation in patients with sepsis. The 144 patients with sepsis were divided into an experimental group (78 patients with cardiac insufficiency) and a control group (66 patients with normal cardiac function), and another 58 healthy people were included in a blank control. The ultrasound examination was performed on all patients. In addition, new ultrasound image reconstruction and diagnosis were performed based on ADF and E-health, and its reconstruction effects were compared with those of the Bilateral Filter-ultrasonic (BFU) algorithm and the Wavelet Threshold-ultrasonic (WTU) algorithm. The left and right ventricular parameters and neuropeptide levels were detected and recorded. The results show that the running time, average gradient (AG), and peak signal-to-noise ratio (SNR) (PSNR) of the ADF-U algorithm were greater than those of the Bilateral Filter-ultrasonic (BFU) and Wavelet Threshold-ultrasonic (WTU), but the mean square error (MSE) was opposite (P < 0.05); the left ventricular end-systolic volume (LVESV) and the vertical distance between the mitral valve E-point to septal separation (EPSS) in the experimental group were higher than those in the control and blank group, while the left ventricular ejection fraction (LVEF), stroke volume (SV), cardiac output (CO), and left ventricular fractional shortening (LVFS) were opposite (P < 0.05); the systolic peak velocity of right ventricular free wall tricuspid annulus (Sm) and pulmonary valve blood velocity (PVBV) in the experimental group were lower than those of the control group and blank group (P < 0.05); the messenger ribonucleic acid (mRNA) of Proopiomelanocortin (POMC) and Cocain and amphetamine-regulated transcript (CART) was higher than the mRNA IN control group and blank group (P < 0.05). In short, the ADF-U algorithm proposed in this study improved the resolution, SNR, and reconstruction efficiency of E-health ultrasound images and provided an effective reference value for the diagnosis of cardiac insufficiency and neuronal adjustment analysis in patients with sepsis in the emergency department.
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Affiliation(s)
- Zhonghua Fang
- Department of Emergency Medicine, Jiande First People's Hospital, Jiande, Hangzhou 311600, China
| | - Mao Zhang
- Department of Emergency Medicine, The Second Affiliated Hospital of Medical College of Zhejiang University, Hangzhou 310006, China
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