دورية أكاديمية
أعرض في EDS

Windowed Eigen-Decomposition Algorithm for Motion Artifact Reduction in Optical Coherence Tomography-Based Angiography

التفاصيل البيبلوغرافية
العنوان: Windowed Eigen-Decomposition Algorithm for Motion Artifact Reduction in Optical Coherence Tomography-Based Angiography
المؤلفون: Tianyu Zhang, Kanheng Zhou, Holly R. Rocliffe, Antonella Pellicoro, Jenna L. Cash, Wendy Wang, Zhiqiong Wang, Chunhui Li, Zhihong Huang
المصدر: Applied Sciences, Vol 13, Iss 1, p 378 (2022)
بيانات النشر: MDPI AG, 2022.
سنة النشر: 2022
المجموعة: LCC:Technology
LCC:Engineering (General). Civil engineering (General)
LCC:Biology (General)
LCC:Physics
LCC:Chemistry
مصطلحات موضوعية: optical coherence tomography (OCT), optical coherence tomography-based angiography (OCTA), eigen-decomposition (ED), motion artifact, Technology, Engineering (General). Civil engineering (General), TA1-2040, Biology (General), QH301-705.5, Physics, QC1-999, Chemistry, QD1-999
الوصف: Optical coherence tomography-based angiography (OCTA) has attracted attention in clinical applications as a non-invasive and high-resolution imaging modality. Motion artifacts are the most seen artifact in OCTA. Eigen-decomposition (ED) algorithms are popular choices for OCTA reconstruction, but have limitations in the reduction of motion artifacts. The OCTA data do not meet one of the requirements of ED, which is that the data should be normally distributed. To overcome this drawback, we propose an easy-to-deploy development of ED, windowed-ED (wED). wED applies a moving window to the input data, which can contrast the blood-flow signals with significantly reduced motion artifacts. To evaluate our wED algorithm, pre-acquired dorsal wound healing data in a murine model were used. The ideal window size was optimized by fitting the data distribution with the normal distribution. Lastly, the cross-sectional and en face results were compared among several OCTA reconstruction algorithms, Speckle Variance, A-scan ED (aED), B-scan ED, and wED. wED could reduce the background noise intensity by 18% and improve PSNR by 4.6%, compared to the second best-performed algorithm, aED. This study can serve as a guide for utilizing wED to reconstruct OCTA images with an optimized window size.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 2076-3417
Relation: https://www.mdpi.com/2076-3417/13/1/378; https://doaj.org/toc/2076-3417
DOI: 10.3390/app13010378
URL الوصول: https://doaj.org/article/c23df658ba5c41bcb3b11582bb1be97b
رقم الأكسشن: edsdoj.23df658ba5c41bcb3b11582bb1be97b
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:20763417
DOI:10.3390/app13010378