Literature DB >> 30800529

Quality improvement of OCT angiograms with elliptical directional filtering.

Michał Chlebiej1,2, Iwona Gorczynska2, Andrzej Rutkowski1,2, Jakub Kluczewski1,2, Tomasz Grzona1,2, Ewelina Pijewska3, Bartosz L Sikorski4,5, Anna Szkulmowska2, Maciej Szkulmowski3.   

Abstract

We present a method of OCT angiography (OCTA) data filtering for noise suppression and improved visualization of the retinal vascular networks in en face projection images. In our approach, we use a set of filters applied in three orthogonal axes in the three-dimensional (3-D) data sets. Minimization of artifacts generated in B-scan-wise data processing is accomplished by filtering the cross-sections along the slow scanning axis. A-scans are de-noised by axial filtering. The core of the method is the application of directional filtering to the C-scans, i.e. one-pixel thick sections of the 3-D data set, perpendicular to the direction of the scanning OCT beam. The method uses a concept of structuring, directional kernels of shapes matching the geometry of the image features. We use rotating ellipses to find the most likely local orientation of the vessels and use the best matching ellipses for median filtering of the C-scans. We demonstrate our approach in the imaging of a normal human eye with laboratory-grade spectral-domain OCT setup. The "field performance" is demonstrated in imaging of diabetic retinopathy cases with a commercial OCT device. The absolute complex differences method is used for the generation of OCTA images from the data collected in the most noise-wise unfavorable OCTA scanning regime-two frame scanning.

Entities:  

Year:  2019        PMID: 30800529      PMCID: PMC6377873          DOI: 10.1364/BOE.10.001013

Source DB:  PubMed          Journal:  Biomed Opt Express        ISSN: 2156-7085            Impact factor:   3.732


  6 in total

1.  Reconstruction of high-resolution 6×6-mm OCT angiograms using deep learning.

Authors:  Min Gao; Yukun Guo; Tristan T Hormel; Jiande Sun; Thomas S Hwang; Yali Jia
Journal:  Biomed Opt Express       Date:  2020-06-08       Impact factor: 3.732

2.  Simultaneous directional full-field OCT using path-length and carrier multiplexing.

Authors:  Denise Valente; Kari V Vienola; Robert J Zawadzki; Ravi S Jonnal
Journal:  Opt Express       Date:  2021-09-27       Impact factor: 3.833

Review 3.  Artificial intelligence in OCT angiography.

Authors:  Tristan T Hormel; Thomas S Hwang; Steven T Bailey; David J Wilson; David Huang; Yali Jia
Journal:  Prog Retin Eye Res       Date:  2021-03-22       Impact factor: 21.198

Review 4.  Past, present and future role of retinal imaging in neurodegenerative disease.

Authors:  Amir H Kashani; Samuel Asanad; Jane W Chan; Maxwell B Singer; Jiong Zhang; Mona Sharifi; Maziyar M Khansari; Farzan Abdolahi; Yonggang Shi; Alessandro Biffi; Helena Chui; John M Ringman
Journal:  Prog Retin Eye Res       Date:  2021-01-15       Impact factor: 19.704

5.  An Open-Source Deep Learning Network for Reconstruction of High-Resolution OCT Angiograms of Retinal Intermediate and Deep Capillary Plexuses.

Authors:  Min Gao; Tristan T Hormel; Jie Wang; Yukun Guo; Steven T Bailey; Thomas S Hwang; Yali Jia
Journal:  Transl Vis Sci Technol       Date:  2021-11-01       Impact factor: 3.283

6.  Intrasession repeatability and intersession reproducibility of peripapillary OCTA vessel parameters in non-glaucomatous and glaucomatous eyes.

Authors:  Jae Chang Lee; Dominic J Grisafe; Bruce Burkemper; Brenda R Chang; Xiao Zhou; Zhongdi Chu; Ali Fard; Mary Durbin; Brandon J Wong; Brian J Song; Benjamin Y Xu; Ruikang Wang; Grace M Richter
Journal:  Br J Ophthalmol       Date:  2020-09-11       Impact factor: 4.638

  6 in total

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