A hand-held optical coherence tomography angiography scanner based on angiography reconstruction transformer networks

Jinpeng Liao, Shufan Yang, Tianyu Zhang, Chunhui Li (Lead / Corresponding author), Zhihong Huang

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Abstract

Optical coherence tomography angiography (OCTA) has successfully demonstrated its viability for clinical applications in dermatology. Due to the high optical scattering property of skin, extracting high-quality OCTA images from skin tissues requires at least six-repeated scans. While the motion artifacts from the patient and the free hand-held probe can lead to a low-quality OCTA image. Our deep-learning-based scan pipeline enables fast and high-quality OCTA imaging with 0.3-s data acquisition. We utilize a fast scanning protocol with a 60 μm/pixel spatial interval rate and introduce angiography-reconstruction-transformer (ART) for 4× super-resolution of low transverse resolution OCTA images. The ART outperforms state-of-the-art networks in OCTA image super-resolution and provides a lighter network size. ART can restore microvessels while reducing the processing time by 85%, and maintaining improvements in structural similarity and peak-signal-to-noise ratio. This study represents that ART can achieve fast and flexible skin OCTA imaging while maintaining image quality. (Figure presented.).

Original languageEnglish
Article numbere202300100
Number of pages17
JournalJournal of Biophotonics
Volume16
Issue number9
Early online date1 Jun 2023
DOIs
Publication statusPublished - Sept 2023

Keywords

  • deep learning
  • optical coherence tomography angiography
  • single image super-resolution

ASJC Scopus subject areas

  • General Engineering
  • General Physics and Astronomy
  • General Chemistry
  • General Biochemistry,Genetics and Molecular Biology
  • General Materials Science

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