A Hand-held Optical Coherence Tomography Angiography Scanner based on
Angiography Reconstruction Transformer Networks
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-second 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.