A Hand-held Optical Coherence Tomography Angiography Scanner based on Angiography Reconstruction Transformer Networks.
Jinpeng LiaoShufan YangTianyu ZhangChunhui LiZhihong HuangPublished in: Journal of biophotonics (2023)
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. This article is protected by copyright. All rights reserved.
Keyphrases
- deep learning
- computed tomography
- image quality
- high resolution
- optical coherence tomography
- hiv infected
- convolutional neural network
- artificial intelligence
- antiretroviral therapy
- soft tissue
- wound healing
- randomized controlled trial
- quantum dots
- quality improvement
- air pollution
- single molecule
- machine learning
- magnetic resonance
- fluorescent probe