Generation of augmented capillary network optical coherence tomography image data of human skin for deep learning and capillary segmentation
Journal
Diagnostics
Journal Volume
11
Journal Issue
4
Date Issued
2021
Author(s)
Abstract
The segmentation of capillaries in human skin in full-field optical coherence tomography (FF-OCT) images plays a vital role in clinical applications. Recent advances in deep learning techniques have demonstrated a state-of-the-art level of accuracy for the task of automatic medical image segmentation. However, a gigantic amount of annotated data is required for the successful training of deep learning models, which demands a great deal of effort and is costly. To overcome this fundamental problem, an automatic simulation algorithm to generate OCT-like skin image data with augmented capillary networks (ACNs) in a three-dimensional volume (which we called the ACN data) is presented. This algorithm simultaneously acquires augmented FF-OCT and corresponding ground truth images of capillary structures, in which potential functions are introduced to conduct the capillary pathways, and the two-dimensional Gaussian function is utilized to mimic the brightness reflected by capillary blood flow seen in real OCT data. To assess the quality of the ACN data, a U-Net deep learning model was trained by the ACN data and then tested on real in vivo FF-OCT human skin images for capillary segmentation. With properly designed data binarization for predicted image frames, the testing result of real FF-OCT data with respect to the ground truth achieved high scores in performance metrics. This demonstrates that the proposed algorithm is capable of generating ACN data that can imitate real FF-OCT skin images of capillary networks for use in research and deep learning, and that the model for capillary segmentation could be of wide benefit in clinical and biomedical applications. ? 2021 by the authors. Licensee MDPI, Basel, Switzerland.
Subjects
Augmented dataset generation
Deep learning
Full-field optical coherence tomography
Image binarization
Skin capillary segmentation
U-Net
algorithm
animal experiment
animal model
article
brightness
capillary flow
controlled study
deep learning
human
in vivo study
nonhuman
optical coherence tomography
performance indicator
simulation
skin capillary
Type
journal article