Calderon-Delgado, M.M.Calderon-DelgadoTjiu, J.-W.J.-W.TjiuLin, M.-Y.M.-Y.LinSHENG-LUNG HUANG2020-06-112020-06-112018https://scholars.lib.ntu.edu.tw/handle/123456789/501302Convolutional neural networks were applied to sub-micron-resolution optical coherence tomography images of the human skin for anatomical segmentation. The main layers of skin were discerned with an average 90% accuracy, which we believe to possess potential in the assessment of skin health. ? 2018 IEEE.convolutional neural networks; machine learning; medical imaging; optical coherence tomography; skin[SDGs]SDG3Convolution; Image segmentation; Learning systems; Medical imaging; Neural networks; Numerical models; Optical tomography; Skin; Convolutional neural network; High resolution; Human skin; Sub-micron resolutions; Optoelectronic devicesconference paper10.1109/NUSOD.2018.85702412-s2.0-85060030335https://www.scopus.com/inward/record.uri?eid=2-s2.0-85060030335&doi=10.1109%2fNUSOD.2018.8570241&partnerID=40&md5=960195c30b463fafc9e835d32414fbdd