Sheng-Lung Huang, Graduate Institute of Photonics and Optoelectronics, National Taiwan University,
Department of Electrical Engineering, National Taiwan University, All Vista Healthcare Center, National Taiwan University, will lecture on "Deep learning empowered optical coherence tomography."
Optical coherence tomography (OCT) has now become a standard of care, impacting the treatment of millions of people every year. There is tremendous clinical and preclinical OCT progress in diagnosing cancers and disorders in ophthalmology, cardiology, neurology, dermatology, gastroenterology, etc. In this talk, deep learning algorithms for detecting/segmenting the crucial cell/tissue/lesion features, such as nuclei, the dermal-epidermal junction of human skin, and tumor boundaries, will be addressed. The performance can be explained by visualizing the neural network's feature activations in response to the cell-like structure of human tissues. Histopathological stained images are considered the gold standard for clinical cancer diagnosis. However, the staining processing time is long, especially when surgery progresses. There is an unmet need to build an image translation model to convert the grey-level OCT images to mimic the stained images. Both semi-supervised and unsupervised approaches toward virtue histopathology will be addressed. Leveraging the ever-escalating techniques in applying deep learning algorithms to medical image analysis could accelerate the acceptance of deep learning applications among clinicians and patients.
