Browsing by Author "Chan C.-C"
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Publication Detecting mouse squamous cell carcinoma from submicron full-field optical coherence tomography images by deep learning(2021) ;Ho C.-J ;Calderon-Delgado M ;Chan C.-C ;Lin M.-Y ;Tjiu J.-W ;Huang S.-L; ; Ho C.-J;Calderon-Delgado M;Chan C.-C;Lin M.-Y;Tjiu J.-W;Huang S.-L;Chen H.H.The standard medical practice for cancer diagnosis requires histopathology, which is an invasive and time-consuming procedure. Optical coherence tomography (OCT) is an alternative that is relatively fast, noninvasive, and able to capture three-dimensional structures of epithelial tissue. Unlike most previous OCT systems, which cannot capture crucial cellular-level information for squamous cell carcinoma (SCC) diagnosis, the full-field OCT (FF-OCT) technology used in this paper is able to produce images at sub-micron resolution and thereby facilitates the development of a deep learning algorithm for SCC detection. Experimental results show that the SCC detection algorithm can achieve a classification accuracy of 80% for mouse skin. Using the sub-micron FF-OCT imaging system, the proposed SCC detection algorithm has the potential for in-vivo applications. ? 2020 Wiley-VCH GmbHjournal article1Scopus© Citations 19 - Some of the metrics are blocked by yourconsent settings
Publication Segmentation based OCT Image to H&E-like image conversion(2020) ;Tsai S.-T ;Chan C.-C ;Chen H.H ;Tjiu J.-W; ; Tsai S.-T;Chan C.-C;Chen H.H;Tjiu J.-W;Huang S.-L.Weakly supervised conversion from in vivo OCT images on human skin to H&E-stain-like images is developed. The dermis-epidermis junction, stratum corneum boundary, and nuclei distribution match well between the OCT and converted H&E-stain-liked images. ? 2020 The Author(s)conference paper1Scopus© Citations 1