https://scholars.lib.ntu.edu.tw/handle/123456789/339008
Title: | Delineation of an oral cancer lesion with swept-source optical coherence tomography | Authors: | Tsai, M.-T. Lee, H.-C. Lu, C.-W. Wang, Y.-M. Lee, C.-K. Yang, C.C. Chiang, C.-P. CHUN-PIN CHIANG CHIH-CHUNG YANG |
Issue Date: | 2008 | Journal Volume: | 13 | Journal Issue: | 4 | Source: | Journal of Biomedical Optics | Abstract: | We demonstrate the ex vivo imaging of an oral cancerous sample with a swept-source optical coherence tomography (SS-OCT) system. With the axial resolution of 8μm in free space and system sensitivity of 108dB, we can well distinguish the normal and abnormal tissue portions in a sample. In particular, we analyze the lateral variation of A-scan profiles to show two parameters of SS-OCT signal for delineating an oral cancer lesion. One of the parameters is the decay constant in the exponential fitting of the SS-OCT signal intensity along depth. This decay constant decreases as the A-scan point moves laterally across the margin of a lesion. The other parameter is the standard deviation of the SS-OCT signal intensity fluctuation in an A-scan. This parameter increases significantly when the A-scan point is moved across the transition region between the normal and abnormal portions. Such parameters are useful for determining the margins of oral cancer. ? 2008 Society of Photo-Optical Instrumentation Engineers. |
URI: | http://www.scopus.com/inward/record.url?eid=2-s2.0-58149376555&partnerID=MN8TOARS http://scholars.lib.ntu.edu.tw/handle/123456789/339008 |
DOI: | 10.1117/1.2960632 | SDG/Keyword: | Abnormal tissues; Axial resolutions; biomedical optics; Coherent optical systems; Decay constants; Ex vivo imaging; Exponential fitting; Free space; Lateral variations; Oral cancer; Point moves; Signal intensities; Standard deviation; Swept source; System sensitivity; Transition regions; Two parameter; Optical systems; Tissue; Tomography; Diseases; algorithm; article; artificial intelligence; automated pattern recognition; computer assisted diagnosis; human; image enhancement; instrumentation; methodology; mouth tumor; optical coherence tomography; pathology; reproducibility; sensitivity and specificity; Algorithms; Artificial Intelligence; Humans; Image Enhancement; Image Interpretation, Computer-Assisted; Mouth Neoplasms; Pattern Recognition, Automated; Reproducibility of Results; Sensitivity and Specificity; Tomography, Optical Coherence [SDGs]SDG3 |
Appears in Collections: | 電機工程學系 |
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