Paper
13 September 2024 Automatic extraction of asymmetric collagen for T staging of esophageal cancer in multiphoton microscopy
Jian Xu, Chi Zhang, Shanghai Jiang, Geliang Xu, Yuanhua Wu, Deyong Kang, Jiangbo Lin, Jianxin Chen
Author Affiliations +
Proceedings Volume 13254, Fourth International Conference on Optics and Image Processing (ICOIP 2024); 132541F (2024) https://doi.org/10.1117/12.3039098
Event: Fourth International Conference on Optics and Image Processing (ICOIP 2024), 2024, Chongqing, China
Abstract
Research goal was to demonstrate whether multiphoton microscopy (MPM) can be employed for identifying T staging of esophageal cancer (EC). For comprehending T staging of EC better, the tumor infiltration depth in esophageal wall of each cancer staging was first shown. In order to automatic identification the boundaries between normal layers that without tumor infiltration, a boundary detection algorithm is proposed by extracting SHG signals which are produced by collagen molecules with asymmetric architecture in MPM images. Then, the morphological differentiation of tumor cells from main components of esophageal wall was performed. The tumor infiltration depth was decided by evaluating the position of tumor cells and the boundaries. After then, Tis, T1a, T1b, T2 and T3 staging of esophageal cancer were identified. The outcomes indicate that MPM can be applied for automatic identifying T staging of EC. Every effort was made to developed compact multiphoton microendoscope system with high speed and ultra-deep penetration depth in recent years. There was every reason to believe that clinical application of MPM in automatic identifying esophageal cancer staging will be possible in the future.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Jian Xu, Chi Zhang, Shanghai Jiang, Geliang Xu, Yuanhua Wu, Deyong Kang, Jiangbo Lin, and Jianxin Chen "Automatic extraction of asymmetric collagen for T staging of esophageal cancer in multiphoton microscopy", Proc. SPIE 13254, Fourth International Conference on Optics and Image Processing (ICOIP 2024), 132541F (13 September 2024); https://doi.org/10.1117/12.3039098
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KEYWORDS
Tumors

Cancer

Tissues

Connective tissue

Muscles

Collagen

Cancer detection

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