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30 October 2017 Combining deep learning and coherent anti-Stokes Raman scattering imaging for automated differential diagnosis of lung cancer
Sheng Weng, Xiaoyun Xu, Jiasong Li, Stephen T. C. Wong
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Journal of Biomedical Optics, Vol. 22, Issue 10, 106017 (October 2017). https://doi.org/10.1117/1.JBO.22.10.106017
Abstract
Lung cancer is the most prevalent type of cancer and the leading cause of cancer-related deaths worldwide. Coherent anti-Stokes Raman scattering (CARS) is capable of providing cellular-level images and resolving pathologically related features on human lung tissues. However, conventional means of analyzing CARS images requires extensive image processing, feature engineering, and human intervention. This study demonstrates the feasibility of applying a deep learning algorithm to automatically differentiate normal and cancerous lung tissue images acquired by CARS. We leverage the features learned by pretrained deep neural networks and retrain the model using CARS images as the input. We achieve 89.2% accuracy in classifying normal, small-cell carcinoma, adenocarcinoma, and squamous cell carcinoma lung images. This computational method is a step toward on-the-spot diagnosis of lung cancer and can be further strengthened by the efforts aimed at miniaturizing the CARS technique for fiber-based microendoscopic imaging.
CC BY: © The Authors. Published by SPIE under a Creative Commons Attribution 4.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.
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Sheng Weng, Xiaoyun Xu, Jiasong Li, and Stephen T. C. Wong "Combining deep learning and coherent anti-Stokes Raman scattering imaging for automated differential diagnosis of lung cancer," Journal of Biomedical Optics 22(10), 106017 (30 October 2017). https://doi.org/10.1117/1.JBO.22.10.106017
Received: 7 July 2017; Accepted: 4 October 2017; Published: 30 October 2017
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Cited by 76 scholarly publications and 2 patents.
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KEYWORDS
Lung
Lung cancer
Tissues
Tumor growth modeling
CARS tomography
Data modeling
Image classification
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