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9 March 2020 Rapid label-free computational staining for cancer histopathology (Conference Presentation)
Bo Gao, Xin Xie, Ashraf Talukder, Run Li, Min Xu
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Proceedings Volume 11234, Optical Biopsy XVIII: Toward Real-Time Spectroscopic Imaging and Diagnosis; 1123417 (2020) https://doi.org/10.1117/12.2548756
Event: SPIE BiOS, 2020, San Francisco, California, United States
Abstract
Cancer diagnosis is critical in patient care yet it currently depends on time-consuming histopathology processes. We report a new method of computational staining in place of the traditional hematoxylin and eosin (H&E) staining. This method is derived from chemometric fluorescence microscopic imaging of unstained specimens. The computationally stained images visually differentiate specific cell properties, such as cellular metabolism of NADH, FAD, as well as protein production of tryptophan and elastin. Different color encoding strategies will be discussed including emulating the traditional H&E staining and optimizing for the contrast. The preliminary study on lung tissues suggests the proposed approach is a promising rapid histopathology alternative.
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Bo Gao, Xin Xie, Ashraf Talukder, Run Li, and Min Xu "Rapid label-free computational staining for cancer histopathology (Conference Presentation)", Proc. SPIE 11234, Optical Biopsy XVIII: Toward Real-Time Spectroscopic Imaging and Diagnosis, 1123417 (9 March 2020); https://doi.org/10.1117/12.2548756
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KEYWORDS
Cancer
Chemometrics
Luminescence
Chromophores
Computer programming
Lung cancer
Tissues
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