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Proceedings Paper

Rapid label-free computational staining for cancer histopathology (Conference Presentation)
Author(s): Bo Gao; Xin Xie; Ashraf Talukder; Run Li; Min Xu

Paper 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.

Paper Details

Date Published: 9 March 2020
Proc. SPIE 11234, Optical Biopsy XVIII: Toward Real-Time Spectroscopic Imaging and Diagnosis, 1123417 (9 March 2020); doi: 10.1117/12.2548756
Show Author Affiliations
Bo Gao, Hunter College (United States)
Xin Xie, Fairfield Univ. (United States)
Ashraf Talukder, Hunter College (United States)
Run Li, Fairfield Univ. (United States)
Min Xu, Hunter College (United States)

Published in SPIE Proceedings Vol. 11234:
Optical Biopsy XVIII: Toward Real-Time Spectroscopic Imaging and Diagnosis
Robert R. Alfano; Stavros G. Demos; Angela B. Seddon, Editor(s)

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