FIGURE 1 from Accelerating Cancer Histopathology Workflows with Chemical Imaging and Machine Learning
Year: 2023
Type: other
Abstract: Overview of the experiment and results presented in this article. A, Comparison of the presented SRS histopathologic workflow with standard workflows (POC, point of care). B (i)–(v), results for benign tissue. (i) Brightfield image of unstained tissue; (ii) brightfield image of H&E-stained adjacent section; (iii) SRS image at 2933/cm−1 showing overall tissue composition; (iv) SRS image at 2847/cm−1 highlighting epithelium; and (v) SRS image at 2979/cm−1 highlighting stroma and blood vessels. B (vi)–(x), results for low-grade cancer (GS = 3). (vi) Brightfield image of unstained tissue; (vii) brightfield image of H&E-stained adjacent section; (viii) SRS image at 2933/cm−1, (ix) SRS image at 2847/cm−1, and (x) SRS image at 2979/cm−1. B (xi)–(xv), Results for high-grade cancer (GS = 4). B, (xi) Brightfield image of unstained tissue; (xii) brightfield image of H&E-stained adjacent section; (xiii) SRS image at 2933/cm−1; (xiv) SRS image at 2847/cm−1; and (xv) SRS image at 2979/cm−1. C, Two-color SRS images (as described in the text) of a zoomed in region of a gland. D, Average max normalized SRS spectra of stroma, nuclei, epithelium, and LDs (color coded). Inset, spectral heterogeneity of epithelial cells shown in C.
Language: English
Subfield: Biophysics
Domain: Life Sciences
Open Access status: gold
OpenAlex ID: W4386828801