Virtual Gram staining of label-free bacteria using dark-field microscopy and deep learning.

ABSTRACT: Gram staining has been a frequently used staining protocol in microbiology. It is vulnerable to staining artifacts due to, e.g., operator errors and chemical variations. Here, we introduce virtual Gram staining of label-free bacteria using a trained neural network that digitally transforms dark-field images of unstained bacteria into their Gram-stained equivalents matching bright-field image contrast. After a one-time training, the virtual Gram staining model processes an axial stack of dark-field microscopy images of label-free bacteria (never seen before) to rapidly generate Gram staining, bypassing several chemical steps involved in the conventional staining process. We demonstrated the success of virtual Gram staining on label-free bacteria samples containing Escherichia coli an

SUBMITTER: Isıl C 

PROVIDER: S-EPMC11803577 | biostudies-literature | 2025 Jan

REPOSITORIES: biostudies-literature