Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Deep learning-based virtual histology staining using auto-fluorescence
  of label-free tissue   Histological analysis of tissue samples is one of the most widely used
methods for disease diagnosis. After taking a sample from a patient, it goes
through a lengthy and laborious preparation, which stains the tissue to
visualize different histological features under a microscope. Here, we
demonstrate a label-free approach to create a virtually-stained microscopic
image using a single wide-field auto-fluorescence image of an unlabeled tissue
sample, bypassing the standard histochemical staining process, saving time and
cost. This method is based on deep learning, and uses a convolutional neural
network trained using a generative adversarial network model to transform an
auto-fluorescence image of an unlabeled tissue section into an image that is
equivalent to the bright-field image of the stained-version of the same sample.
We validated this method by successfully creating virtually-stained microscopic
images of human tissue samples, including sections of salivary gland, thyroid,
kidney, liver and lung tissue, also covering three different stains. This
label-free virtual-staining method eliminates cumbersome and costly
histochemical staining procedures, and would significantly simplify tissue
preparation in pathology and histology fields.

9
The categories of this paper are: nlin
7
The categories of this paper are: hep-th
6
The categories of this paper are: astro-ph
21
The categories of this paper are: adap-org
29
The categories of this paper are: funct-an
15
The categories of this paper are: nucl-ex
14
The categories of this paper are: math-ph
18
The categories of this paper are: econ
26
The categories of this paper are: bayes-an
25
The categories of this paper are: patt-sol
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The categories of this paper are: hep-lat
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The categories of this paper are: quant-ph
27
The categories of this paper are: comp-gas
30
The categories of this paper are: q-alg
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The categories of this paper are: stat
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The categories of this paper are: q-fin