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Review
. 2018 Nov 14:9:38.
doi: 10.4103/jpi.jpi_53_18. eCollection 2018.

Artificial Intelligence and Digital Pathology: Challenges and Opportunities

Hamid Reza Tizhoosh  1   2 , Liron Pantanowitz  3
Affiliations
Review

Artificial Intelligence and Digital Pathology: Challenges and Opportunities

Hamid Reza Tizhoosh et al. J Pathol Inform. .

Abstract

In light of the recent success of artificial intelligence (AI) in computer vision applications, many researchers and physicians expect that AI would be able to assist in many tasks in digital pathology. Although opportunities are both manifest and tangible, there are clearly many challenges that need to be overcome in order to exploit the AI potentials in computational pathology. In this paper, we strive to provide a realistic account of all challenges and opportunities of adopting AI algorithms in digital pathology from both engineering and pathology perspectives.

Keywords: Artificial intelligence; deep learning; digital pathology.

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Conflict of interest statement

There are no conflicts of interest.

Figures

Figure 1
Figure 1
Patching is generally used to represent large scans. For instance, every patch could be a 1000 pixel ×1000 pixel image at ×20
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