Faculty, Staff and Student Publications
Language
English
Publication Date
3-26-2020
Journal
Cancers
DOI
10.3390/cancers12040797
PMID
32224980
PMCID
PMC7226574
PubMedCentral® Posted Date
March 2020
PubMedCentral® Full Text Version
Post-print
Abstract
Digital Pathology is the process of converting histology glass slides to digital images using sophisticated computerized technology to facilitate acquisition, evaluation, storage, and portability of histologic information. By its nature, digitization of analog histology data renders it amenable to analysis using deep learning/artificial intelligence (DL/AI) techniques. The application of DL/AI to digital pathology data holds promise, even if the scope of use cases and regulatory framework for deploying such applications in the clinical environment remains in the early stages. Recent studies using whole-slide images and DL/AI to detect histologic abnormalities in general and cancer in particular have shown encouraging results. In this review, we focus on these emerging technologies intended for use in diagnostic hematology and the evaluation of lymphoproliferative diseases.
Keywords
digital pathology, artificial intelligence, leukemia, lymphoma, hematopathology
Published Open-Access
yes
Recommended Citation
Hanadi El Achi and Joseph D Khoury, "Artificial Intelligence and Digital Microscopy Applications In Diagnostic Hematopathology" (2020). Faculty, Staff and Student Publications. 1934.
https://digitalcommons.library.tmc.edu/uthmed_docs/1934