Work

Robotic Intelligent Scanning With In-line Quality Assessment Successfully Digitized 24k Histopathology Archival Slides With Minimal Intervention

Year: 2022

Type: article

Abstract: Conclusion: Our results suggesting that our label-free anomaly detection pipeline is a viable strategy for generating high quality annotations -without tedious manual segmentation by pathologists.

Source: Journal of Pathology Informatics

DOI: 10.1016/j.jpi.2022.100068

Authors: Andrew P. Norgan, Bryan J. Dangott, Prasanth Perugupalli, Jason Ross, Kurt E. Simon, Darin P. Morgan, Stephanie A. Derauf, Thomas J. Flotte

Institutions: Mayo Clinic, Nference (United States)

Language: English

Topic: AI in cancer detection

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $1,400

OpenAlex ID: W4293217033

FWCI: 0.082

Cites:

Cited by: 1

Related to: 10