Telepathology uses telecommunication technology to transmit microscopic images for diagnostic or teaching purposes. Basic requirements for a telepathology system are described. Usage scenarios for a telepathology network are presented including applications in intraoperative frozen section diagnosis, scientific collaboration and computer based training. Results of an evaluation of 4 currently available telepathology systems are presented.
Download full-text PDF |
Source |
|---|
Publication Analysis
Top Keywords
Similar Publications
Globalization of a telepathology network with artificial intelligence applications in Colombia: The GLORIA program study protocol.
J Pathol Inform
December 2024
Research Institute, Fundación Universitaria de Ciencias de la Salud, Bogotá, Colombia.
Article Synopsis
Cancer diagnosis in the post-coronavirus disease era: the promising role of telepathology and artificial intelligence.
Rev Assoc Med Bras (1992)
June 2024
D'Or IDOR Network Research Institute, Department of Pathology - São Paulo (SP), Brazil.
Digital pathology structure and deployment in Veneto: a proof-of-concept study.
Virchows Arch
September 2024
Surgical Pathology and Cytopathology Unit, Department of Medicine-DIMED, University of Padua School of Medicine, Padua, Italy.
Nowadays pathology laboratories are worldwide facing a digital revolution, with an increasing number of institutions adopting digital pathology (DP) and whole slide imaging solutions. Despite indeed providing novel and helpful advantages, embracing a whole DP workflow is still challenging, especially for wide healthcare networks. The Azienda Zero of the Veneto Italian region has begun a process of a fully digital transformation of an integrated network of 12 hospitals producing nearly 3 million slides per year.
View Article and Find Full Text PDFDeep Learning Assisted Imaging Methods to Facilitate Access to Ophthalmic Telepathology.
Ophthalmol Sci
December 2023
Department of Biomedical Engineering, University of California, Irvine, California.
Purpose: To investigate the use of super-resolution imaging techniques to enable telepathology using low-cost commercial cameras.
Design: Experimental study.
Participants: A total of 139 ophthalmic pathology slides obtained from the Ophthalmic Pathology service at the University of California, Irvine.
Artificial intelligence for evaluating the risk of gastric cancer: reliable detection and scoring of intestinal metaplasia with deep learning algorithms.
Gastrointest Endosc
December 2023
Department of Clinical Laboratory Sciences, School of Health Sciences, Shinshu University, Nagano, Japan.
Article Synopsis
- Gastric cancer risk is linked to chronic gastritis, and the OLGIM system can determine GC risk based on the level of intestinal metaplasia (IM), although scoring requires considerable expertise.
- A deep learning model, ResNet50, was used to analyze 5753 images of gastric biopsy samples, achieving a high sensitivity (97.7%) and specificity (94.6%) in classifying IM.
- The study indicates that the AI system can improve the accuracy and consistency of GC risk evaluation, potentially standardizing pathology assessments globally.
Want AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!