Artificial Intelligence

Course Description

This course will introduce the learner to:

a. Explain the theory, principles, and indications for techniques in cytology/pathology for:

1) Telepathology/Telecytology
2) Digital image acquisition, management (storage, retrieval and sharing pathology information)
3) Image capture via static photography, dynamic telepathology (viewing real-time images and virtual slides / whole- slide imaging
4) Quantification of specific image features (DNA analysis, morphometric analysis, FISH)
5) Video conferencing and presentation techniques

b. Utilize clinical digital cytology/pathology to assist the pathologist as part of a health care team, including, but not limited to rapid on-site adequacy assessment, intra-operative consultation, and second opinion consultation.

Learning Outcomes

The learner will be able to explain the theory, principles, indications, technical aspects, and troubleshooting of Digital Pathology; and the role of AI in pathology.

  1. Introduction to Digital Pathology
  2. Potential of digital pathology in routine diagnosis
  3. Role of Artificial Intelligence in Digital Pathology

Digital Pathology Explained – Animation

Introduction to Digital Pathology

Unlocking the full potential of digital pathology in routine diagnosis at AZ Sint-Jan, Bruges

AI for Pathology – Professor Nasir Rajpoot

Artificial Intelligence in Pathology : Implementation Strategies