Deep learning in digital pathology and microscopy for research and clinical practice
Deep learning in digital pathology and microscopy for research and clinical practice
- Abstract number
- 286
- Event
- European Microscopy Congress 2020 Invited Speakers
- DOI
- 10.22443/rms.emc2020.286
- Corresponding Email
- [email protected]
- Session
- DHA.1 - Deep learning for analysis and interpretation of microscopy imaging data
- Authors
- Dr Geert Litjens (1)
- Affiliations
-
1. Radboud University Medical Center
- Keywords
artificial intelligence; biomedical imaging; computational pathology; deep learning;
- Abstract text
In recent years, deep learning has revolutionized computer vision. The (bio)medical imaging community has taken note of these developments and over the past five years has introduced these techniques in research, with sometimes revolutionary results. In this talk, I will focus on novel machine learning applications for the analysis and interpretation of microscopy images, both from a clinical, histopathology and a pre-clinical, research setting. I will show current possibilities with respect to disease detection, classification, segmentation and prognosis estimation for a variety of modalities. Last, I will focus on the impact these methods can have for clinicians and researchers alike by accelerating diagnostics and research while improving the quality.