Seminar Digital Pathology and Deep Learning 2020/2021 /CourseID:1977

Detailed information

Most recent entry on 2020-11-10 

Organisational Unit

Friedrich-Alexander-Universität Erlangen-Nürnberg

Recording type

Vorlesungsreihe

Via

IdM-login / Studon

Language

English

Lecturers:
Prof. Katharina Breininger, PD Dr. Samir Jabari, Christian Marzahl, M.Sc.
Prof. Dr.-Ing. habil. Andreas Maier, Prof. Dr. med. Ingmar Blümcke

Description:
Pathology is the study of diseases and aims to deliver a fine-grained diagnosis to understand processes in the body as well as to enable targeted treatment. In this area, the opportunities for digital image processing are vast: While the need for precision medicine, i.e., taking into account various co-dependencies when formulating the best possible treatment for a patient, is high, the number of pathologists ist not increasing accordingly. Deep learning-based techniques can be used for different objectives in this scope. Examples include screening large microscopy images for specific rare events, providing visual augmentation with analysis data. Additionally, the availability of massive data collections, including genomics and further biological factors, can be utilized to determine specific information about diseases that were previously unavailable.

Associated Clips

Episode
Title
Lecturer
Updated
Via
Duration
Media
1
Introduction: Digital Pathology and Deep Learning
Prof. Eva Katharina Breininger
2020-11-03
IdM-login / Studon
01:33:45
2
Introduction to Pathology
PD Dr. Samir Jabari
2020-11-10
IdM-login / Studon
01:06:06

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