Seminar Digital Pathology and Deep Learning 2021 /KursID:2419
- Letzter Beitrag vom 2021-06-20

Einrichtung

Friedrich-Alexander-Universität Erlangen-Nürnberg

Aufzeichnungsart

Vorlesungsreihe

Zugang

IdM-Anmeldung / Studon

Sprache

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

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.

Kurskapitel

Folge
Titel
Lehrende(r)
Aktualisiert
Zugang
Dauer
Medien
1
Introduction: Digital Pathology and Deep Learning
Prof. Eva Katharina Breininger
2021-04-20
IdM-Anmeldung / Studon
01:33:34
2
Introduction: Digital Pathology and Deep Learning
PD Dr. Samir Jabari
2021-04-20
IdM-Anmeldung / Studon
01:14:48
Folge
Titel
Lehrende(r)
Aktualisiert
Zugang
Dauer
Medien
3
Mohammad Shkokani - Histopathology Quality Control and Artefacts Detection
Prof. Eva Katharina Breininger
2021-06-20
IdM-Anmeldung / Studon
00:28:24
4
Luisa Graf - Public datasets anc challenges
Prof. Eva Katharina Breininger
2021-06-20
IdM-Anmeldung / Studon
00:29:41
5
Mengzhou Sun - Histology and tissue segmentation
Prof. Eva Katharina Breininger
2021-06-20
IdM-Anmeldung / Studon
00:26:24
6
Bitan Saha - Cytology and Cell Detection
Prof. Eva Katharina Breininger
2021-06-20
IdM-Anmeldung / Studon
00:17:21
7
Ruolin Wang - Computational and Augmented Cancer Grading using Deep Neural Networks
Prof. Eva Katharina Breininger
2021-06-20
IdM-Anmeldung / Studon
00:35:23
8
Rahul Raj Menon - In vivo microstructual analysis
Prof. Eva Katharina Breininger
2021-06-20
IdM-Anmeldung / Studon
00:24:11
9
Deepak Charles Cheellapandian - Annotation tools and noisy labels
Prof. Eva Katharina Breininger
2021-06-20
IdM-Anmeldung / Studon
00:19:47
10
Dominik Perrin - Staining Differences and Ways to Counteract Them
Prof. Eva Katharina Breininger
2021-06-20
IdM-Anmeldung / Studon
00:00:00
11
Dóra Varnyú - Image Registration for Histology
Prof. Eva Katharina Breininger
2021-06-20
IdM-Anmeldung / Studon
00:27:29

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