Seminar Digital Pathology and Deep Learning [SerienID : 2419]

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.

Semester

Sommersemester 2021

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aktualisiert

2021-10-25 20:55:27

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    • #1
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      Introduction: Digital Pathology and Deep Learning
      Prof. Eva Katharina Breininger
      2021-04-20 Sommersemester 2021
    • #2
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      Introduction: Digital Pathology and Deep Learning
      PD Dr. Samir Jabari
      2021-04-20 Sommersemester 2021
    • #3
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      Mohammad Shkokani - Histopathology Quality Control and Artefacts Detection
      Prof. Eva Katharina Breininger
      2021-06-20 Sommersemester 2021
    • #4
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      Luisa Graf - Public datasets anc challenges
      Prof. Eva Katharina Breininger
      2021-06-20 Sommersemester 2021
    • #5
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      Mengzhou Sun - Histology and tissue segmentation
      Prof. Eva Katharina Breininger
      2021-06-20 Sommersemester 2021
    • #6
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      Bitan Saha - Cytology and Cell Detection
      Prof. Eva Katharina Breininger
      2021-06-20 Sommersemester 2021
    • #7
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      Ruolin Wang - Computational and Augmented Cancer Grading using Deep Neural Networks
      Prof. Eva Katharina Breininger
      2021-06-20 Sommersemester 2021
    • #8
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      Rahul Raj Menon - In vivo microstructual analysis
      Prof. Eva Katharina Breininger
      2021-06-20 Sommersemester 2021
    • #9
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      Deepak Charles Cheellapandian - Annotation tools and noisy labels
      Prof. Eva Katharina Breininger
      2021-06-20 Sommersemester 2021
    • #10
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      Dominik Perrin - Staining Differences and Ways to Counteract Them
      Prof. Eva Katharina Breininger
      2021-06-20 Sommersemester 2021
    • #11
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      Dóra Varnyú - Image Registration for Histology
      Prof. Eva Katharina Breininger
      2021-06-20 Sommersemester 2021