Data augmentation based on spatial deformations for histopathology: An evaluation in the context of glomeruli segmentation-Reference-Cited by-同舟云学术

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Data augmentation based on spatial deformations for histopathology: An evaluation in the context of glomeruli segmentation

Published:2022-06 Issue: Volume:221 Page:106919
ISSN:0169-2607
Container-title:Computer Methods and Programs in Biomedicine
language:en
Short-container-title:Computer Methods and Programs in Biomedicine

Author:

Allender Florian,Allègre Rémi^ORCID,Wemmert Cédric,Dischler Jean-Michel

Funder

Horizon 2020 Framework Programme

Agence Nationale de la Recherche

Bundesministerium für Bildung und Forschung

Publisher

Elsevier BV

Subject

Health Informatics,Computer Science Applications,Software

Reference52 articles.

1. Deep learning as a tool for increased accuracy and efficiency of histopathological diagnosis;Litjens;Sci. Rep.,2016

2. A survey on deep learning in medical image analysis;Litjens;Med. Image Anal.,2017

3. Machine learning methods for histopathological image analysis;Komura;Comput. Struct. Biotechnol. J.,2018

4. Deep learning for whole slide image analysis: an overview;Dimitriou;Front. Med.,2019

5. Deep neural network models for computational histopathology: a survey;Srinidhi;Med. Image Anal.,2021

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