Automated processing of zebrafish imaging data: a survey

Mikut, Ralf and Dickmeis, Thomas and Driever, Wolfgang and Geurts, Pierre and Hamprecht, Fred A. and Kausler, Bernhard X. and Ledesma Carbayo, María Jesús and Marée, Raphael and Mikula, Karol and Pantazis, Periklis and Ronneberger, Olaf and Santos Lleo, Andres de and Stotzka, Rainer and Sträehle, Uwe and Peyrieras, Nadine (2013). Automated processing of zebrafish imaging data: a survey. "Zebrafish", v. 10 (n. 3); pp. 401-421. ISSN 1545-8547.


Title: Automated processing of zebrafish imaging data: a survey
  • Mikut, Ralf
  • Dickmeis, Thomas
  • Driever, Wolfgang
  • Geurts, Pierre
  • Hamprecht, Fred A.
  • Kausler, Bernhard X.
  • Ledesma Carbayo, María Jesús
  • Marée, Raphael
  • Mikula, Karol
  • Pantazis, Periklis
  • Ronneberger, Olaf
  • Santos Lleo, Andres de
  • Stotzka, Rainer
  • Sträehle, Uwe
  • Peyrieras, Nadine
Item Type: Article
Título de Revista/Publicación: Zebrafish
Date: August 2013
ISSN: 1545-8547
Volume: 10
Faculty: E.T.S.I. Telecomunicación (UPM)
Department: Ingeniería Electrónica
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Due to the relative transparency of its embryos and larvae, the zebrafish is an ideal model organism for bioimaging approaches in vertebrates. Novel microscope technologies allow the imaging of developmental processes in unprecedented detail, and they enable the use of complex image-based read-outs for high-throughput/high-content screening. Such applications can easily generate Terabytes of image data, the handling and analysis of which becomes a major bottleneck in extracting the targeted information. Here, we describe the current state of the art in computational image analysis in the zebrafish system. We discuss the challenges encountered when handling high-content image data, especially with regard to data quality, annotation, and storage. We survey methods for preprocessing image data for further analysis, and describe selected examples of automated image analysis, including the tracking of cells during embryogenesis, heartbeat detection, identification of dead embryos, recognition of tissues and anatomical landmarks, and quantification of behavioral patterns of adult fish. We review recent examples for applications using such methods, such as the comprehensive analysis of cell lineages during early development, the generation of a three-dimensional brain atlas of zebrafish larvae, and high-throughput drug screens based on movement patterns. Finally, we identify future challenges for the zebrafish image analysis community, notably those concerning the compatibility of algorithms and data formats for the assembly of modular analysis pipelines.

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Item ID: 26813
DC Identifier:
OAI Identifier:
DOI: 10.1089/zeb.2013.0886
Official URL:
Deposited by: Memoria Investigacion
Deposited on: 31 May 2014 10:26
Last Modified: 22 Sep 2014 11:43
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