Literature DB >> 27207369

Challenges and Benchmarks in Bioimage Analysis.

Michal Kozubek1.   

Abstract

Similar to the medical imaging community, the bioimaging community has recently realized the need to benchmark various image analysis methods to compare their performance and assess their suitability for specific applications. Challenges sponsored by prestigious conferences have proven to be an effective means of encouraging benchmarking and new algorithm development for a particular type of image data. Bioimage analysis challenges have recently complemented medical image analysis challenges, especially in the case of the International Symposium on Biomedical Imaging (ISBI). This review summarizes recent progress in this respect and describes the general process of designing a bioimage analysis benchmark or challenge, including the proper selection of datasets and evaluation metrics. It also presents examples of specific target applications and biological research tasks that have benefited from these challenges with respect to the performance of automatic image analysis methods that are crucial for the given task. Finally, available benchmarks and challenges in terms of common features, possible classification and implications drawn from the results are analysed.

Mesh:

Year:  2016        PMID: 27207369     DOI: 10.1007/978-3-319-28549-8_9

Source DB:  PubMed          Journal:  Adv Anat Embryol Cell Biol        ISSN: 0301-5556            Impact factor:   1.231


  4 in total

1.  MultiMap: A Tool to Automatically Extract and Analyse Spatial Microscopic Data From Large Stacks of Confocal Microscopy Images.

Authors:  Gherardo Varando; Ruth Benavides-Piccione; Alberto Muñoz; Asta Kastanauskaite; Concha Bielza; Pedro Larrañaga; Javier DeFelipe
Journal:  Front Neuroanat       Date:  2018-05-23       Impact factor: 3.856

2.  CytoPacq: a web-interface for simulating multi-dimensional cell imaging.

Authors:  David Wiesner; David Svoboda; Martin Maška; Michal Kozubek
Journal:  Bioinformatics       Date:  2019-11-01       Impact factor: 6.937

3.  The Need for Careful Data Collection for Pattern Recognition in Digital Pathology.

Authors:  Raphaël Marée
Journal:  J Pathol Inform       Date:  2017-04-10

4.  BIAS: Transparent reporting of biomedical image analysis challenges.

Authors:  Lena Maier-Hein; Annika Reinke; Michal Kozubek; Anne L Martel; Tal Arbel; Matthias Eisenmann; Allan Hanbury; Pierre Jannin; Henning Müller; Sinan Onogur; Julio Saez-Rodriguez; Bram van Ginneken; Annette Kopp-Schneider; Bennett A Landman
Journal:  Med Image Anal       Date:  2020-08-21       Impact factor: 8.545

  4 in total

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