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Challenges and Benchmarks in Bioimage Analysis
M. Kozubek,
Jazyk angličtina Země Německo
Typ dokumentu časopisecké články, práce podpořená grantem, přehledy
- MeSH
- algoritmy MeSH
- benchmarking * MeSH
- databáze faktografické MeSH
- fluorescenční mikroskopie přístrojové vybavení metody normy MeSH
- lidé MeSH
- molekulární zobrazování přístrojové vybavení metody normy MeSH
- počítačové zpracování obrazu metody statistika a číselné údaje MeSH
- rozpoznávání automatizované statistika a číselné údaje MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- přehledy MeSH
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.
Citace poskytuje Crossref.org
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- $a Kozubek, Michal $u Faculty of Informatics, Centre for Biomedical Image Analysis, Masaryk University, Botanická 68a, Brno, 60200, Czech Republic. kozubek@fi.muni.cz.
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- $a 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.
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