Bioimage Informatics for Big Data.

Bioimage Informatics for Big Data.
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大数据生物图像信息学。

DOI:
10.1007/978-3-319-28549-8_10
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发表时间:
2016
期刊:
Advances in anatomy, embryology, and cell biology
影响因子:
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通讯作者:
Chen,Hanbo
Chen,Hanbo
中科院分区:
--
文献类型:
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作者:
Peng,Hanchuan;Zhou,Jie;Zhou,Zhi;Bria,Alessandro;Li,Yujie;Kleissas,DeanMark;Drenkow,NathanG;Long,Brian;Liu,Xiaoxiao;Chen,Hanbo

文献摘要

相似文献

生物图像信息学是一个领域,其中高通量图像信息学方法用于解决与生物学和医学相关的具有挑战性的科学问题。当图像数据集变得越来越大和复杂时,许多传统的图像分析方法不再适用。在这里,我们讨论了大规模生物图像信息学应用的两个关键挑战,即数据可访问性和自适应数据分析。我们强调案例研究表明,这些挑战可以解决基于分布式图像计算以及机器学习的图像示例在多维环境中。
Bioimage informatics is a field wherein high-throughput image informatics methods are used to solve challenging scientific problems related to biology and medicine. When the image datasets become larger and more complicated, many conventional image analysis approaches are no longer applicable. Here, we discuss two critical challenges of large-scale bioimage informatics applications, namely, data accessibility and adaptive data analysis. We highlight case studies to show that these challenges can be tackled based on distributed image computing as well as machine learning of image examples in a multidimensional environment.