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Adv Anat Embryol Cell Biol ; 219: 263-72, 2016.
Article in English | MEDLINE | ID: mdl-27207370

ABSTRACT

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 When the image datasets become larger and more complicated, many conventional image analysis approaches are no longer applicable.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.


Subject(s)
Computational Biology/statistics & numerical data , Image Processing, Computer-Assisted/statistics & numerical data , Machine Learning , Molecular Imaging/methods , Computational Biology/methods , Data Interpretation, Statistical , Humans , Image Processing, Computer-Assisted/methods , Microscopy, Fluorescence/instrumentation , Microscopy, Fluorescence/methods , Molecular Imaging/instrumentation , Pattern Recognition, Automated/statistics & numerical data
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