Microscopy Image Browser: A Platform for Segmentation and Analysis of Multidimensional Datasets

被引：287

作者：

Belevich, Ilya ^{[1
]}

Joensuu, Merja ^{[1
,2
]}

Kumar, Darshan ^{[1
]}

Vihinen, Helena ^{[1
]}

Jokitalo, Eija ^{[1
]}

机构：

[1] Univ Helsinki, Inst Biotechnol, Electron Microscopy Unit, Helsinki, Finland

[2] Queensland Brain Inst, Single Mol Neurosci Lab, Brisbane, Qld, Australia

来源：

PLOS BIOLOGY | 2016年 / 14卷 / 01期

基金：

芬兰科学院;

关键词：

3D VISUALIZATION; CELLS;

D O I：

10.1371/journal.pbio.1002340

中图分类号：

Q5 [生物化学]; Q7 [分子生物学];

学科分类号：

071010 ; 081704 ;

摘要：

Understanding the structure-function relationship of cells and organelles in their natural context requires multidimensional imaging. As techniques for multimodal 3-D imaging have become more accessible, effective processing, visualization, and analysis of large datasets are posing a bottleneck for the workflow. Here, we present a new software package for high-performance segmentation and image processing of multidimensional datasets that improves and facilitates the full utilization and quantitative analysis of acquired data, which is freely available from a dedicated website. The open-source environment enables modification and insertion of new plug-ins to customize the program for specific needs. We provide practical examples of program features used for processing, segmentation and analysis of light and electron microscopy datasets, and detailed tutorials to enable users to rapidly and thoroughly learn how to use the program.

引用

页数：13

共 38 条

[1] SLIC Superpixels Compared to State-of-the-Art Superpixel Methods [J].