CellProfiler 3.0: Next-generation image processing for biology.
CellProfiler 3.0: Next-generation image processing for biology.
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DOI：
10.1371/journal.pbio.2005970
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发表时间：
2018-07
期刊：
影响因子：
9.8
通讯作者：
Carpenter AE
中科院分区：
文献类型：
--
作者：
McQuin C;Goodman A;Chernyshev V;Kamentsky L;Cimini BA;Karhohs KW;Doan M;Ding L;Rafelski SM;Thirstrup D;Wiegraebe W;Singh S;Becker T;Caicedo JC;Carpenter AE
自2005年发布以来，CellProfiler使科学研究社区能够创建灵活的模块化图像分析管道。在这里，我们描述了CellProfiler 3.0，一个新版本的软件，支持全体积和平面分析的三维（3D）图像堆栈，越来越普遍的生物医学研究。CellProfiler的基础设施得到了极大的改进，我们提供了一个基于云的大规模图像处理协议。新的插件可以在图像上运行预训练的深度学习模型。CellProfiler由生物学家设计并为生物学家设计，通过记录良好的用户界面为研究人员提供强大的计算工具，使所有领域的生物学家能够创建定量，可重现的图像分析工作流程。“大数据革命”已经冲击了生物学：现在机器人准备细胞样本并拍摄数千张显微镜图像已经很常见。用眼睛观看生成的图像将是极其乏味的，更不用说主观的了。因此，许多生物学家发现他们需要软件来轻松准确地分析图像。我们的免费开源软件CellProfiler的第三个主要版本旨在帮助生物学家处理图像，无论是几张还是数千张。研究人员可以下载在线示例工作流（即“管道”）或从头开始创建自己的工作流。管道易于保存、重用和共享，有助于提高科学的可重复性。在此版本中，我们添加了在三维（3D）图像中查找和测量对象的功能。我们还对CellProfiler的底层代码进行了更改，使其运行速度更快，安装更容易，我们还增加了在云中处理图像和使用神经网络（深度学习）的功能。我们还为CellProfiler的设置添加了更多说明，以帮助新用户入门。我们希望这些变化将使CellProfiler成为当前用户更好的工具，并为新用户提供更好的方法来开始进行定量图像分析。
CellProfiler has enabled the scientific research community to create flexible, modular image analysis pipelines since its release in 2005. Here, we describe CellProfiler 3.0, a new version of the software supporting both whole-volume and plane-wise analysis of three-dimensional (3D) image stacks, increasingly common in biomedical research. CellProfiler’s infrastructure is greatly improved, and we provide a protocol for cloud-based, large-scale image processing. New plugins enable running pretrained deep learning models on images. Designed by and for biologists, CellProfiler equips researchers with powerful computational tools via a well-documented user interface, empowering biologists in all fields to create quantitative, reproducible image analysis workflows. The “big-data revolution” has struck biology: it is now common for robots to prepare cell samples and take thousands of microscopy images. Looking at the resulting images by eye would be extremely tedious, not to mention subjective. Thus, many biologists find they need software to analyze images easily and accurately. The third major release of our free open-source software CellProfiler is designed to help biologists working with images, whether a few or thousands. Researchers can download an online example workflow (that is, a “pipeline”) or create their own from scratch. Pipelines are easy to save, reuse, and share, helping improve scientific reproducibility. In this release, we’ve added the capability to find and measure objects in three-dimensional (3D) images. We’ve also made changes to CellProfiler’s underlying code to make it faster to run and easier to install, and we’ve added the ability to process images in the cloud and using neural networks (deep learning). We’ve also added more explanations to CellProfiler’s settings to help new users get started. We hope these changes will make CellProfiler an even better tool for current users and will provide new users better ways to get started doing quantitative image analysis.
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影响因子：
12.3
作者：
Carpenter AE;Jones TR;Lamprecht MR;Clarke C;Kang IH;Friman O;Guertin DA;Chang JH;Lindquist RA;Moffat J;Golland P;Sabatini DM
通讯作者：
Sabatini DM
影响因子：
48
作者：
Caicedo JC;Cooper S;Heigwer F;Warchal S;Qiu P;Molnar C;Vasilevich AS;Barry JD;Bansal HS;Kraus O;Wawer M;Paavolainen L;Herrmann MD;Rohban M;Hung J;Hennig H;Concannon J;Smith I;Clemons PA;Singh S;Rees P;Horvath P;Linington RG;Carpenter AE
通讯作者：
Carpenter AE
影响因子：
3.7
作者：
RAND, WM
通讯作者：
RAND, WM
影响因子：
6.7
作者：
Stanley SA;Barczak AK;Silvis MR;Luo SS;Sogi K;Vokes M;Bray MA;Carpenter AE;Moore CB;Siddiqi N;Rubin EJ;Hung DT
通讯作者：
Hung DT
影响因子：
48
作者：
Eliceiri, Kevin W.;Berthold, Michael R.;Goldberg, Ilya G.;Ibanez, Luis;Manjunath, B. S.;Martone, Maryann E.;Murphy, Robert F.;Peng, Hanchuan;Plant, Anne L.;Roysam, Badrinath;Stuurmann, Nico;Swedlow, Jason R.;Tomancak, Pavel;Carpenter, Anne E.
通讯作者：
Carpenter, Anne E.