MIT License

项目介绍

lahammond/BrainJ 是一个托管在 GitHub 上的开源项目,主要使用 ImageJ Macro 编写,采用 MIT License 许可证,目前获得 33 个 Star、8 次 Fork。

仓库全名
lahammond/BrainJ
开源许可证
MIT License
Star 数
33
Fork 数
8
未关闭 Issue
4

README 摘要

BrainJ An accessible tool for automated brain reconstruction, mesoscale mapping, and cell analysis. Please read the BrainJ Guide.pdf for step-by-step instructions and troubleshooting. A recorded workshop on using BrainJ for quantitive analysis of cells and projections, as well as analysis of probe and GRIN lens placement, is now available on YouTube. We also support the enhanced and unified mouse brain atlas. About…

完整内容见 GitHub 原始 README 或本页 。

常见问题

BrainJ 用什么语言开发?

主要使用 ImageJ Macro 编写,采用 MIT License 许可证,目前有 33 个 Star。

BrainJ 可以免费商用吗?

仓库采用 MIT License 许可证,可免费使用与修改,商业使用请遵守许可证条款(例如保留版权声明与许可声明)。

如何获取 BrainJ 的源码?

可以直接克隆仓库:git clone https://github.com/lahammond/BrainJ.git,默认分支为 master;安装与运行步骤见仓库 README。

BrainJ 最近还在维护吗?

仓库最近一次更新为 2023年10月13日,当前有 4 个未关闭 Issue;Star 数为 33,可作为社区活跃度的参考。

关于

Fiji pipeline for automated serial section reconstruction and mouse brain analysis.

描述取自 GitHub 官方 API,中文内容由 GitRead 中文社区 编辑团队整理。

简要分析

热度分
51
价值分
22
活跃状态
活跃
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语言占比

ImageJ Macro
JavaScript

Release

README

DOI

BrainJ

An accessible tool for automated brain reconstruction, mesoscale mapping, and cell analysis.

Please read the BrainJ Guide.pdf for step-by-step instructions and troubleshooting.

A recorded workshop on using BrainJ for quantitive analysis of cells and projections, as well as analysis of probe and GRIN lens placement, is now available on YouTube.

We also support the enhanced and unified mouse brain atlas.

About

Reconstructing serial tissue sections into whole brains and analyzing them within a common coordinate framework is an essential capability for the discovery of novel circuits and studies in neuroscience. Many existing solutions require coding experience, commercial software, or labor-intensive interaction and annotation for researchers. With an emphasis on accessibility and automation, BrainJ enables high-throughput analysis of serial tissue sections imaged using confocal or widefield techniques. Developed in Fiji, our approach leverages freely available tools for machine learning pixel classification for cell detection and mesoscale mapping of axons and dendrites. With a simple graphical user interface, this approach is easy to deploy and use, requiring no coding experience and minimal manual intervention to process multiple datasets. Our approach is extensible to any project requiring serial section reconstruction and atlas-based analysis and allows a typical whole-brain dataset to be reconstructed and analyzed within 2-4 hours.

Installation

  • Install Fiji/ImageJ
  • Install BrainJ - Download BrainJ.jar and copy into your ImageJ plugins folder
  • Install MultiStackReg - Download and copy into your ImageJ plugins folder
  • Install TurboReg
  • Install Elastix 5.0.0)
  • Install Ilastix 1.3.3post3
  • Download the required atlas files and Ilastik project
  • Store the atlas files folder somewhere on your computer. The pipeline will use the files in this folder to perform analysis and generate visualizations

Citing

If you use BrainJ please cite our publication:

An amygdala circuit mediates experience-dependent momentary exploratory arrests. Botta et al. Cell 2020

Usage

Limitations

  • Badly damaged tissue may prevent registration and alignment to atlas.
  • Requires sections spanning at least 2-3mm in the anterior-posterior axis.

Similar Tools

If you are reconstructing and analyzing spinal cords - see our new tool SpinalJ for the mouse spinal cord.**

For tissue sections:

For whole brain data:

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