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ShuTu: Rat dentate gyrus granule cell 100X (compressed)

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DataCite Commons2022-12-21 更新2025-04-16 收录
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https://janelia.figshare.com/articles/dataset/ShuTu_an_Open-Source_Software_for_Neuron_Reconstruction_rat_dente_gyrus_granule_cell_100X_compressed_/5613184/4
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Here we provide images of a rat dentate gyrus granule cell (100X) for practicing reconstruction using the ShuTu software platform. The cell was filled and imaged by Ching-Lung Hsu in the Spruston Lab. Two resolutions are provided, 63X and 100X. For more accurate reconstruction, use 100X.Currently this compressed file is set up only for Ubuntu. Due to agressive compression, the sharpness of the images is somewhat reduced. To decompress, first install OpenJPEG then decompress the images using the following commands:sudo sh installOpenJpegForCompression.shpython decompressToTiff.py ~/granuleCellCompressShuTu (Chinese for "dendrite") is a software platform for semi-automated reconstruction of neuronal morphology. It is designed for neurons stained following patch-clamp recording and biocytin filling/staining. With an additional preprocessing step, it can also handle fluorescence images from confocal stacks. Even when there is only a single neuron in the imaged volume, automated reconstruction is tricky, because of background. Thus, ShuTu was developed to facilitate a two-step process: automated reconstruction, followed by manual correction. The software uses sophisticated algorithms to perform the automated reconstruction, as well as a convenient user interface to facilitate efficient completion of the reconstruction via manual annotation. <br> <br>

本数据集提供大鼠齿状回颗粒细胞(100倍)的成像图像,用于在ShuTu软件平台上练习神经元重建操作。该细胞由Spruston实验室的徐景龙(Ching-Lung Hsu)完成胞内填充与成像。本次提供了两种分辨率的图像:63倍与100倍。若需获得更精准的重建结果,建议使用100倍图像。 目前该压缩文件仅适配Ubuntu系统。由于采用了高强度压缩,图像的锐度有所下降。若需解压缩,请先安装OpenJPEG,再通过以下命令完成图像解压缩: sudo sh installOpenJpegForCompression.sh python decompressToTiff.py ~/granuleCellCompressShuTu ShuTu(中文意为“树突”)是一款用于神经元形态半自动化重建的软件平台。该软件适配经膜片钳记录及生物胞素填充/染色的神经元样本。若增加额外的预处理步骤,亦可处理共聚焦成像栈获取的荧光图像。即便成像视野中仅存在单个神经元,由于背景噪声的干扰,自动化重建仍颇具难度。因此,ShuTu的开发旨在支持两步式重建流程:先完成自动化重建,再进行手动校正。该软件集成了高精度的自动化重建算法,并配备便捷的用户界面,可通过手动标注高效完成神经元形态重建工作。
提供机构:
Janelia Research Campus
创建时间:
2017-11-27
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