Manual organelle segmentations (crop161) in near-isotropic, reconstructed volume electron microscopy (FIB-SEM) of mouse kidney (jrc_mus-kidney)

<b>This acquisition is part of the CellMap 2024 Segmentation Challenge</b><br><br>- <b>Challenge DOI:</b> https://doi.org/10.25378/janelia.c.7456966<br><br>- <b>Challenge Website:</b> https://cellmapchallenge.janelia.org/<br><br><b>Annotation description</b>: Dense segmentations of extracellular space, plasma membrane, mitochondrial membrane, mitochondrial lumen, vesicle membrane, endosome membrane, vesicle lumen, Golgi lumen, Golgi membrane, mitochondrial ribosome, endoplasmic reticulum lumen, endoplasmic reticulum membrane, lipid droplet lumen, lipid droplet membrane, endosome lumen, cytosol, Golgi, endosome, vesicle, lipid droplet, mitochondria, endoplasmic reticulum, cell, endoplasmic reticulum membrane collective in jrc_mus-kidney using Amira 3D 2021.1, Classic Segmentation Workroom and the 'Using Amira to manually segment organelles in vEM for machine learning V.3' annotation protocol.<br><br><b>Annotation ID</b>: crop161<br><br><b>Primary Annotator</b>: Woohyun Park<br><br><b>Annotation protocol</b>: Using Amira to manually segment organelles in vEM for machine learning V.3 (http://dx.doi.org/10.17504/protocols.io.bp2l61rb5vqe/v3)<br><br><b>Software</b>: Amira 3D 2021.1, Classic Segmentation Workroom<br><br><b>Annotated voxel size (nm)</b>: 4 x 4 x 4 (x, y, z)<br><br><b>Annotated data dimensions (µm)</b>: 0.8 x 0.8 x 0.8 (x, y, z)<br><br><b>Annotated data offset (nm)</b>: 44806 x 44078 x 68006 (x, y, z)<br><br><b>Classes annotated</b>: extracellular space, plasma membrane, mitochondrial membrane, mitochondrial lumen, vesicle membrane, endosome membrane, vesicle lumen, Golgi lumen, Golgi membrane, mitochondrial ribosome, endoplasmic reticulum lumen, endoplasmic reticulum membrane, lipid droplet lumen, lipid droplet membrane, endosome lumen, cytosol, Golgi, endosome, vesicle, lipid droplet, mitochondria, endoplasmic reticulum, cell, endoplasmic reticulum membrane collective<br><br><b>Dataset URL</b>: s3://janelia-cosem-datasets/jrc_mus-kidney/jrc_mus-kidney.zarr/recon-1/labels/groundtruth/crop161<br><br><b>Source (EM) dataset ID</b>: jrc_mus-kidney<br><br><b>Source (EM) voxel size (nm)</b>: 8 x 8 x 8 (x, y, z)<br><br><b>Source (EM) data dimensions (µm)</b>: 98.3 x 63.81 x 177.59 (x, y, z)<br><br><b>Source (EM) DOI</b>: https://doi.org/10.25378/janelia.16913035<br><br><b>Visualization website</b>: https://openorganelle.janelia.org/datasets/jrc_mus-kidney<br><br><b>Publication:</b> <i>CellMap Segmentation Challenge,</i> 2024.<br><br><b>The CellMap Project Team during this time consisted of:</b> David Ackerman, Davis Bennett, Marley Bryant, Hannah Nguyen, Grace Park, Alyson Petruncio, Alannah Post, Jacquelyn Price, Diana Ramirez, Jeff Rhoades, Rebecca Vorimo, Aubrey Weigel, Marwan Zouinkhi, Yurii Zubov.<br><br><b>The CellMap Project Team Steering Committee during this time consisted of:</b> Misha Ahrens, Christopher Beck, Teng-Leong Chew, Daniel Feliciano, Jan Funke, Harald Hess, Wyatt Korff, Jennifer Lippincott-Schwartz, Zhe J. Liu, Kayvon Pedram, Stephan Preibisch, Stephan Saalfeld, Ronald Vale, and Aubrey Weigel.

<b>本数据集属于CellMap 2024分割挑战赛（CellMap 2024 Segmentation Challenge）</b><br><br>- <b>挑战赛DOI</b>：https://doi.org/10.25378/janelia.c.7456966<br><br>- <b>挑战赛官网</b>：https://cellmapchallenge.janelia.org/<br><br><b>标注说明</b>：使用Amira 3D 2021.1、Classic Segmentation Workroom以及《Using Amira to manually segment organelles in vEM for machine learning V.3》标注协议，对jrc_mus-kidney样本中的细胞外间隙（extracellular space）、质膜（plasma membrane）、线粒体膜（mitochondrial membrane）、线粒体腔（mitochondrial lumen）、囊泡膜（vesicle membrane）、内体膜（endosome membrane）、囊泡腔（vesicle lumen）、高尔基腔（Golgi lumen）、高尔基膜（Golgi membrane）、线粒体核糖体（mitochondrial ribosome）、内质网腔（endoplasmic reticulum lumen）、内质网膜（endoplasmic reticulum membrane）、脂滴腔（lipid droplet lumen）、脂滴膜（lipid droplet membrane）、内体腔（endosome lumen）、细胞质基质（cytosol）、高尔基体（Golgi）、内体（endosome）、囊泡（vesicle）、脂滴（lipid droplet）、线粒体（mitochondria）、内质网（endoplasmic reticulum）、细胞（cell）以及内质网膜集合体（endoplasmic reticulum membrane collective）进行密集分割。<br><br><b>标注ID</b>：crop161<br><br><b>主要标注者</b>：Woohyun Park<br><br><b>标注协议</b>：《Using Amira to manually segment organelles in vEM for machine learning V.3》（http://dx.doi.org/10.17504/protocols.io.bp2l61rb5vqe/v3）<br><br><b>使用软件</b>：Amira 3D 2021.1、Classic Segmentation Workroom<br><br><b>标注体素尺寸（nm）</b>：4×4×4（x、y、z轴）<br><br><b>标注数据尺寸（µm）</b>：0.8×0.8×0.8（x、y、z轴）<br><br><b>标注数据偏移量（nm）</b>：44806×44078×68006（x、y、z轴）<br><br><b>标注类别</b>：细胞外间隙、质膜、线粒体膜、线粒体腔、囊泡膜、内体膜、囊泡腔、高尔基腔、高尔基膜、线粒体核糖体、内质网腔、内质网膜、脂滴腔、脂滴膜、内体腔、细胞质基质、高尔基体、内体、囊泡、脂滴、线粒体、内质网、细胞、内质网膜集合体<br><br><b>数据集URL</b>：s3://janelia-cosem-datasets/jrc_mus-kidney/jrc_mus-kidney.zarr/recon-1/labels/groundtruth/crop161<br><br><b>原始（EM）数据集ID</b>：jrc_mus-kidney<br><br><b>原始（EM）体素尺寸（nm）</b>：8×8×8（x、y、z轴）<br><br><b>原始（EM）数据尺寸（µm）</b>：98.3×63.81×177.59（x、y、z轴）<br><br><b>原始（EM）DOI</b>：https://doi.org/10.25378/janelia.16913035<br><br><b>可视化官网</b>：https://openorganelle.janelia.org/datasets/jrc_mus-kidney<br><br><b>相关出版物</b>：<i>CellMap 分割挑战赛</i>，2024年。<br><br><b>本项目期间的CellMap团队成员包括</b>：David Ackerman、Davis Bennett、Marley Bryant、Hannah Nguyen、Grace Park、Alyson Petruncio、Alannah Post、Jacquelyn Price、Diana Ramirez、Jeff Rhoades、Rebecca Vorimo、Aubrey Weigel、Marwan Zouinkhi、Yurii Zubov。<br><br><b>本项目期间的CellMap项目指导委员会成员包括</b>：Misha Ahrens、Christopher Beck、Teng-Leong Chew、Daniel Feliciano、Jan Funke、Harald Hess、Wyatt Korff、Jennifer Lippincott-Schwartz、Zhe J. Liu、Kayvon Pedram、Stephan Preibisch、Stephan Saalfeld、Ronald Vale以及Aubrey Weigel。