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Title | Quantifying Variability of Manual Annotation in Cryo-Electron Tomograms. |
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Journal, issue, pages | Microsc Microanal, Vol. 22, Issue 3, Page 487-496, Year 2016 |
Publish date | May 26, 2016 |
Authors | Corey W Hecksel / Michele C Darrow / Wei Dai / Jesús G Galaz-Montoya / Jessica A Chin / Patrick G Mitchell / Shurui Chen / Jemba Jakana / Michael F Schmid / Wah Chiu / |
PubMed Abstract | Although acknowledged to be variable and subjective, manual annotation of cryo-electron tomography data is commonly used to answer structural questions and to create a "ground truth" for evaluation ...Although acknowledged to be variable and subjective, manual annotation of cryo-electron tomography data is commonly used to answer structural questions and to create a "ground truth" for evaluation of automated segmentation algorithms. Validation of such annotation is lacking, but is critical for understanding the reproducibility of manual annotations. Here, we used voxel-based similarity scores for a variety of specimens, ranging in complexity and segmented by several annotators, to quantify the variation among their annotations. In addition, we have identified procedures for merging annotations to reduce variability, thereby increasing the reliability of manual annotation. Based on our analyses, we find that it is necessary to combine multiple manual annotations to increase the confidence level for answering structural questions. We also make recommendations to guide algorithm development for automated annotation of features of interest. |
External links | Microsc Microanal / PubMed:27225525 / PubMed Central |
Methods | EM (tomography) |
Structure data | EMDB-8173: EMDB-8174: |
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