Blinded Visual Scoring of Images Using the Freely-available Software Blinder.


Journal Article

In nearly all subfields of biomedical sciences, there are phenotypes that are currently classified by expert visual scoring. In research applications, these classifications require the experimenter to be blinded to the treatment group in order to avoid unintentional bias in scoring. Currently, many labs either use laborious and tedious methods to manually blind the images, require multiple experimenters to gather and score the data blindly or fail to properly blind the data altogether. In this protocol, we present a simple, freely available software that we created that allows the experimenter to blindly score images. In our protocol, the user loads unblinded images and defines a scoring system. The software then shows the user the images in a random order, allowing the user to select a score from their defined scoring system for each image. Furthermore, the software has an optional "quality control" mechanism where the user will be shown some images multiple times to test the robustness of the visual scoring. Finally, the software summarizes the results in an exportable file that includes unblinded summary data for each group and a full list of images with their scores. In this protocol, we briefly present directions for using the software, potential applications, and caveats/limitations to this approach.

Full Text

Duke Authors

Cited Authors

  • Cothren, SD; Meyer, JN; Hartman, JH

Published Date

  • December 2018

Published In

Volume / Issue

  • 8 / 23

PubMed ID

  • 30761327

Pubmed Central ID

  • 30761327

Electronic International Standard Serial Number (EISSN)

  • 2331-8325

International Standard Serial Number (ISSN)

  • 2331-8325

Digital Object Identifier (DOI)

  • 10.21769/BioProtoc.3103


  • eng