Building a mass online annotation tool for dental radiographic imageryDownload PDF

11 Apr 2018 (modified: 16 May 2018)MIDL 2018 Abstract SubmissionReaders: Everyone
  • Abstract: In medical images analysis in general and for dental radiographic imagery more specifically, deep learning algorithms, in particular convolutional neural networks, are increasingly applied for detecting pathologies. However, creating an sufficiently large data set of labeled radiographic imagery for training deep neural networks is resource- and time-consuming. In order to build a large and reliably database of annotated dental radiographic imagery we are building a mass online annotation tool (Mono) for dental panoramic x-ray images. The tool is designed to allow evaluating the annotator’s proficiency against clinical records, majority vote schemes and model predictions in real time.
  • Keywords: online annotation system, radiographic imagery, oral pathologies, dentistry
  • Author Affiliation: CODE University of Applied Science and Charité – Universitätsmedizin Berlin
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