DICODerma: A Practical Approach for Metadata Management of Images in Dermatology.

Clinical images are vital for diagnosing and monitoring skin diseases, and their importance has increased with the growing popularity of machine learning. Lack of standards has stifled innovation in dermatological imaging, unlike other image-intensive specialties such as radiology. We investigate th...

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Publicado en:Journal of Digital Imaging Vol. 35; no. 5; pp. 1231 - 1238
Autores principales: Eapen, Bell Raj, Kaliyadan, Feroze, Ashique, Karalikkattil T
Formato: pictorial tables/charts Journal Article
Publicado: Springer Nature Oct2022
Acceso en línea:Ver este registro en EBSCOhost
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          Eapen, Bell Raj
          Kaliyadan, Feroze
          Ashique, Karalikkattil T
        affil: McMaster University, 1280 Main Street West, L8S 4L8, Hamilton, Ontario, Canada
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        subj:
          Metadata
          Data Management
          DICOM
          Dermatology
          Machine Learning
          Image Processing, Computer Assisted
      ab: Clinical images are vital for diagnosing and monitoring skin diseases, and their importance has increased with the growing popularity of machine learning. Lack of standards has stifled innovation in dermatological imaging, unlike other image-intensive specialties such as radiology. We investigate the meta-requirements for utilizing the popular DICOM standard for metadata management of images in dermatology. We propose practical design solutions and provide open-source tools to integrate dermatologists' workflow with enterprise imaging systems. Using the tool, dermatologists can tag, search, organize and convert clinical images to the DICOM format. We believe that our less disruptive approach will improve the adoption of standards in the specialty.
      pubtype: Academic Journal
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    language: English
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