ActiveDICOM - Enhancing Static Medical Images with Interaction

Florian Mistelbauer, Gabriel Mistelbauer, Meister Eduard Gröller
ActiveDICOM - Enhancing Static Medical Images with Interaction
Poster shown at Eurographics Workshop on Visual Computing for Biology and Medicine (2014-09-03-2014-09-05) In Posters at Eurographics Workshop on Visual Computing for Biology and Medicine. September 2014.

Information

Abstract

Digital Imaging and Communications in Medicine (DICOM) is a well-establish standard in medical imaging, consisting not only of image data, but sensitive data such as patient and examination information. Nowadays, although having a large variety of advanced rendering techniques available, DICOM images are still generated and sent to the Picture Archiving and Communication System (PACS). These images are then fetched by the medical doctor from a workstation and used for medical reporting. The user has no other possibilities than being able to change the windowing function for displaying the DICOM images. If a certain region is of special interest, either images of the whole data set are generated or have to be specifically requested. Both approaches consume a considerable amount of time. Secondly, the image generation on demand remains pending until done by the responsible assistant. Despite supporting a broad range of features and being widely applied, DICOM images remain static. We propose a visualization mapping language, Active DICOM Script (ADICT), which enhances conventional DICOM with interactive elements by combining heterogeneous data, interaction and visualization. Such DICOM images are then called Active Digital Imaging and Communications in Medicine (ActiveDICOM).

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BibTeX

@misc{fmistelbauer-2014-adict,
  title =      "ActiveDICOM - Enhancing Static Medical Images with
               Interaction",
  author =     "Florian Mistelbauer and Gabriel Mistelbauer and Meister
               Eduard Gr{"o}ller",
  year =       "2014",
  abstract =   "Digital Imaging and Communications in Medicine (DICOM) is a
               well-establish standard in medical imaging, consisting not
               only of image data, but sensitive data such as patient and
               examination information. Nowadays, although having a large
               variety of advanced rendering techniques available, DICOM
               images are still generated and sent to the Picture Archiving
               and Communication System (PACS). These images are then
               fetched by the medical doctor from a workstation and used
               for medical reporting. The user has no other possibilities
               than being able to change the windowing function for
               displaying the DICOM images. If a certain region is of
               special interest, either images of the whole data set are
               generated or have to be specifically requested. Both
               approaches consume a considerable amount of time. Secondly,
               the image generation on demand remains pending until done by
               the responsible assistant. Despite supporting a broad range
               of features and being widely applied, DICOM images remain
               static. We propose a visualization mapping language, Active
               DICOM Script (ADICT), which enhances conventional DICOM with
               interactive elements by combining heterogeneous data,
               interaction and visualization. Such DICOM images are then
               called Active Digital Imaging and Communications in Medicine
               (ActiveDICOM).",
  month =      sep,
  booktitle =  "Posters at Eurographics Workshop on Visual Computing for
               Biology and Medicine",
  event =      "Eurographics Workshop on Visual Computing for Biology and
               Medicine",
  location =   "Vienna, Austria",
  series =     "EG VCBM 2014",
  note =       "Poster presented at Eurographics Workshop on Visual
               Computing for Biology and Medicine (2014-09-03--2014-09-05)",
  URL =        "https://www.cg.tuwien.ac.at/research/publications/2014/fmistelbauer-2014-adict/",
}