Digital pen in mammography patient forms

Authors:
Daniel Sonntag;Marcus Liwicki;Markus Weber
Affiliations:
German Research Center for AI, Saarbrücken, Germany;German Research Center for AI, Kaiserslautern, Germany;German Research Center for AI, Kaiserslautern, Germany
Venue:
ICMI '11 Proceedings of the 13th international conference on multimodal interfaces
Year:
2011

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Abstract

We present a digital pen based interface for clinical radiology reports in the field of mammography. It is of utmost importance in future radiology practices that the radiology reports be uniform, comprehensive, and easily managed. This means that reports must be "readable" to humans and machines alike. In order to improve reporting practices in mammography, we allow the radiologist to write structured reports with a special pen on paper with an invisible dot pattern. A handwriting software takes care of the interpretation of the written report which is transferred into an ontological representation. In addition, a gesture recogniser allows radiologists to encircle predefined annotation suggestions which turns out to be the most beneficial feature. The radiologist can (1) provide the image and image region annotations mapped to a FMA, RadLex, or ICD10 code, (2) provide free text entries, and (3) correct/select annotations while using multiple gestures on the forms and sketch regions. The resulting, automatically generated PDF report is then stored in a semantic backend system for further use and contains all transcribed annotations as well as all free form sketches.