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Published in: BMC Medical Imaging 1/2017

Open Access 01-12-2017 | Research article

Testing of the assisting software for radiologists analysing head CT images: lessons learned

Authors: Petr Martynov, Nikolai Mitropolskii, Katri Kukkola, Monika Gretsch, Vesa-Matti Koivisto, Ilkka Lindgren, Jani Saunavaara, Jarmo Reponen, Anssi Mäkynen

Published in: BMC Medical Imaging | Issue 1/2017

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Abstract

Background

Assessing a plan for user testing and evaluation of the assisting software developed for radiologists.

Methods

Test plan was assessed in experimental testing, where users performed reporting on head computed tomography studies with the aid of the software developed. The user testing included usability tests, questionnaires, and interviews. In addition, search relevance was assessed on the basis of user opinions.

Results

The testing demonstrated weaknesses in the initial plan and enabled improvements. Results showed that the software has acceptable usability level but some minor fixes are needed before larger-scale pilot testing. The research also proved that it is possible even for radiologists with under a year’s experience to perform reporting of non-obvious cases when assisted by the software developed. Due to the small number of test users, it was impossible to assess effects on diagnosis quality.

Conclusions

The results of the tests performed showed that the test plan designed is useful, and answers to the key research questions should be forthcoming after testing with more radiologists. The preliminary testing revealed opportunities to improve test plan and flow, thereby illustrating that arranging preliminary test sessions prior to any complex scenarios is beneficial.
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Metadata
Title
Testing of the assisting software for radiologists analysing head CT images: lessons learned
Authors
Petr Martynov
Nikolai Mitropolskii
Katri Kukkola
Monika Gretsch
Vesa-Matti Koivisto
Ilkka Lindgren
Jani Saunavaara
Jarmo Reponen
Anssi Mäkynen
Publication date
01-12-2017
Publisher
BioMed Central
Published in
BMC Medical Imaging / Issue 1/2017
Electronic ISSN: 1471-2342
DOI
https://doi.org/10.1186/s12880-017-0229-1

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