Towards a GUI for Declarative Medical Image Analysis: Cognitive and Memory Load Issues
Communications in Computer and Information Science, ISSN: 1865-0937, Vol: 1581 CCIS, Page: 103-111
2022
- 5Captures
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Captures5
- Readers5
Conference Paper Description
In medical imaging, (semi-)automatic image analysis techniques have been proposed to support the current time-consuming and cognitively demanding practice of manual segmentation of regions of interest (ROIs). The recently proposed image query language ImgQL, based on spatial logic and model checking, represents segmentation methods as concise, domain-oriented, human-readable procedures aimed at domain experts rather than technologists, and has been validated in several case studies. Such efforts are directed towards a human-centred Artificial Intelligence methodology. To this aim, we complemented the ongoing research line with a study of the Human-Computer Interaction aspects. In this work we investigate the design of a graphical user interface (GUI) prototype that supports the analysis procedure with minimal impact on the focus and the memory load of domain experts.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85133258201&origin=inward; http://dx.doi.org/10.1007/978-3-031-06388-6_14; https://link.springer.com/10.1007/978-3-031-06388-6_14; https://dx.doi.org/10.1007/978-3-031-06388-6_14; https://link.springer.com/chapter/10.1007/978-3-031-06388-6_14
Springer Science and Business Media LLC
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