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Interactive visual exploration of surgical process data

PURPOSE: Integrated operating rooms provide rich sources of temporal information about surgical procedures, which has led to the emergence of surgical data science. However, little emphasis has been put on interactive visualization of such temporal datasets to gain further insights. Our goal is to p...

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Autores principales: Mayer, Benedikt, Meuschke, Monique, Chen, Jimmy, Müller-Stich, Beat P., Wagner, Martin, Preim, Bernhard, Engelhardt, Sandy
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9883333/
https://www.ncbi.nlm.nih.gov/pubmed/36271214
http://dx.doi.org/10.1007/s11548-022-02758-1
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author Mayer, Benedikt
Meuschke, Monique
Chen, Jimmy
Müller-Stich, Beat P.
Wagner, Martin
Preim, Bernhard
Engelhardt, Sandy
author_facet Mayer, Benedikt
Meuschke, Monique
Chen, Jimmy
Müller-Stich, Beat P.
Wagner, Martin
Preim, Bernhard
Engelhardt, Sandy
author_sort Mayer, Benedikt
collection PubMed
description PURPOSE: Integrated operating rooms provide rich sources of temporal information about surgical procedures, which has led to the emergence of surgical data science. However, little emphasis has been put on interactive visualization of such temporal datasets to gain further insights. Our goal is to put heterogeneous data sequences in relation to better understand the workflows of individual procedures as well as selected subsets, e.g., with respect to different surgical phase distributions and surgical instrument usage patterns. METHODS: We developed a reusable web-based application design to analyze data derived from surgical procedure recordings. It consists of aggregated, synchronized visualizations for the original temporal data as well as for derived information, and includes tailored interaction techniques for selection and filtering. To enable reproducibility, we evaluated it across four types of surgeries from two openly available datasets (HeiCo and Cholec80). User evaluation has been conducted with twelve students and practitioners with surgical and technical background. RESULTS: The evaluation showed that the application has the complexity of an expert tool (System Usability Score of 57.73) but allowed the participants to solve various analysis tasks correctly (78.8% on average) and to come up with novel hypotheses regarding the data. CONCLUSION: The novel application supports postoperative expert-driven analysis, improving the understanding of surgical workflows and the underlying datasets. It facilitates analysis across multiple synchronized views representing information from different data sources and, thereby, advances the field of surgical data science. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11548-022-02758-1.
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spelling pubmed-98833332023-01-29 Interactive visual exploration of surgical process data Mayer, Benedikt Meuschke, Monique Chen, Jimmy Müller-Stich, Beat P. Wagner, Martin Preim, Bernhard Engelhardt, Sandy Int J Comput Assist Radiol Surg Original Article PURPOSE: Integrated operating rooms provide rich sources of temporal information about surgical procedures, which has led to the emergence of surgical data science. However, little emphasis has been put on interactive visualization of such temporal datasets to gain further insights. Our goal is to put heterogeneous data sequences in relation to better understand the workflows of individual procedures as well as selected subsets, e.g., with respect to different surgical phase distributions and surgical instrument usage patterns. METHODS: We developed a reusable web-based application design to analyze data derived from surgical procedure recordings. It consists of aggregated, synchronized visualizations for the original temporal data as well as for derived information, and includes tailored interaction techniques for selection and filtering. To enable reproducibility, we evaluated it across four types of surgeries from two openly available datasets (HeiCo and Cholec80). User evaluation has been conducted with twelve students and practitioners with surgical and technical background. RESULTS: The evaluation showed that the application has the complexity of an expert tool (System Usability Score of 57.73) but allowed the participants to solve various analysis tasks correctly (78.8% on average) and to come up with novel hypotheses regarding the data. CONCLUSION: The novel application supports postoperative expert-driven analysis, improving the understanding of surgical workflows and the underlying datasets. It facilitates analysis across multiple synchronized views representing information from different data sources and, thereby, advances the field of surgical data science. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11548-022-02758-1. Springer International Publishing 2022-10-21 2023 /pmc/articles/PMC9883333/ /pubmed/36271214 http://dx.doi.org/10.1007/s11548-022-02758-1 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Original Article
Mayer, Benedikt
Meuschke, Monique
Chen, Jimmy
Müller-Stich, Beat P.
Wagner, Martin
Preim, Bernhard
Engelhardt, Sandy
Interactive visual exploration of surgical process data
title Interactive visual exploration of surgical process data
title_full Interactive visual exploration of surgical process data
title_fullStr Interactive visual exploration of surgical process data
title_full_unstemmed Interactive visual exploration of surgical process data
title_short Interactive visual exploration of surgical process data
title_sort interactive visual exploration of surgical process data
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9883333/
https://www.ncbi.nlm.nih.gov/pubmed/36271214
http://dx.doi.org/10.1007/s11548-022-02758-1
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