Print Email Facebook Twitter User Interaction in Semi-Automatic Segmentation of Organs at Risk: A Case Study in Radiotherapy Title User Interaction in Semi-Automatic Segmentation of Organs at Risk: A Case Study in Radiotherapy Author Ramkumar, A. Dolz, J. Kirisli, H.A. Adebahr, S. Schimek-Jasch, T. Nestle, U. Massoptier, L. Varga, E. Stappers, P.J. Niessen, W.J. Song, Y. Faculty Industrial Design Engineering Department Design Engineering Date 2015-11-09 Abstract Accurate segmentation of organs at risk is an important step in radiotherapy planning. Manual segmentation being a tedious procedure and prone to inter- and intra-observer variability, there is a growing interest in automated segmentation methods. However, automatic methods frequently fail to provide satisfactory result, and post-processing corrections are often needed. Semi-automatic segmentation methods are designed to overcome these problems by combining physicians’ expertise and computers’ potential. This study evaluates two semi-automatic segmentation methods with different types of user interactions, named the “strokes” and the “contour”, to provide insights into the role and impact of human-computer interaction. Two physicians participated in the experiment. In total, 42 case studies were carried out on five different types of organs at risk. For each case study, both the human-computer interaction process and quality of the segmentation results were measured subjectively and objectively. Furthermore, different measures of the process and the results were correlated. A total of 36 quantifiable and ten non-quantifiable correlations were identified for each type of interaction. Among those pairs of measures, 20 of the contour method and 22 of the strokes method were strongly or moderately correlated, either directly or inversely. Based on those correlated measures, it is concluded that: (1) in the design of semi-automatic segmentation methods, user interactions need to be less cognitively challenging; (2) based on the observed workflows and preferences of physicians, there is a need for flexibility in the interface design; (3) the correlated measures provide insights that can be used in improving user interaction design. Subject radiotherapyorgans at risksemi-automatic segmentationhuman-computer interactionevaluationcorrelations To reference this document use: http://resolver.tudelft.nl/uuid:9b84f886-549a-4b3a-ae9f-d15bf1f3a8a8 Publisher Springer ISSN 0897-1889 Source https://doi.org/10.1007/s10278-015-9839-8 Source Journal of Digital Imaging, 29 (2), 2015 Part of collection Institutional Repository Document type journal article Rights (c) 2015 The Author(s)This article is published with open access at Springerlink.com Files PDF Song 2015.pdf 4.67 MB Close viewer /islandora/object/uuid:9b84f886-549a-4b3a-ae9f-d15bf1f3a8a8/datastream/OBJ/view