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Objective: This study aims to examine the type of involvement of patient companions in the argumentative exchanges in consultations and explore when their contributions should be taken into account in shared decision-making (SDM)., Methods: A qualitative analysis was carried out using transcribed medical consultations (N = 10) between health professionals (doctors at a regional Dutch hospital), adult patients and informal patient companions. Insights from argumentation theory were used to develop an inventory of twelve theoretically distinct discussion situations involving patient companions, distinguishing possible discussion roles, disagreement types and coalition formations., Results: Consultations contained on average 4.3 discussion situations. In most discussions (37.21 %) the health professional adopted a standpoint, and the patient and their companion only expressed doubt. More complex cases occurred when one of the three parties, including the companion, opposed opinions of the other parties (in 34.88 % of the situations found) and when coalitions were formed (possible in 18.60 % of the situations found). We found that disagreements occurred or were anticipated by all three parties and involved standpoints about the diagnosis as well as treatment options., Conclusion: Using the pragma-dialectical argumentation theory as an analytical framework reveals that patient companions can substantially influence treatment decision-making during medical consultation. This influence is contingent upon the specific role they assume in the discussion, the type of disagreement with the health professional and patient, and the formation of coalitions with these parties., Practice Implications: The contributions by patient companions should be considered in SDM if the companion forms a coalition with the patient. If the companion does not form a coalition, the contributions might have a bearing on SDM as well, but their acceptability and relevance for the treatment decision should be checked by the health professional. In general, it is desirable to explicitly establish the role of patient companions in consultations., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

In this paper we present a knowledge-based femur detection algorithm. The algorithm uses femur corpus constraints, Canny edge detection and Hough lines. For optimal femur template placement in the local area we use cross-correlation. The segmentation itself is done with an optimized active shape modeling technique. Using the knowledge-based technique we have located 95% of the femur shapes of N=117 X-rays. From those 83% of the target femur shapes have been segmented successfully (point-to-point error: approximately 14 pixels, point-to-boundary error = approximately 9 pixels).