Design of a cooperative protocol to reference anatomical bone structures during orthopedic procedures via ultrasound imaging

X-rays remain the preferred imaging modality for orthopedic surgery for surgical planning, intra-operative control or patient follow-up. Nevertheless, it does not allow anatomical bone structures referencing. It is then impossible to control geometrical modifications of bone structures during the surgical process. However, surgical tools are referenced in the operating-room space and allow the surgeon to define anatomical structures geometrically by defining landmark positions. This process is only allowed during surgical procedures because it requires to do cuts on the patient. In this work, we propose a new approach using an ultrasound probe that is referenced in the operating-room space. We present an image processing algorithm to extract anatomical landmark position in a surgical context. It is a crucial improvement because it allows a complete patient follow-up from pre-operative planning to post-operative consults. To determine anatomical landmark positions on ultrasound images we added an intermediate step to extract the bone/soft tissues interface via several segmentation methods as active contours. Due to the low quality of ultrasound images we decided to design a innovative cooperative process. As the surgeon positions the ultrasound probe on the patient, the bone interface appears on the system screen in real time. Then the clinician can help the segmentation result to converge to the final solution by a soft movement of the probe. The validation of our work was performed on a database of 651 ultrasound images, in a non-cooperative way. The best algorithm that extracts the bone interface by defining the optimal path in a graph of potential candidates was validated with a cooperative protocol on a prototype called PhysioPilot, in order to perform physiological measurements in a non-surgical context

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Source https://theses.hal.science/tel-00906101
Author Masson-Sibut, Agnès
Maintainer CCSD
Last Updated May 8, 2026, 04:49 (UTC)
Created May 8, 2026, 04:49 (UTC)
Identifier NNT: 2013PEST1017
Language fr
Rights https://about.hal.science/hal-authorisation-v1/
contributor Laboratoire Images, Signaux et Systèmes Intelligents (LISSI) ; Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)
creator Masson-Sibut, Agnès
date 2013-01-31T00:00:00
harvest_object_id 0d78a3bb-fd4c-406e-ade3-a55c391da0e2
harvest_source_id 3374d638-d20b-4672-ba96-a23232d55657
harvest_source_title test moissonnage SELUNE
metadata_modified 2026-03-31T00:00:00
set_spec type:THESE