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Erschienen in: Medical & Biological Engineering & Computing 4/2019

27.11.2018 | ORIGINAL ARTICLE

Iterative simulations to estimate the elastic properties from a series of MRI images followed by MRI-US validation

verfasst von: Francesco Visentin, Vincent Groenhuis, Bogdan Maris, Diego Dall’Alba, Françoise Siepel, Stefano Stramigioli, Paolo Fiorini

Erschienen in: Medical & Biological Engineering & Computing | Ausgabe 4/2019

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Abstract

The modeling of breast deformations is of interest in medical applications such as image-guided biopsy, or image registration for diagnostic purposes. In order to have such information, it is needed to extract the mechanical properties of the tissues. In this work, we propose an iterative technique based on finite element analysis that estimates the elastic modulus of realistic breast phantoms, starting from MRI images acquired in different positions (prone and supine), when deformed only by the gravity force. We validated the method using both a single-modality evaluation in which we simulated the effect of the gravity force to generate four different configurations (prone, supine, lateral, and vertical) and a multi-modality evaluation in which we simulated a series of changes in orientation (prone to supine). Validation is performed, respectively, on surface points and lesions using as ground-truth data from MRI images, and on target lesions inside the breast phantom compared with the actual target segmented from the US image. The use of pre-operative images is limited at the moment to diagnostic purposes. By using our method we can compute patient-specific mechanical properties that allow compensating deformations.

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Metadaten
Titel
Iterative simulations to estimate the elastic properties from a series of MRI images followed by MRI-US validation
verfasst von
Francesco Visentin
Vincent Groenhuis
Bogdan Maris
Diego Dall’Alba
Françoise Siepel
Stefano Stramigioli
Paolo Fiorini
Publikationsdatum
27.11.2018
Verlag
Springer Berlin Heidelberg
Erschienen in
Medical & Biological Engineering & Computing / Ausgabe 4/2019
Print ISSN: 0140-0118
Elektronische ISSN: 1741-0444
DOI
https://doi.org/10.1007/s11517-018-1931-z

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