P
Philippe Delachartre
Researcher at Claude Bernard University Lyon 1
Publications - 115
Citations - 1427
Philippe Delachartre is an academic researcher from Claude Bernard University Lyon 1. The author has contributed to research in topics: Motion estimation & Imaging phantom. The author has an hindex of 18, co-authored 112 publications receiving 1311 citations. Previous affiliations of Philippe Delachartre include Lyon College & University of Lyon.
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Characterization of PVA cryogel for intravascular ultrasound elasticity imaging
TL;DR: The mechanical similitude of PVA cryogel with the biological tissues present in arteries is shown, and a good agreement between Young's modulus obtained from pressure column and from elastogram was also observed.
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Application of texture image analysis for the classification of bovine meat
TL;DR: Regression experiments showed that textural features have potential to indicate meat characteristics, and the potential of image analysis for meat sample recognition was shown.
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Axial strain imaging of intravascular data: results on polyvinyl alcohol cryogel phantoms and carotid artery.
Elisabeth Brusseau,Jérémie Fromageau,Gérard Finet,Gérard Finet,Philippe Delachartre,Didier Vray +5 more
TL;DR: The strain estimation method recently developed to compute elastograms of original vessel-mimicking cryogel phantoms and a fresh excised human carotid artery is used, effectively proved to be accurate in a wider range of strains than commonly used gradient-based methods, and very adapted for investigating highly heterogeneous tissues.
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A method for vector displacement estimation with ultrasound imaging and its application for thyroid nodular disease
Adrian Basarab,Herve Liebgott,Fabrice Morestin,Andrej Lyshchik,Andrej Lyshchik,Tatsuya Higashi,Ryo Asato,Philippe Delachartre +7 more
TL;DR: The proposed method, referred to as Bilinear Deformable Block Matching (BDBM), uses a bilinear model with eight parameters for controlling the local mesh deformation and outperforms the usual block matching.
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Axial Strain Imaging Using a Local Estimation of the Scaling Factor from RF Ultrasound Signals
TL;DR: An adaptive method based on the estimation of strains as local scaling factors, which can track various local deformations and its accuracy for strain up to 7% is developed.