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Scattering Operator and Spectral Clustering for Ultrasound Images: Application on Deep Venous Thrombi

Thibaud Berthomier 1 Ali Mansour 2 Luc Bressollette 3 Frédéric Le Roy 2 Dominique Mottier 4 Léo Fréchier Barthélémy Hermenault
1 Lab-STICC_ENSTAB_CACS_COM
Lab-STICC - Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance
2 Lab-STICC_ENSTAB_CACS_COM
Lab-STICC - Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance
Abstract : Deep Venous Thrombosis (DVT) occurs when a thrombus is formed within a deep vein (most often in the legs). This disease can be deadly if a part or the whole thrombus reaches the lung and causes a Pulmonary Embolism (PE). This disorder, often asymptomatic, has multifactorial causes: immobilization, surgery, pregnancy, age, cancers, and genetic variations. Our project aims to relate the thrombus epidemiology (origins, patient predispositions, PE) to its structure using ultrasound images. Ultrasonography and elastography were collected using Toshiba Aplio 500 at Brest Hospital. This manuscript compares two classification approaches: spectral clustering and scattering operator. The former is based on the graph and matrix theories while the latter cascades wavelet convolutions with nonlinear modulus and averaging operators.
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https://hal.archives-ouvertes.fr/hal-01707228
Contributeur : Claude Morvan <>
Soumis le : mardi 27 février 2018 - 08:51:59
Dernière modification le : mercredi 24 juin 2020 - 16:19:51

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  • HAL Id : hal-01707228, version 1

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Thibaud Berthomier, Ali Mansour, Luc Bressollette, Frédéric Le Roy, Dominique Mottier, et al.. Scattering Operator and Spectral Clustering for Ultrasound Images: Application on Deep Venous Thrombi. International Journal of Biomedical and Biological Engineering, World Academy of Science, Engineering and Technology, 2017. ⟨hal-01707228⟩

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