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Appilications accepted until March 28, 2021.
Scientific field and context: Ultrasound (US) imaging is well suited for cardiovascular disease screening. In particular, it allows the observation of thickening and pathological changes in the distensibility of the arterial wall. Recently, it has been shown that longitudinal wall motion and variations in wall thickness during the heart beat provide additional information on the biomechanical state of the wall, which may improve early detection of at-risk individuals. These phenomena are much more difficult to quantify and the validation of methods published to date is subject to uncertainties related to the use of manual tracings as a reference.
Objectives of the thesis: The main goal of the thesis is to develop segmentation and motion estimation methods capable of delineating the arterial wall and finding all the components of its displacement, throughout sequences of US images representing an artery, typically a carotid artery. To do so, the candidate will also develop simulation methods to generate realistic US-image sequences incorporating all the movements of interest, with the dual objective of training the models and creating perfectly controlled references to validate the proposed segmentation and motion estimation methods.
Expected innovative contributions: The main contribution will be a deep-learning-based motion estimation method capable of finding not only global displacements, but also local tissue deformations. In order to do this, a model will be developed relating the tissue motion to the changes in visual appearance of the characteristic US-image texture, called speckle. Another contribution will be a simulation method for generating very realistic sequences with perfectly controlled deformations, both to train the model and to create the ground truth necessary to validate the estimation method.
PhD thesis funding: Doctoral contract (3 years) at UCBL (University of Lyon). Please note that the applicant selected by the supervisors will have to defend her/his candidacy face to the institutional final-selection committee.
Expected candidate profile (prerequisite): image processing, machine learning, programming, interest for biomedical field and biomechanical modeling for health sector.
Application: Send to the supervisors your resume, transcript of records, and contacts of two references, preferably including your MSc project supervisor.
Bibliography examples:
Sami Qorchi, Didier Vray, Maciej Orkisz, Estimating arterial-wall deformations from automatic key-point detection and matching, Ultrasound in Medicine & Biology, 2021, in press, DOI: 10.1016/j.ultrasmedbio.2021.01.001
Fereshteh Yousefi Rizi, Jason Au, Heikki Yli-Ollila, Spyretta Golemati, Monika Makūnaitė, Maciej Orkisz, Nassir Navab, Maureen MacDonald, Tiina Marja Laitinen, Hamid Behnam, Zhifan Gao, Aimilia Gastounioti, Rytis Jurkonis, Didier Vray, Tomi Laitinen, André Sérusclat, Konstantina S. Nikita, Guillaume Zahnd, “Carotid Wall Longitudinal Motion in Ultrasound Imaging: An Expert Consensus Review”, Ultrasound in Medicine & Biology, 46:10, 2605-2624, 2020, DOI : 10.1016/j.ultrasmedbio.2020.06.006
Vincent Perrot, Ingvild Kinn Ekroll, Jørgen Avdal, Lars Saxhaug, Håvard Dalen, Didier Vray, Lasse Lovstakken, Hervé Liebgott. “Translation of Simultaneous Vessel Wall Motion and Vectorial Blood Flow Imaging in Healthy and Diseased Carotids to the Clinic: a Pilot Study”, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control, August 2020, DOI : 10.1109/TUFFC.2020.3015340
Guillaume Zahnd, Kostas Kapellas, Martijn van Hattem, Anouk van Dijk, André Sérusclat, Philippe Moulin, Aad van der Lugt, Michael Skilton, Maciej Orkisz, "A fully-automatic method to segment the carotid artery layers in ultrasound imaging - Application to quantify the compression-decompression pattern of the intima-media complex during the cardiac cycle", Ultrasound in Medicine and Biology, 43:1, 239–257 January 2017, DOI: 10.1016/j.ultrasmedbio.2016.08.016