000125148 001__ 125148
000125148 005__ 20190509132207.0
000125148 0247_ $$2doi$$a10.5075/epfl-thesis-4165
000125148 02470 $$2urn$$aurn:nbn:ch:bel-epfl-thesis4165-8
000125148 02471 $$2nebis$$a5588468
000125148 037__ $$aTHESIS
000125148 041__ $$aeng
000125148 088__ $$a4165
000125148 245__ $$btheory and applications$$aInverse problems in acoustic tomography
000125148 269__ $$a2008
000125148 260__ $$bEPFL$$c2008$$aLausanne
000125148 300__ $$a139
000125148 336__ $$aTheses
000125148 520__ $$aAcoustic tomography aims at recovering the unknown parameters that describe a field of interest by studying the physical characteristics of sound propagating through the considered field. The tomographic approach is appealing in that it is non-invasive and allows to obtain a significantly larger amount of data compared to the classical one-sensor one-measurement setup. It has, however, two major drawbacks which may limit its applicability in a practical setting: the methods by which the tomographic data are acquired and then converted to the field values are computationally intensive and often ill-conditioned. This thesis specifically addresses these two shortcomings by proposing novel acoustic tomography algorithms for signal acquisition and field reconstruction. The first part of our exposition deals with some theoretical aspects of the tomographic sampling problems and associated reconstruction schemes for scalar and vector tomography. We show that the classical time-of-flight measurements are not sufficient for full vector field reconstruction. As a solution, an additional set of measurements is proposed. The main advantage of the proposed set is that it can be directly computed from acoustic measurements. It thus avoids the need for extra measuring devices. We then describe three novel reconstruction methods that are conceptually quite different. The first one is based on quadratic optimization and does not require any a priori information. The second method builds upon the notion of sparsity in order to increase the reconstruction accuracy when little data is available. The third approach views tomographic reconstruction as a parametric estimation problem and solves it using recent sampling results on non-bandlimited signals. The proposed methods are compared and their respective advantages are outlined. The second part of our work is dedicated to the application of the proposed algorithms to three practical problems: breast cancer detection, thermal therapy monitoring, and temperature monitoring in the atmosphere. We address the problem of breast cancer detection by computing a map of sound speed in breast tissue. A noteworthy contribution of this thesis is the development of a signal processing technique that significantly reduces the artifacts that arise in very inhomogeneous and absorbent tissue. Temperature monitoring during thermal therapies is then considered. We show how some of our algorithms allow for an increased spatial resolution and propose ways to reduce the computational complexity. Finally, we demonstrate the feasibility of tomographic temperature monitoring in the atmosphere using a custom-built laboratory-scale experiment. In particular, we discuss various practical aspects of time-of-flight measurement using cheap, off-the-shelf sensing devices.
000125148 6531_ $$aacoustic tomography
000125148 6531_ $$ainverse problems
000125148 6531_ $$abreast cancer
000125148 6531_ $$atemperature
000125148 6531_ $$awind
000125148 6531_ $$atomographie acoustique
000125148 6531_ $$aproblèmes inverses
000125148 6531_ $$acancer du sein
000125148 6531_ $$atempérature
000125148 6531_ $$avent
000125148 700__ $$0241124$$g154787$$aJovanovic, Ivana
000125148 720_2 $$aVetterli, Martin$$edir.$$g107537$$0240184
000125148 720_2 $$aSbaiz, Luciano$$edir.$$g115222$$0244018
000125148 8564_ $$uhttps://infoscience.epfl.ch/record/125148/files/EPFL_TH4165.pdf$$zTexte intégral / Full text$$s2769886$$yTexte intégral / Full text
000125148 909C0 $$xU10434$$0252056$$pLCAV
000125148 909CO $$pthesis-bn2018$$pDOI$$pIC$$ooai:infoscience.tind.io:125148$$qDOI2$$qGLOBAL_SET$$pthesis
000125148 918__ $$bIC-SSC$$cISC$$aIC
000125148 919__ $$aLCAV1
000125148 920__ $$b2008
000125148 970__ $$a4165/THESES
000125148 973__ $$sPUBLISHED$$aEPFL
000125148 980__ $$aTHESIS