Estimation de paramètres de champs markoviens cachés avec applications à la segmentation d'images et la localisation de formes

Thèse numérisée par la Direction des bibliothèques de l'Université de Montréal

Coherent and incoherent ultrasound backscatter from cell aggregates

International audienceThe Effective Medium Theory (EMT) combined with the Structure Factor Model was recently developed to model the ultrasound backscatter from aggregating Red Blood Cells (RBCs) [Frances-chini, Metzger, Cloutier, IEEE UFFC, 2011]. The EMT assumes that aggregates can be treated as homogeneous effective spheres and the structure factor considers the interactions between the effective spheres. In this study, the EMT is further developed to decompose the differential backscattering cross section of a single cell aggregate into coherent and incoherent components. The coherent component corresponds to the average backscatter from the effective scatterer, and the incoherent component considers the fluctuation of the scattering wave around its average within the effective scatterer. A new theoretical expression for the incoherent component based on the structure factor is proposed and compared with another formulation based on the Gaussian direct correlation function. This theoretical improvement is assessed using computer simulations of ultrasound backscatter from aggregating cells. The consideration of the incoherent component based on the structure factor allows to approximate the simulations satisfactorily for a krag limit around 2, against a krag limit comprised between 1.07 and 1.47 with the former model considering only the coherent component

Regularized ultrasound phantom-free local Attenuation Coefficient Slope (ACS) imaging in homogeneous and heterogeneous tissues

Attenuation map or measurements based on local attenuation coefficient slope (ACS) in quantitative ultrasound (QUS) has shown potential for diagnosis of liver steatosis. In liver cancers, tissue abnormalities and tumors detected using ACS are also of interest to provide new image contrast to clinicians. Current phantom-based approaches have the limitation of assuming comparable speed of sound between the reference phantom and insonified tissues. Moreover, these methods present the inconvenience for operators to acquire data on phantoms as well as on patients. The main goal was to alleviate these drawbacks by proposing a methodology for constructing phantom-free regularized (PF-R) local ACS maps and investigate the performance in both homogeneous and heterogeneous media. The proposed method was tested on two tissue mimicking media with different ACS constructed as homogeneous phantoms, side-byside and top-to-bottom phantoms, and inclusion phantoms with different attenuations. Moreover, an in-vivo proof-of-concept was performed on healthy, steatotic and cancerous human liver datasets. Modifications brought to previous works include: a) a linear interpolation of the power spectrum in log-scale; b) the relaxation of the underlying hypothesis on the diffraction factor; c) a generalization to nonhomogeneous local ACS; and d) an adaptive restriction of frequencies to a more reliable range than the usable frequency range. Regularization was formulated as a generalized LASSO, and a variant of the Bayesian Information Criterion (BIC) was applied to estimate the Lagrangian multiplier on the LASSO constraint. In addition, we evaluated the proposed algorithm when applying median filtering before and after regularization. Tests conducted showed that the PF-R yielded robust results in all tested conditions, suggesting potential for additional validation as a diagnosis method

The added value of quantitative ultrasound to shear-wave elastography for assessment of steatohepatitis in a rat model

Non-alcoholic fatty liver disease is a highly prevalent condition, which may progress to non-alcoholic steatohepatitis (NASH), an advanced form found in 3 to 5% of the population. As liver biopsy is invasive, there is a need for a non-invasive technique for the assessment of NASH. Due to promising results of shear wave elastography (SWE) in staging this disease, there is a high interest in developing a multi-parametric approach for assessment of liver steatosis within the same ultrasound (US) examination. The goal of this study was to assess the added value of quantitative US (QUS) parameters to SWE, based on random forest classifiers and areas under the ROC curve (AUC). Sixty male Sprague-Dawley rats were either fed a standard chow or a methionine- and choline-deficient diet. Using a research US system (model V1, Verasonics Inc.), SWE measurements were performed while rats were under anesthesia. To generate shear wavefronts within the liver, a linear array US transducer (ATL L7-4, Philips) was used to induce three 40-V 125-μs long radiation force pushes 4 mm apart. For SW tracking, the same transducer was used to acquire plane wave radiofrequency data at a frame rate of 4 kHz; images were reconstructed using the f-k migration algorithm. QUS acquisitions were performed using the same system and transducer. One hundred frames were acquired, migrated, and the echo envelope was obtained with Hilbert transforms. The image post-processing yielded 4 homodyned-K parametric maps within the region-of-interest (ROI), from which 8 features were extracted. The local attenuation coefficient slope within the ROI was also computed using the spectral shift method. QUS parameters improved the classification accuracy of steatohepatitis, liver steatosis, inflammation, and fibrosis compared to SWE alone. For detection of liver steatosis grades 0 vs ≥ 1, ≤ 1 vs ≥ 2, ≤ 2 vs 3, respectively, AUCs increased from 0.70, 0.65, and 0.69 to 0.78, 0.78, and 0.75 (p <; 0.001)

Ultrafast quantitative ultrasound and shear wave elastography imaging of in vivo duck fatty livers

Multi-parametric ultrasound imaging is a promising tool for quantification of nonalcoholic fatty liver disease. In this work, a protocol of plane wave quantitative ultrasound (QUS) and shear wave elastography imaging (SWEI), quasi-simultaneously acquired, dedicated to quantification of liver steatosis on in vivo fatty duck liver is presented. Shear wave velocity was estimated to classify stiffness in duck liver tissue. QUS consisted of local attenuation coefficient slope estimated with Spectral Log Difference method, and coherent-to-diffuse signal ratio computed from homodyned-K parametric maps. After 9 days of feeding, US attenuation reached a maximum and coherent-todiffuse signal ratio reached a minimum. Coupled together, QUS and SWEI promise a strong potential in steatosis monitoring of fatty liver tissue, in ducks or humans

A Statistical Model for Contours in Images

In this paper, we describe a statistical model for the gradient vector field of the gray level in images validated by different experiments. Moreover, we present a global constrained Markov model for contours in images that uses this statistical model for the likelihood. Our model is amenable to an Iterative Conditional Estimation (ICE) procedure for the estimation of the parameters; our model also allows segmentation by means of the Simulated Annealing (SA) algorithm, the Iterated Conditional Modes (ICM) algorithm, or the Modes of Posterior Marginals (MPM) Monte Carlo (MC) algorithm. This yields an original unsupervised statistical method for edgedetection, with three variants. The estimation and the segmentation procedures have been tested on a total of 160 images. Those tests indicate that the model and its estimation are valid for applications that require an energy term based on the log-likelihood ratio. Besides edge-detection, our model can be used for semiautomatic extraction of contours, localization of shapes, non-photo-realistic rendering; more generally, it might be useful in various problems that require a statistical likelihood for contours