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In this paper we propose a Compressed Sensing-based image acquisition and recovery method that combines Fourier magnitude measurements and Fourier phase estimation for sequential microscopy image acquisition. The main idea is to combine sequential Optical Fourier Transform (OTF) magnitude measurements with Fourier phase estimation from complete keyframes acquisition. For images with homogeneous objects...
The presence of non-coherent blood speckle patterns makes the assessment of lumen size in intravascular ultrasound (IVUS) images a challenging problem, especially for images acquired with recent high frequency transducers. In this paper, we present a robust three-dimensional (3D) feature extraction algorithm based on the expansion of IVUS cross-sectional images and pullback directions onto an orthonormal...
Dynamic cardiac metrics, including myocardial strains and displacements, provide a quantitative approach to evaluate cardiac function. However, in current clinical diagnosis, largely 2D strain measures are used despite that cardiac motions are complex 3D volumes over time. Recent advances in 4D ultrasound enable the capability to capture such complex motion in a single image data set. In our previous...
In fluorescence microscopy the noise level and the photobleaching are cross-dependent problems since reducing exposure time to reduce photobleaching degrades image quality while increasing noise level. These two problems cannot be solved independently as a post-processing task, hence the most important contribution in this work is to a-priori denoise and reduce photobleaching simultaneously by using...
In this paper, we present and study two local features for the tracking of vascular structures on 3D angiograms. The first one, Flux, measures the inward gradient flux through circular cross-sections. The second one, MFlux, introduces a non-linear penalization of asymmetric flux contributions to reduce false positive responses. Through a series of experiments on synthetic and real cardiac CT data,...
Recent improvements of fetal MRI acquisitions now allow three-dimensional segmentation of fetal structures, to extract bio-metrical measures for pregnancy follow-up. Automation of the segmentation process remains a difficult challenge, given the complexity of the fetal organs and their spatial organization. As a starting point, we propose in this paper a fully automated segmentation method to localize...
A statistical variational framework is proposed for the fetus and uterus segmentation in ultrasound images. The Rayleigh and exponential distributions are used to model the pixel intensity. An energy is derived to perform an optimal partition of the 3D data into two classes corresponding to these two distributions, in a Bayesian MAP framework. Some numerical difficulties are raised by the combination...
An automated, level-set based, segmentation framework is proposed in this work for computation of tumoral volumes on mice brain bearing gliomal tumors. Tl and T2 weighted MRI images were acquired to monitor tumor growth, at different time points. We developed an original multi-phase and multi-channel segmentation method, based on the level set framework of Chan and Vese, to facilitate the estimation...
Four-dimensional ultrasound based on matrix phased array transducers can capture the complex 4D cardiac motion in a complete and real-time fashion. However, the large amount of information residing in 4D ultrasound scans and novel applications under interventional settings pose a big challenge in efficiency for workflow and computer-aided diagnostic algorithms such as segmentation. In this context,...
We propose a new Bayesian, stochastic tracking algorithm for the segmentation of blood vessels from 3D medical image data. Inspired by the recent developments in particle filtering, it relies on a constrained, medial-based geometric model and on an original sampling scheme for the selection of tracking hypotheses. A key property of this new sampling scheme is the ability to take into account a distribution...
Detection of millimetric brain tumor growth patterns on longitudinal MRI acquisitions remains challenging in clinical practice. A simple difference map of two longitudinal co-registered MRI volumes fails to detect specific tumor evolution, due to non-linear contrast change between the two data sets. This paper presents a novel method for detection and quantification of tumor evolution in longitudinal...
Quantitative analysis of cardiac motion is of great clinical interest in assessment of ventricular function. Ultrasound imaging, especially matrix transducers acquiring real-time three dimensional data, provide valuable information, from which quantitative measures of cardiac function can be extracted via optical flow computation. Such analysis requires tracking of the image brightness patterns with...
Although numerous methods to segment brain MRI for extraction of white matter, gray matter and cerebrospinal fluid (CSF) have been proposed for the past two decades, little work has been done to evaluate and compare the performance of different segmentation methods on real clinical data sets, especially for CSF. This study focuses on the comparison of the four following methods for segmentation of...
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