Fluorescence microendoscopy can potentially be a powerful modality in minimally invasive percutaneous intervention for cancer diagnosis because it has an exceptional ability to provide micron-scale resolution images in tissues inaccessible to traditional microscopy. After targeting the tumor with guidance by macroscopic images such as computed tomorgraphy or magnetic resonance imaging, fluorescence microendoscopy can help select the biopsy spots or perform an on-site molecular imaging diagnosis. However, one challenge of this technique for percutaneous lung intervention is that the respiratory and hemokinesis motion often renders instability of the sequential image visualization and results in inaccurate quantitative measurement. Motion correction on such serial microscopy image sequences is, therefore, an important post-processing step. We propose a nonlinear motion compensation algorithm using a cubature Kalman filter (NMC-CKF) to correct these periodic spatial and intensity changes, and validate the algorithm using preclinical imaging experiments. The algorithm integrates a longitudinal nonlinear system model using the CKF in the serial image registration algorithm for robust estimation of the longitudinal movements. Experiments were carried out using simulated and real microendoscopy videos captured from the CellVizio 660 system in rabbit VX2 cancer intervention. The results show that the NMC-CKF algorithm yields more robust and accurate alignment results.
[Show abstract][Hide abstract] ABSTRACT: In this paper, we present a new nonlinear filter for high-dimensional state estimation, which we have named the cubature Kalman filter (CKF). The heart of the CKF is a spherical-radial cubature rule, which makes it possible to numerically compute multivariate moment integrals encountered in the nonlinear Bayesian filter. Specifically, we derive a third-degree spherical-radial cubature rule that provides a set of cubature points scaling linearly with the state-vector dimension. The CKF may therefore provide a systematic solution for high-dimensional nonlinear filtering problems. The paper also includes the derivation of a square-root version of the CKF for improved numerical stability. The CKF is tested experimentally in two nonlinear state estimation problems. In the first problem, the proposed cubature rule is used to compute the second-order statistics of a nonlinearly transformed Gaussian random variable. The second problem addresses the use of the CKF for tracking a maneuvering aircraft. The results of both experiments demonstrate the improved performance of the CKF over conventional nonlinear filters.
IEEE Transactions on Automatic Control 07/2009; 54(6-54):1254 - 1269. DOI:10.1109/TAC.2009.2019800 · 2.78 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: We applied a novel approach to respiratory waveform analysis--Monotone Signal Segments Analysis (MSSA) on 6-h recordings of respiratory signals in rats. To validate MSSA as a respiratory signal analysis tool we tested it by detecting: breaths and breath-to-breath intervals; respiratory timing and volume modes; and changes in respiratory pattern caused by lesions of monoaminergic systems in rats. MSSA differentiated three respiratory timing (tachypneic, eupneic, bradypneic-apneic), and three volume (artifacts, normovolemic, hypervolemic-sighs) modes. Lesion-induced respiratory pattern modulation was visible as shifts in the distributions of monotone signal segment amplitudes, and of breath-to-breath intervals. Specifically, noradrenergic lesion induced an increase in mean volume (p<or=0.03), with no change of the mean breath-to-breath interval duration (p>or=0.06). MSSA of timing modes detected noradrenergic lesion-induced interdependent changes in the balance of eupneic (decrease; p<or=0.02), and tachypneic (an increase; p<or=0.02) breath intervals with respect to control. In terms of breath durations within each timing mode, there was a tendency toward prolongation of the eupneic (p<or=0.08) and bradypneic-apneic (p<or=0.06) intervals. These results demonstrate that MSSA is sensitive to subtle shifts in respiratory rhythmogenesis not detectable by simple respiratory pattern descriptive statistics. MSSA represents a potentially valuable new tool for investigations of respiratory pattern control.
[Show abstract][Hide abstract] ABSTRACT: The mouse is the preferred model organism for genetic studies of mammalian brain development. MRI has potential for in utero studies of mouse brain development, but has been limited previously by challenges of maximizing image resolution and contrast while minimizing artifacts due to physiological motion. Manganese (Mn)-enhanced MRI (MEMRI) studies have demonstrated central nervous system (CNS) contrast enhancement in mice from the earliest postnatal stages. The purpose of this study was to expand MEMRI to in utero studies of the embryonic CNS in combination with respiratory gating to decrease motion artifacts. We investigated MEMRI-facilitated CNS segmentation and three-dimensional (3D) analysis in wild-type mouse embryos from midgestation, and explored effects of Mn on embryonic survival and image contrast. Motivated by observations that MEMRI provided an effective method for visualization and volumetric analysis of embryonic CNS structures, especially in ventral regions, we used MEMRI to examine Nkx2.1 mutant mice that were previously reported to have ventral forebrain defects. Quantitative MEMRI analysis of Nkx2.1 knockout mice demonstrated volumetric changes in septum (SE) and basal ganglia (BG), as well as alterations in hypothalamic structures. This method may provide an effective means for in utero analysis of CNS phenotypes in a variety of mouse mutants.
Magnetic Resonance in Medicine 06/2008; 59(6):1320-8. DOI:10.1002/mrm.21609 · 3.57 Impact Factor
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