3D global and regional patterns of human fetal subplate growth determined in utero

The waiting period of subplate evolution is a critical phase for the proper formation of neural connections in the brain. During this time, which corresponds to 15 to 24 postconceptual weeks (PCW) in the human fetus, thalamocortical and cortico-cortical afferents wait in and are in part guided by molecules embedded in the extracellular matrix of the subplate. Recent advances in fetal MRI techniques now allow us to study the developing brain anatomy in 3D from in utero imaging. We describe a reliable segmentation protocol to delineate the boundaries of the subplate from T2-W MRI. The reliability of the protocol was evaluated in terms of intra-rater reproducibility on a subset of the subjects. We also present the first 3D quantitative analyses of temporal changes in subplate volume, thickness, and contrast from 18 to 24 PCW. Our analysis shows that firstly, global subplate volume increases in proportion with the supratentorial volume; the subplate remained approximately one-third of supratentorial volume. Secondly, we found both global and regional growth in subplate thickness and a linear increase in the median and maximum subplate thickness through the waiting period. Furthermore, we found that posterior regions—specifically the occipital pole, ventral occipito-temporal region, and planum temporale—of the developing brain underwent the most statistically significant increases in subplate thickness. During this period, the thickest region was the developing somatosensory/motor cortex. The subplate growth patterns reported here may be used as a baseline for comparison to abnormal fetal brain development

Efficient quantitative assessment of facial paralysis using iris segmentation and active contour-based key points detection with hybrid classifier

BACKGROUND: Facial palsy or paralysis (FP) is a symptom that loses voluntary muscles movement in one side of the human face, which could be very devastating in the part of the patients. Traditional methods are solely dependent to clinician’s judgment and therefore time consuming and subjective in nature. Hence, a quantitative assessment system becomes apparently invaluable for physicians to begin the rehabilitation process; and to produce a reliable and robust method is challenging and still underway. METHODS: We introduce a novel approach for a quantitative assessment of facial paralysis that tackles classification problem for FP type and degree of severity. Specifically, a novel method of quantitative assessment is presented: an algorithm that extracts the human iris and detects facial landmarks; and a hybrid approach combining the rule-based and machine learning algorithm to analyze and prognosticate facial paralysis using the captured images. A method combining the optimized Daugman’s algorithm and Localized Active Contour (LAC) model is proposed to efficiently extract the iris and facial landmark or key points. To improve the performance of LAC, appropriate parameters of initial evolving curve for facial features’ segmentation are automatically selected. The symmetry score is measured by the ratio between features extracted from the two sides of the face. Hybrid classifiers (i.e. rule-based with regularized logistic regression) were employed for discriminating healthy and unhealthy subjects, FP type classification, and for facial paralysis grading based on House-Brackmann (H-B) scale. RESULTS: Quantitative analysis was performed to evaluate the performance of the proposed approach. Experiments show that the proposed method demonstrates its efficiency. CONCLUSIONS: Facial movement feature extraction on facial images based on iris segmentation and LAC-based key point detection along with a hybrid classifier provides a more efficient way of addressing classification problem on facial palsy type and degree of severity. Combining iris segmentation and key point-based method has several merits that are essential for our real application. Aside from the facial key points, iris segmentation provides significant contribution as it describes the changes of the iris exposure while performing some facial expressions. It reveals the significant difference between the healthy side and the severe palsy side when raising eyebrows with both eyes directed upward, and can model the typical changes in the iris region

Phosphomimetic Modulation of eNOS Improves Myocardial Reperfusion and Mimics Cardiac Postconditioning in Mice

Objective: Myocardial infarction resulting from ischemia-reperfusion injury can be reduced by cardiac postconditioning, in which blood flow is restored intermittently prior to full reperfusion. Although key molecular mechanisms and prosurvival pathways involved in postconditioning have been identified, a direct role for eNOS-derived NO in improving regional myocardial perfusion has not been shown. The objective of this study is to measure, with high temporal and spatial resolution, regional myocardial perfusion during ischemia-reperfusion and postconditioning, in order to determine the contribution of regional blood flow effects of NO to infarct size and protection. Methods and Results: We used myocardial contrast echocardiography to measure regional myocardial blood flow in mice over time. Reperfusion after myocardial ischemia-reperfusion injury is improved by postconditioning, as well as by phosphomimetic eNOS modulation. Knock-in mice expressing a phosphomimetic S1176D form of eNOS showed improved myocardial reperfusion and significantly reduced infarct size. eNOS knock-out mice failed to show cardioprotection from postconditioning. The size of the no-reflow zone following ischemia-reperfusion is substantially reduced by postconditioning and by the phosphomimetic eNOS mutation. Conclusions and Significance: Using myocardial contrast echocardiography, we show that temporal dynamics of regional myocardial perfusion restoration contribute to reduced infarct size after postconditioning. eNOS has direct effects on myocardial blood flow following ischemia-reperfusion, with reduction in the size of the no-reflow zone. These results have important implications for ongoing clinical trials on cardioprotection, because the degree of protective benefit may be significantly influenced by the regional hemodynamic effects of eNOS-derived NO.American Heart Association (Predoctoral Fellowship)National Institutes of Health (U.S.) (R01 NS33335)National Institutes of Health (U.S.) (R01 HL57818

Image Sharpening via Sobolev Gradient Flows

© 2010 Society for Industrial and Applied MathematicsDOI:10.1137/090771260Motivated by some recent work in active contour applications, we study the use of Sobolev gradients for PDE-based image diffusion and sharpening. We begin by studying, for the case of isotropic diffusion, the gradient descent/ascent equation obtained by modifying the usual metric on the space of images, which is the L2 metric, to a Sobolev metric. We present existence and uniqueness results for the Sobolev isotropic diffusion, derive a number of maximum principles, and show that the differential equations are stable and well-posed both in the forward and backward directions. This allows us to apply the Sobolev flow in the backward direction for sharpening. Favorable comparisons to the well-known shock filter for sharpening are demonstrated. Finally, we continue to exploit this same well-posed behavior both forward and backward in order to formulate new constrained gradient flows on higher order energy functionals which preserve the first order energy of the original image for interesting combined smoothing and sharpening effects