Atlas-based segmentation of pathological MR brain images using a model of lesion growth.

We propose a method for brain atlas deformation in the presence of large space-occupying tumors, based on an a priori model of lesion growth that assumes radial expansion of the lesion from its starting point. Our approach involves three steps. First, an affine registration brings the atlas and the patient into global correspondence. Then, the seeding of a synthetic tumor into the brain atlas provides a template for the lesion. The last step is the deformation of the seeded atlas, combining a method derived from optical flow principles and a model of lesion growth. Results show that a good registration is performed and that the method can be applied to automatic segmentation of structures and substructures in brains with gross deformation, with important medical applications in neurosurgery, radiosurgery, and radiotherapy.

A surface-based approach to quantify local cortical gyrification.

The high complexity of cortical convolutions in humans is very challenging both for engineers to measure and compare it, and for biologists and physicians to understand it. In this paper, we propose a surface-based method for the quantification of cortical gyrification. Our method uses accurate 3-D cortical reconstruction and computes local measurements of gyrification at thousands of points over the whole cortical surface. The potential of our method to identify and localize precisely gyral abnormalities is illustrated by a clinical study on a group of children affected by 22q11 Deletion Syndrome, compared to control individuals.

Decoding stimulus-related information from single-trial EEG responses based on voltage topographies

Neuroimaging studies typically compare experimental conditions using average brain responses, thereby overlooking the stimulus-related information conveyed by distributed spatio-temporal patterns of single-trial responses. Here, we take advantage of this rich information at a single-trial level to decode stimulus-related signals in two event-related potential (ERP) studies. Our method models the statistical distribution of the voltage topographies with a Gaussian Mixture Model (GMM), which reduces the dataset to a number of representative voltage topographies. The degree of presence of these topographies across trials at specific latencies is then used to classify experimental conditions. We tested the algorithm using a cross-validation procedure in two independent EEG datasets. In the first ERP study, we classified left- versus right-hemifield checkerboard stimuli for upper and lower visual hemifields. In a second ERP study, when functional differences cannot be assumed, we classified initial versus repeated presentations of visual objects. With minimal a priori information, the GMM model provides neurophysiologically interpretable features - vis à vis voltage topographies - as well as dynamic information about brain function. This method can in principle be applied to any ERP dataset testing the functional relevance of specific time periods for stimulus processing, the predictability of subject's behavior and cognitive states, and the discrimination between healthy and clinical populations.

Experimental cerebral malaria develops independently of caspase recruitment domain-containing protein 9 signaling.

The outcome of infection depends on multiple layers of immune regulation, with innate immunity playing a decisive role in shaping protection or pathogenic sequelae of acquired immunity. The contribution of pattern recognition receptors and adaptor molecules in immunity to malaria remains poorly understood. Here, we interrogate the role of the caspase recruitment domain-containing protein 9 (CARD9) signaling pathway in the development of experimental cerebral malaria (ECM) using the murine Plasmodium berghei ANKA infection model. CARD9 expression was upregulated in the brains of infected wild-type (WT) mice, suggesting a potential role for this pathway in ECM pathogenesis. However, P. berghei ANKA-infected Card9(-/-) mice succumbed to neurological signs and presented with disrupted blood-brain barriers similar to WT mice. Furthermore, consistent with the immunological features associated with ECM in WT mice, Card9(-/-) mice revealed (i) elevated levels of proinflammatory responses, (ii) high frequencies of activated T cells, and (iii) CD8(+) T cell arrest in the cerebral microvasculature. We conclude that ECM develops independently of the CARD9 signaling pathway.

New multiple matched filter: design and experimental realization

A method of making a multiple matched filter which allows the recognition of different characters in successive planes in simple conditions is proposed. The generation of the filter is based on recording on the same plate the Fourier transforms of the different patterns to be recognized, each of which is affected by different spherical phase factors because the patterns have been placed at different distances from the lens. This is proved by means of experiments with a triple filter which allows satisfactory recognition of three characters.

Histone deacetylase inhibitors impair innate immune responses to Toll-like receptor agonists and to infection.

Regulated by histone acetyltransferases and deacetylases (HDACs), histone acetylation is a key epigenetic mechanism controlling chromatin structure, DNA accessibility, and gene expression. HDAC inhibitors induce growth arrest, differentiation, and apoptosis of tumor cells and are used as anticancer agents. Here we describe the effects of HDAC inhibitors on microbial sensing by macrophages and dendritic cells in vitro and host defenses against infection in vivo. HDAC inhibitors down-regulated the expression of numerous host defense genes, including pattern recognition receptors, kinases, transcription regulators, cytokines, chemokines, growth factors, and costimulatory molecules as assessed by genome-wide microarray analyses or innate immune responses of macrophages and dendritic cells stimulated with Toll-like receptor agonists. HDAC inhibitors induced the expression of Mi-2β and enhanced the DNA-binding activity of the Mi-2/NuRD complex that acts as a transcriptional repressor of macrophage cytokine production. In vivo, HDAC inhibitors increased the susceptibility to bacterial and fungal infections but conferred protection against toxic and septic shock. Thus, these data identify an essential role for HDAC inhibitors in the regulation of the expression of innate immune genes and host defenses against microbial pathogens.

On-axis joint transform correlation based on a four-level power spectrum

We propose a method to obtain a single centered correlation with use of a joint transform correlator. We analyze the required setup to carry out the whole process optically, and we also present experimental results.

Phase-only filters codified with Burckhardt's method

We show that Burckhardt's method is available to codify phase-only filters with amplitude-only variations. Correlation experimental results are given.

Effects of thresholding level variation in fringe binarization of multiobject joint transform correlation

It is possible to improve the fringe binarization method of joint transform correlation by choosing a suitable threshold level.

Controlled-intensity detection peaks in a binary joint transform correlator

In multiobject pattern recognition the height of the correlation peaks should be controlled when the power spectrum of ajoint transform correlator is binarized. In this paper a method to predetermine the value of detection peaks is demonstrated. The technique is based on a frequency-variant threshold in order to remove the intraclass terms and on a suitable factor to normalize the binary joint power spectrum. Digital simulations and experimental hybrid implementation of this method were carried out.

Diffraction theory of optimized low-resolution Fresnel encoded lenses

A mathematical model describing the behavior of low-resolution Fresnel encoded lenses (LRFEL's) encoded in any low-resolution device (e.g., a spatial light modulator) has recently been developed. From this model, an LRFEL with a short focal length was optimized by our imposing the maximum intensity of light onto the optical axis. With this model, analytical expressions for the light-amplitude distribution, the diffraction efficiency, and the frequency response of the optimized LRFEL's are derived.

New multiple matched filter: design and experimental realization

A method of making a multiple matched filter which allows the recognition of different characters in successive planes in simple conditions is proposed. The generation of the filter is based on recording on the same plate the Fourier transforms of the different patterns to be recognized, each of which is affected by different spherical phase factors because the patterns have been placed at different distances from the lens. This is proved by means of experiments with a triple filter which allows satisfactory recognition of three characters.

Nonlinear filtering in object and Fourier space in a joint transform optical correlator: comparison and experimental realization

The use of different kinds of nonlinear filtering in a joint transform correlator are studied and compared. The study is divided into two parts, one corresponding to object space and the second to the Fourier domain of the joint power spectrum. In the first part, phase and inverse filters are computed; their inverse Fourier transforms are also computed, thereby becoming the reference in the object space. In the Fourier space, the binarization of the power spectrum is realized and compared with a new procedure for removing the spatial envelope. All cases are simulated and experimentally implemented by a compact joint transform correlator.

Computation of arbitrarily constrained synthetic discriminant functions

An algorithm for computing correlation filters based on synthetic discriminant functions that can be displayed on current spatial light modulators is presented. The procedure is nondivergent, computationally feasible, and capable of producing multiple solutions, thus overcoming some of the pitfalls of previous methods.

Correlation postprocessing-based method for the detection of de focused images

We present a method to detect patterns in defocused scenes by means of a joint transform correlator. We describe analytically the correlation plane, and we also introduce an original procedure to recognize the target by postprocessing the correlation plane. The performance of the methodology when the defocused images are corrupted by additive noise is also considered.