Multiscale color gradient for image segmentation

This paper presents a new gradient model for video color images. These multispectral images have the characteristic, either for the transmission or for storage, to present a reduced bandwidth of color components compared to that of luminosity. The use of traditional methods of determination of the multispectral gradient amplifies the noise from the color components. We adapt the vector gradient from Lee and Cok [22], and introduce the computation of the partial derivatives at different scales according to the resolution of each component. We show that a weight is necessary between the derivatives of color and luminosity components to obtain the multiscale color gradient (MCG). The application of the MCG on microscopic color images illustrates the advantages of our method. The contribution of the MCG is shown with results of edge detection from the gradient image. Finally, segmentation by active contours of crystals in microscopic images of cement clinker (industrial application) is realized using the MCG image.Cet article présente une nouvelle méthode de calcul du gradient d'une image couleur de type vidéo. Ces images multispectrales ont la particularité, soit pour la transmission soit pour le stockage, de présenter une bande passante réduite des composantes couleur par rapport à celle de la luminosité. L'utilisation des méthodes classiques de calcul du gradient multispectral amplifie le bruit présent dans les composantes couleur. Nous reprenons le gradient vectoriel de Lee et Cok [22] en introduisant le calcul des dérivées partielles à une échelle différente suivant la composante traitée. Nous montrons qu'une pondération est nécessaire entre les dérivées des composantes couleur et celle de la composante luminosité pour obtenir le gradient couleur multiéchelle (GCM). La mise en oeuvre du GCM sur des images microscopiques couleur illustre les avantages de notre méthode. L'apport du GCM est montré avec des résultats de détection de contour effectuée sur l'image gradient. Enfin, une segmentation par contours actifs des cristaux de clinker de ciment (application industrielle) est également mise en oeuvre à partir de l'image gradient issu du GCM

Sex-Dependent Influences of Obesity on Cerebral White Matter Investigated by Diffusion-Tensor Imaging

Several studies have shown that obesity is associated with changes in human brain function and structure. Since women are more susceptible to obesity than men, it seems plausible that neural correlates may also be different. However, this has not been demonstrated so far. To address this issue, we systematically investigated the brain's white matter (WM) structure in 23 lean to obese women (mean age 25.5 y, std 5.1 y; mean body mass index (BMI) 29.5 kg/m(2), std 7.3 kg/m(2)) and 26 lean to obese men (mean age 27.1 y, std 5.0 y; mean BMI 28.8 kg/m(2), std 6.8 kg/m(2)) with diffusion-weighted magnetic resonance imaging (MRI). There was no significant age (p > 0.2) or BMI (p > 0.7) difference between female and male participants. Using tract-based spatial statistics, we correlated several diffusion parameters including the apparent diffusion coefficient, fractional anisotropy (FA), as well as axial (lambda(parallel to)) and radial diffusivity (lambda(perpendicular to)) with BMI and serum leptin levels. In female and male subjects, the putative axon marker lambda(parallel to) was consistently reduced throughout the corpus callosum, particularly in the splenium (r = -0.62, p < 0.005). This suggests that obesity may be associated with axonal degeneration. Only in women, the putative myelin marker lambda(perpendicular to) significantly increased with increasing BMI (r = 0.57, p < 0.005) and serum leptin levels (r = 0.62, p < 0.005) predominantly in the genu of the corpus callosum, suggesting additional myelin degeneration. Comparable structural changes were reported for the aging brain, which may point to accelerated aging of WM structure in obese subjects. In conclusion, we demonstrate structural WM changes related to an elevated body weight, but with differences between men and women. Future studies on obesity-related functional and structural brain changes should therefore account for sex-related differences

Spatial variation of PM2.5, PM10, PM2.5 absorbance and PMcoarse concentrations between and within 20 European study areas and the relationship with NO2 - Results of the ESCAPE project

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Connectivity-based parcellation of the human frontal polar cortex

The frontal pole corresponds to Brodmann area (BA) 10, the largest single architectonic area in the human frontal lobe. Generally, BA10 is thought to contain two or three subregions that subserve broad functions such as multitasking, social cognition, attention, and episodic memory. However, there is a substantial debate about the functional and structural heterogeneity of this large frontal region. Previous connectivity-based parcellation studies have identified two or three subregions in the human frontal pole. Here, we used diffusion tensor imaging to assess structural connectivity of BA10 in 35 healthy subjects and delineated subregions based on this connectivity. This allowed us to determine the correspondence of structurally based subregions with the scheme previously defined functionally. Three subregions could be defined in each subject. However, these three subregions were not spatially consistent between subjects. Therefore, we accepted a solution with two subregions that encompassed the lateral and medial frontal pole. We then examined resting-state functional connectivity of the two subregions and found significant differences between their connectivities. The medial cluster was connected to nodes of the default-mode network, which is implicated in internally focused, self-related thought, and social cognition. The lateral cluster was connected to nodes of the executive control network, associated with directed attention and working memory. These findings support the concept that there are two major anatomical subregions of the frontal pole related to differences in functional connectivity

Broca's Region: Novel Organizational Principles and Multiple Receptor Mapping

A novel map of Broca's language region is proposed based on transmitter receptor distributions as functionally relevant molecular markers. It sheds new light on the relation between anatomy and functional segregation

Maturation of the Language Network: From Inter- to Intrahemispheric Connectivities

Language development must go hand-in-hand with brain maturation. Little is known about how the brain develops to serve language processing, in particular, the processing of complex syntax, a capacity unique to humans. Behavioral reports indicate that the ability to process complex syntax is not yet adult-like by the age of seven years. Here, we apply a novel method to demonstrate that the basic neural basis of language, as revealed by low frequency fluctuation stemming from functional MRI data, differs between six-year-old children and adults in crucial aspects. Although the classical language regions are actively in place by the age of six, the functional connectivity between these regions clearly is not. In contrast to adults who show strong connectivities between frontal and temporal language regions within the left hemisphere, children's default language network is characterized by a strong functional interhemispheric connectivity, mainly between the superior temporal regions. These data indicate a functional reorganization of the neural network underlying language development towards a system that allows a close interplay between frontal and temporal regions within the left hemisphere

Hemispheric Asymmetry in White Matter Connectivity of the Temporoparietal Junction with the Insula and Prefrontal Cortex

The temporoparietal junction (TPJ) is a key node in the brain's ventral attention network (VAN) that is involved in spatial awareness and detection of salient sensory stimuli, including pain. The anatomical basis of this network's right-lateralized organization is poorly understood. Here we used diffusion-weighted MRI and probabilistic tractography to compare the strength of white matter connections emanating from the right versus left TPJ to target regions in both hemispheres. Symmetry of structural connectivity was evaluated for connections between TPJ and target regions that are key cortical nodes in the right VAN (insula and inferior frontal gyrus) as well as target regions that are involved in salience and/or pain (putamen, cingulate cortex, thalamus). We found a rightward asymmetry in connectivity strength between the TPJ and insula in healthy human subjects who were scanned with two different sets of diffusion-weighted MRI acquisition parameters. This rightward asymmetry in TPJ-insula connectivity was stronger in females than in males. There was also a leftward asymmetry in connectivity strength between the TPJ and inferior frontal gyrus, consistent with previously described lateralization of language pathways. The rightward lateralization of the pathway between the TPJ and insula supports previous findings on the roles of these regions in stimulus-driven attention, sensory awareness, interoception and pain. The findings also have implications for our understanding of acute and chronic pains and stroke-induced spatial hemineglect

Lewis Base Mediated β-Elimination and Lewis Acid Mediated Insertion Reactions of Disilazido Zirconium Compounds

The reactivity of a series of disilazido zirconocene complexes is dominated by the migration of anionic groups (hydrogen, alkyl, halide, OTf) between the zirconium and silicon centers. The direction of these migrations is controlled by the addition of two-electron donors (Lewis bases) or two-electron acceptors (Lewis acids). The cationic nonclassical [Cp2ZrN(SiHMe2)2]+ ([2]+) is prepared from Cp2Zr{N(SiHMe2)2}H (1) and B(C6F5)3 or [Ph3C][B(C6F5)4], while reactions of B(C6F5)3 and Cp2Zr{N(SiHMe2)2}R (R = Me (3), Et (5), n-C3H7 (7), CH═CHSiMe3 (9)) provide a mixture of [2]+ and [Cp2ZrN(SiHMe2)(SiRMe2)]+. The latter products are formed through B(C6F5)3 abstraction of a β-H and R group migration from Zr to the β-Si center. Related β-hydrogen abstraction and X group migration reactions are observed for Cp2Zr{N(SiHMe2)2}X (X = OTf (11), Cl (13), OMe (15), O-i-C3H7 (16)). Alternatively, addition of DMAP (DMAP = 4-(dimethylamino)pyridine) to [2]+ results in coordination to a Si center and hydrogen migration to zirconium, giving the cationic complex [Cp2Zr{N(SiHMe2)(SiMe2DMAP)}H]+ ([19]+). Related hydrogen migration occurs from [Cp2ZrN(SiHMe2)(SiMe2OCHMe2)]+ ([18]+) to give [Cp2Zr{N(SiMe2DMAP)(SiMe2OCHMe2)}H]+ ([22]+), whereas X group migration is observed upon addition of DMAP to [Cp2ZrN(SiHMe2)(SiMe2X)]+ (X = OTf ([12]+), Cl ([14]+)) to give [Cp2Zr{N(SiHMe2)(SiMe2DMAP)}X]+ (X = OTf ([26]+), Cl ([20]+)). The species involved in these transformations are described by resonance structures that suggest β-elimination. Notably, such pathways are previously unknown in early metal amide chemistry. Finally, these migrations facilitate direct Si–H addition to carbonyls, which is proposed to occur through a pathway that previously had been reserved for later transition metal compounds

Building connectomes using diffusion MRI: why, how and but

Why has diffusion MRI become a principal modality for mapping connectomes in vivo? How do different image acquisition parameters, fiber tracking algorithms and other methodological choices affect connectome estimation? What are the main factors that dictate the success and failure of connectome reconstruction? These are some of the key questions that we aim to address in this review. We provide an overview of the key methods that can be used to estimate the nodes and edges of macroscale connectomes, and we discuss open problems and inherent limitations. We argue that diffusion MRI-based connectome mapping methods are still in their infancy and caution against blind application of deep white matter tractography due to the challenges inherent to connectome reconstruction. We review a number of studies that provide evidence of useful microstructural and network properties that can be extracted in various independent and biologically-relevant contexts. Finally, we highlight some of the key deficiencies of current macroscale connectome mapping methodologies and motivate future developments