Coupled nonparametric shape priors for segmentation of multiple basal ganglia structures

This paper presents a new method for multiple structure segmentation, using a maximum a posteriori (MAP) estimation framework, based on prior shape densities involving nonparametric multivariate kernel density estimation of multiple shapes. Our method is motivated by the observation that neighboring or coupling structures in medical images generate configurations and co-dependencies which could potentially aid in segmentation if properly exploited. Our technique allows simultaneous segmentation of multiple objects, where highly contrasted, easy-to-segment structures can help improve the segmentation of weakly contrasted objects. We demonstrate the effectiveness of our method on both synthetic images and real magnetic resonance images (MRI) for segmentation of basal ganglia structures

The relationship between epicardial fat thickness and gestational diabetes mellitus

Aim: Gestational diabetes mellitus (GDM) is associated with cardiovascular diseases; however, the relationship between epicardial fat thickness (EFT) and GDM remains unclear. The present study evaluates and compares EFT using transthoracic echocardiography in pregnant women with GDM. Materials and methods: This cross-sectional study included 129 pregnant women in the third trimester: 65 with GDM (GDM group) and 64 with uncomplicated pregnancies (control group). As defined by the World Health Organization, the diagnosis of GDM was based on an abnormal 2-h oral glucose tolerance test (OGTT) results. We used echocardiography to measure EFT in blood samples for all the participants. Results: The postprandial blood glucose level was significantly higher in the GDM group than in the control group (P < 0.001). There were no significant differences in BMI, heart rate, systolic and diastolic blood pressure or lipid parameters between the groups. In the GDM group, isovolumic relaxation time (IVRT) parameters were significantly higher than in the control group. EFT was significantly higher in the GDM group (P < 0.001) and was correlated with postprandial glucose, BMI, age, and heart rate in both the groups. Only postprandial glucose and BMI remained significantly associated with EFT after multiple stepwise regression analysis. Conclusion: Echocardiographically measured EFT was significantly higher in the patients with GDM. The findings show that EFT was strongly correlated with postprandial glucose. © 2014 Nar et al

Volumetric segmentation of multiple basal ganglia structures

We present a new active contour-based, statistical method for simultaneous volumetric segmentation of multiple subcortical structures in the brain. Neighboring anatomical structures in the human brain exhibit co-dependencies which can aid in segmentation, if properly analyzed and modeled. Motivated by this observation, we formulate the segmentation problem as a maximum a posteriori estimation problem, in which we incorporate statistical prior models on the shapes and inter-shape (relative) poses of the structures of interest. This provides a principled mechanism to bring high level information about the shapes and the relationships of anatomical structures into the segmentation problem. For learning the prior densities based on training data, we use a nonparametric multivariate kernel density estimation framework. We combine these priors with data in a variational framework, and develop an active contour-based iterative segmentation algorithm. We test our method on the problem of volumetric segmentation of basal ganglia structures in magnetic resonance (MR) images. We compare our technique with existing methods and demonstrate the improvements it provides in terms of segmentation accuracy

Coupled non-parametric shape and moment-based inter-shape pose priors for multiple basal ganglia structure segmentation

This paper presents a new active contour-based, statistical method for simultaneous volumetric segmentation of multiple subcortical structures in the brain. In biological tissues, such as the human brain, neighboring structures exhibit co-dependencies which can aid in segmentation, if properly analyzed and modeled. Motivated by this observation, we formulate the segmentation problem as a maximum a posteriori estimation problem, in which we incorporate statistical prior models on the shapes and inter-shape (relative) poses of the structures of interest. This provides a principled mechanism to bring high level information about the shapes and the relationships of anatomical structures into the segmentation problem. For learning the prior densities we use a nonparametric multivariate kernel density estimation framework. We combine these priors with data in a variational framework and develop an active contour-based iterative segmentation algorithm. We test our method on the problem of volumetric segmentation of basal ganglia structures in magnetic resonance (MR) images. We present a set of 2D and 3D experiments as well as a quantitative performance analysis. In addition, we perform a comparison to several existent segmentation methods and demonstrate the improvements provided by our approach in terms of segmentation accuracy

Multi-object segmentation using coupled nonparametric shape and relative pose priors

We present a new method for multi-object segmentation in a maximum a posteriori estimation framework. Our method is motivated by the observation that neighboring or coupling objects in images generate configurations and co-dependencies which could potentially aid in segmentation if properly exploited. Our approach employs coupled shape and inter-shape pose priors that are computed using training images in a nonparametric multi-variate kernel density estimation framework. The coupled shape prior is obtained by estimating the joint shape distribution of multiple objects and the inter-shape pose priors are modeled via standard moments. Based on such statistical models, we formulate an optimization problem for segmentation, which we solve by an algorithm based on active contours. Our technique provides significant improvements in the segmentation of weakly contrasted objects in a number of applications. In particular for medical image analysis, we use our method to extract brain Basal Ganglia structures, which are members of a complex multi-object system posing a challenging segmentation problem. We also apply our technique to the problem of handwritten character segmentation. Finally, we use our method to segment cars in urban scenes

Çoklu beyin yapılarının bağlaşık, parametrik olmayan şekil önbilgisi kullanılarak bölütlenmesi = Segmentation of multiple brain structures using coupled nonparametric shape priors

We consider the problem of segmenting multiple brain structures in medical images. Due to the low contrast of medical images and the presence of noise, solution of this problem based only on image data, is rather challenging. Motivated by this observation, we propose an appraoch that incorporates prior information about the shapes of the anatomical structures, as well as about the interaction of neighboring shapes. We construct a statistical framework for the segmentation problem, which captures information about the shapes of coupled anatomical structures through prior probability density functions. We nonparametrically estimate these probability density functions from training shapes. We develop an active contour-based segmentation algorithm that combines image-based data with shape information. We demonstrate the benefits of our approach over existing methods through challenging segmentation scenarios on real magnetic resonance images

Vortioxetine suppresses epileptiform activity and cognition deficits in a chronic PTZ-induced kindling rat model

Objective. This study aimed to examine the effects of vortioxetine, a novel antidepressant, on epileptiform activity in pentylenetetrazole (PTZ)-induced kindling model in rats

Regulation of GSK-3 Activity as A Shared Mechanism in Psychiatric Disorders

Glycogen synthase kinase-3 (GSK-3), a member of the serine/threonine kinase family was first identified as an inhibitor of the metabolic enzyme glycogen synthase and is now accepted as a widely influential enzyme responsible for many intracellular regulatory mechanisms with over 50 known substrates characterized. There are two mammalian GSK-3 isoforms encoded by separate genes: GSK-3 alpha and GSK-3 beta with high structural homology. Both GSK-3 alpha and GSK-3 beta are widely expressed in many tissues with the highest levels in the brain and their functions are generally considered to be indistinguishable. Unlike many other protein kinases, GSK-3 is constitutively dephosphorylated and active in resting cells. Phosphorylation of GSK-3 by other protein kinases such as PKA (Protein kinase A), AKT (Protein kinase B) and PKC (Protein kinase C) inhibits its activity. Today a growing body of evidence strongly suggests that increased GSK-3 activity is involved in the development of schizophrenia and mood disorders such as bipolar disorder, major depression and hyperactivity associated disorders. Thus, inhibition of overactive GSK-3 has become a promising target in the treatment of these psychiatric disorders. Herein we will briefly discuss the underlying mechanisms related to how GSK-3 is thought to participate in such diseases and will give examples of clinically important treatments that have a role in GSK-3 regulation

Three-dimensional palatal morphology and upper arch changes following nonsurgical and surgical maxillary expansion in adults

Objective. The objective of this study was to evaluate the effects of nonsurgical rapid maxillary expansion (RME) and surgically assisted RME (SARME) on palatal morphology and upper arch dimensions using three-dimensional (3D) models in skeletally mature patients. Study Design. Thirty-eight skeletally mature patients with a maxillary transverse deficiency were divided into RME and SARME groups. Nineteen patients in the RME group (mean age, 19.16 +/- 2.25 years) were treated using a full-coverage bonded acrylic splint expander; 19 patients in the SARME group (mean age, 20.38 +/- 3.36) were treated using the banded palatal expansion appli-ance with hyrax screws. The 3D models were obtained before and after expansion. The maxillary dental arch widths, maxillary first molar angulation, palatal area, and palatal volume were calculated on the 3D models. Results. All variables showed statistically significant changes after the retention period (P < .001). The maxillary arch width between first premolars (P < .05), the palatal area (P < .01), and the palatal volume (P < .05) significantly increased in the SARME group compared to the RME group. The maxillary first molar tipping in the RME group was significantly higher than that in the SARME group (P < .01). Conclusions. Although SARME has more positive effects in skeletally mature patients, nonsurgical RME can be considered as an alternative by evaluating surgical risks, periodontal status, and the need for skeletal expansion. (Oral Surg Oral Med Oral Pathol Oral Radiol 2022;134:425-431