Unraveling the pathophysiology of schizophrenia: insights from structural magnetic resonance imaging studies.

Background: Schizophrenia affects about 1% of the global population. In addition to the complex etiology, linking this illness to genetic, environmental, and neurobiological factors, the dynamic experiences associated with this disease, such as experiences of delusions, hallucinations, disorganized thinking, and abnormal behaviors, limit neurological consensuses regarding mechanisms underlying this disease.

Methods: In this study, we recruited 72 patients with schizophrenia and 74 healthy individuals matched by age and sex to investigate the structural brain changes that may serve as prognostic biomarkers, indicating evidence of neural dysfunction underlying schizophrenia and subsequent cognitive and behavioral deficits.

Repeated Cross-Scale Structure-Induced Feature Fusion Network for 2D Hand Pose Estimation.

Recently, the use of convolutional neural networks for hand pose estimation from RGB images has dramatically improved. However, self-occluded keypoint inference in hand pose estimation is still a challenging task. We argue that these occluded keypoints cannot be readily recognized directly from traditional appearance features, and sufficient contextual information among the keypoints is especially needed to induce feature learning.

Brain Tumor Segmentation Network with Multi-View Ensemble Discrimination and Kernel-Sharing Dilated Convolution.

Accurate segmentation of brain tumors from magnetic resonance 3D images (MRI) is critical for clinical decisions and surgical planning. Radiologists usually separate and analyze brain tumors by combining images of axial, coronal, and sagittal views. However, traditional convolutional neural network (CNN) models tend to use information from only a single view or one by one.

Altered striatal functional connectivity and structural dysconnectivity in individuals with bipolar disorder: A resting state magnetic resonance imaging study.

Objective: Bipolar disorder (BD) is a mood swing illness characterized by episodes ranging from depressive lows to manic highs. Although the specific origin of BD is unknown, genetics, environment, and changes in brain structure and chemistry may all have a role. Through magnetic resonance imaging (MRI) evaluations, this study looked into functional abnormalities involving the striatum between BD group and healthy controls (HC), compared the whole-brain gray matter (GM) morphological patterns between the groups and see whether functional connectivity has its underlying structural basis.

Gray matter, white matter and cerebrospinal fluid abnormalities in Parkinson's disease: A voxel-based morphometry study.

Background: Parkinson's disease (PD) is a chronic neurodegenerative disorder characterized by bradykinesia, tremor, and rigidity among other symptoms. With a 70% cumulative prevalence of dementia in PD, cognitive impairment and neuropsychiatric symptoms are frequent.

Materials And Methods: In this study, we looked at anatomical brain differences between groups of patients and controls.

An Efficient Turbo Decoding and Frequency Domain Turbo Equalization for LTE Based Narrowband Internet of Things (NB-IoT) Systems.

This paper addresses the main crucial aspects of physical (PHY) layer channel coding in uplink NB-IoT systems. In uplink NB-IoT systems, various channel coding algorithms are deployed due to the nature of the adopted Long-Term Evolution (LTE) channel coding which presents a great challenge at the expense of high decoding complexity, power consumption, error floor phenomena, while experiencing performance degradation for short block lengths. For this reason, such a design considerably increases the overall system complexity, which is difficult to implement.