Abstract 18 F‐Fluorodeoxyglucose positron emission tomography ( F‐FDG PET) is widely employed to reveal metabolic abnormalities linked Parkinson's disease (PD) at a systemic level. However, the individual connectome details with PD based on PET remain largely unknown. To alleviate this issue, we derived novel brain network estimation method for connectome, that is, Jensen‐Shannon Divergence Similarity Estimation (JSSE). Further, intergroup difference between individual's and its global/local...

Automatic optical-to-synthetic aperture radar (SAR) image matching is still a challenging task due to the existence of severe nonlinear radiometric differences between images and presence strong speckles in SAR images. To address this problem, we propose novel feature descriptor called rank-based local self-similarity (RLSS) for optical-to-SAR template matching. The RLSS an improved version (LSS) descriptor, inspired by Spearman's rank correlation coefficient statistics. It can describe...

Abstract The early diagnosis of autism spectrum disorder (ASD) has been extensively facilitated through the utilization resting-state fMRI (rs-fMRI). With rs-fMRI, functional brain network (FBN) gained much attention in diagnosing ASD. As a promising strategy, graph convolutional networks (GCN) provide an attractive approach to simultaneously extract FBN features and facilitate ASD identification, thus replacing manual feature extraction from FBN. Previous GCN studies primarily emphasized...

Subjective cognitive decline (SCD) is considered the earliest preclinical stage of Alzheimer's disease (AD) that precedes mild impairment (MCI). Effective and accurate diagnosis SCD crucial for early detection timely intervention in AD. In this study, brain functional connectome (i.e., connections graph theory metrics) based on resting-state magnetic resonance imaging (rs-fMRI) provided multiple information about networks has been used to distinguish individuals with from normal controls...

Abstract Functional connectome has revealed remarkable potential in the diagnosis of neurological disorders, e.g. autism spectrum disorder. However, existing studies have primarily focused on a single connectivity pattern, such as full correlation, partial or causality. Such an approach fails discovering complementary topology information FCNs at different connection patterns, resulting lower diagnostic performance. Consequently, toward accurate disorder diagnosis, straightforward ambition...

Mild cognitive impairment (MCI) is generally considered to be a key indicator for predicting the early progression of Alzheimer's disease (AD). Currently, brain connection (BC) estimated by fMRI data has been validated an effective diagnostic biomarker MCI. Existing studies mainly focused on single pattern neuro-disease diagnosis. Thus, such approaches are commonly insufficient reveal underlying changes between groups MCI patients and normal controls (NCs), thereby limiting their...

We aimed to use an individual metabolic connectome method, the Jensen-Shannon Divergence Similarity Estimation (JSSE), characterize aberrant connectivity patterns and topological alterations of individual-level brain predict long-term surgical outcomes in temporal lobe epilepsy (TLE).

The functional connectivity network (FCN) has been used to achieve several remarkable advancements in the diagnosis of neuro-degenerative disorders. Therefore, it is imperative accurately estimate biologically meaningful FCNs. Several efforts have dedicated this purpose by encoding biological priors. However, owing high complexity human brain, estimation an 'ideal' FCN remains open problem. To best our knowledge, almost all existing studies lack integration domain expert which limits their...

Functional connectivity network (FCN) analysis is an effective technique for modeling human brain patterns and diagnosing neurological disorders such as Alzheimer's disease (AD) its early stage, Mild Cognitive Impairment. However, accurately estimating biologically meaningful discriminative FCNs remains challenging due to the poor quality of functional magnetic resonance imaging (fMRI) data our limited understanding brain. Inspired by inter-similarity nature FCNs, similar regions interest...

Functional brain network (FBN) provides an effective biomarker for understanding activation patterns and a diagnostic criterion neurodegenerative diseases detections. Unfortunately, it remains challenges to estimate the biologically meaningful or discriminative FBNs accurately, because of poor quality functional magnetic resonance imaging data our limited human brain. In this study, novel FBN estimation model based on group similarity prior was proposed. particular, we extended tensor form...

Subjective cognitive decline (SCD) was considered to be the preclinical stage of Alzheimer's disease (AD). However, less is known about altered rich-club organizations morphological networks in individuals with SCD. This study included 53 SCD and 54 well-matched healthy controls (HC) from Neuroimaging Initiative (ADNI) database. Individual-level brain were constructed by estimating Jensen-Shannon distance-based similarity distribution regional gray matter volume. Rich-club properties then...

Structural magnetic resonance imaging (sMRI) reveals abnormalities in patients with autism spectrum syndrome (ASD). Previous connectome studies of ASD have failed to identify the individual neuroanatomical details preschool-age individuals. This paper aims establish an morphological method characterize connectivity patterns and topological alterations individual-level brain their diagnostic value ASD.Brain sMRI data from 24 17 normal controls (NCs) were collected; participants both groups...

2,3,7,8-Tetrachlorodibenzo-p-dioxin (TCDD) induces aberrant release of gonadotropins, FSH, and LH blocks ovulation during induced ovarian follicular development in rats by an unknown mechanism. In the current study, TCDD (0, 8, or 32 microg/kg orally) was administered to immature female Sprague-Dawley rats, synchronous 24 h later with equine chorionic gonadotropin (eCG, 5 IU s.c.). Both doses a significant premature increase serum FSH (P < 0.05) at 12 post-eCG. This surge facilitated...

Background: <TEX>$FOXP3^+$</TEX> regulatory T cells (Tregs) inhibit effector cell functions and are implicated in tumour progression. However, together with microvessel density (MVD) they remain controversial prognostic predictors for renal carcinoma (RCC), potential associations have yet to be determined. The objective of this study was determine the significance Tregs MVD their relationship RCCs. Design: Paraffin-embedded tissues from 62 RCC patients were analysed using...

Objective Autism spectrum disorder (ASD) is a common neurodevelopmental characterized by the development of multiple symptoms, with incidences rapidly increasing worldwide. An important step in early diagnosis ASD to identify informative biomarkers. Currently, use functional brain network (FBN) deemed for extracting data on imaging Unfortunately, most existing studies have reported utilization information from connection train classifier; such an approach ignores topological and, turn,...