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As the ∊4 allele of apolipoprotein E (APOE4) is proved a high risk factor of Alzheimer's disease (AD), numerous studies have used modalities of neuroimaging data to investigate the alterations of brain caused by APOE4. A recent study has shown that APOE4-related pathological changes of cortical networks during rest exist in APOE4 carriers. However, the interrelationship among the resting intrinsic...
Mild cognitive impairment (MCI) is a transition stage between normal aging and dementia. Brain network has been proven to occupy an important role in the study of differences in Alzheimer's disease (AD) and MCI. However, there is little knowledge about individual metabolic network abnormities which might be sensitive features in the prediction of MCI progression. In this paper, we constructed the...
Nonlinear system identification has always been a hot and difficult problem in the field of identification research. In this paper, a modified shuffled frog leaping algorithm is proposed for the typical nonlinear Hammerstein model. The proposed method converted the parameter identification problem in nonlinear system into a function optimization problem in the parameter space. Specifically, the learning...
This paper presents a new contrast enhancement method using Histogram Equalization named Dualistc Sub-Image and Non-parametric Modified Histogram Equalization (DSINMHE). Our proposed method consists of three steps: (i) The original image is segmented into two sub-images by the median value of the image. (ii) Then we use the histogram modification technique to maximize entropy and control over enhancement...
This paper presents a new image enhancement method using histogram equalization called Bi-Histogram Equalization with Non-parametric Modified Technology (BHENMT). Our proposed method consists of three steps: (i) The input original histogram is divided into two parts using the Otsu method. (ii) Then the histogram modification technique is used to control over enhancement and maximize entropy. (iii)...
The rapid development of neuroimaging technology and brain network analysis methodologies have promoted the research of Alzheimer's disease (AD). Recently, studies on brain networks reported that AD patients showed abnormal connectivity alterations and disrupted coordinated organizations compared with normal controls (NC). However, much less knowledge is about the abnormalities of metabolic network...
Recent studies suggested that cognitive impairments and memory difficulties in cancer survivors were associated with topology changes of brain network, particularly in terms of the functional and structural abnormalities. However, little is known about the modular reconfiguration of metabolic brain network among this population. In this study, we recruited 78 patients with pre-treatment cancer and...
The hazardous materials (Hazmat) transportation routing is of great importance for transport safety. This paper presents a routing approach for Hazmat transportation, namely fuzzy analytic hierarchy process (fuzzy AHP) based on historical traffic data. Firstly, we use historical traffic data to preplan the candidate routes. Then we determine the best route by combining AHP with fuzzy comprehensive...
In the paper, we propose a histogram equalization-based image enhancement method named Brightness Preserving and Contrast Limited Bi-histogram Equalization (BPCLBHE). Our method includes three steps: (i) First, we use the average intensity value of the image to divide the input original image into two sub-images. (ii) Second, the histogram clipping approach is used to control enhancement rate. (iii)...
In this paper, we propose a novel method that can detect fingertips as well as recognize hand gestures. Firstly, we collect the hand curves with a Kinect sensor. Secondly, we detect fingertips based on the discrete curve evolution. Thirdly, we recognize hand gestures using evolved curves partitioned at the detected fingertips. Experimental results show that our method performs well in both fingertips...
Recently, investigating boundary prior to aid other low-level image cues, have gained great attention in salient object detection. Although the salient regions are mostly located in the image center, the inverse might not necessarily be true. In addition, such kind of center-bias assumption is very simple and fragile, especially when salient regions often touch the image boundary or the images are...
In recent years, finger vein recognition has become more attractive due to some obvious advantages, such as: in-vivo recognition, high anti-counterfeiting, high acceptability, and high stability, etc. But for some finger vein image, its vein structure is too simple and the useful information is too less, the conventional recognition method often behave badly for this kind of image. For this kind of...
The paper proposes a novel image enhancement method based on histogram equalization called Quadrants Histogram Equalization with a Clipping Limit (QHECL). The proposed method consists of four steps: (i) The first step is to compute the median value of the input image, which is used to divide the input histogram into two sub histograms. (ii) We calculate the average brightness value of each sub histogram...
This paper presents a new image enhancement method by histogram equalization called Brightness Preserving and Non-parametric Modified Bi-histogram Equalization (BPNMBHE). Our method consists of three steps: (i) The input original image is divided into two sub images using the average intensity value. (ii) We use the histogram modification technique to maximize entropy and control over enhancement...
Recently, many researchers have used graph theory to study the aberrant brain functions in mental disorders. However, the characteristics of the brain functional network in attention deficit hyperactivity disorder (ADHD) are still largely unexplored. In this study, blood oxygen level-dependence (BOLD) functional magnetic resonance images (fMRI) were employed to construct brain functional networks...
The problem of learning conditional preference networks (CP-nets) from a set of examples has received great attention recently. However, because of the randomicity of the users' behaviors and the observation errors, there is always some noise making the examples inconsistent, namely, there exists at least one outcome preferred over itself (by transferring) in examples. Existing CP-nets learning methods...
Imaging cerebral glucose metabolism with positron emission tomography (PET) has been widely used in studying Alzheimer's disease (AD) and mild cognitive impairment (MCI). In this study, we used fluoro-deoxyglucose (FDG) PET images to investigate reduced glucose metabolism in 90 AD subjects, 90 MCI subjects and 90 healthy elderly normal controls (NC). Compared to NC, the AD showed a significant hypometabolism...
Mild cognitive impairment (MCI) is a brain-function syndrome involving the onset and evolution of cognitive impairments which are not significant enough to interfere with daily activities. In this study, we used resting state functional magnetic resonance imaging (fMRI) to detect the whole brain fractional amplitude of low-frequency fluctuations (fALFF) and functional connectivity in 32 amnestic MCI...
In this study, the amplitude of low frequency (0.01–0.08Hz) fluctuation (ALFF) and functional connections were used to analyze blood oxygen level-dependent (BOLD) functional magnetic resonance imaging (fMRI) data for 57 children with attention deficit hyperactivity disorder (ADHD) and 59 healthy controls (HC) in a resting state. Compared with HC, the ADHD showed significantly altered neural activity...
Detection of salient regions in natural scenes is useful for computer vision applications, such as image segmentation, object recognition, and image retrieval. In this paper, we propose a new bottom-up visual saliency detection method after analyzing the weakness of the frequency tuned saliency detection method. The proposed method uses the YCbCr color space to present the image and computes the Mahalanobis...
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