This study explored how the human cortical folding pattern composed of convex gyri and concave sulci affected single-subject morphological brain networks, which are becoming an important method for studying the human brain connectome. We found that gyri-gyri networks exhibited higher morphological similarity, lower small-world parameters, and lower long-term test-retest reliability than sulci-sulci networks for cortical thickness- and gyrification index-based networks, while opposite patterns were observed for fractal dimension-based networks. Further behavioral association analysis revealed that gyri-gyri networks and connections between gyral and sulcal regions significantly explained inter-individual variance in Cognition and Motor domains for fractal dimension- and sulcal depth-based networks. Finally, the clinical application showed that only sulci-sulci networks exhibited morphological similarity reductions in major depressive disorder for cortical thickness-, fractal dimension-, and gyrification index-based networks. Taken together, these findings provide novel insights into the constraint of the cortical folding pattern to the network organization of the human brain.

• MeSH
• Depressive Disorder, Major pathology   diagnostic imaging   MeSH
• Adult MeSH
• Connectome * MeSH
• Humans MeSH
• Magnetic Resonance Imaging * MeSH
• Young Adult MeSH
• Cerebral Cortex * diagnostic imaging   anatomy & histology   MeSH
• Nerve Net * diagnostic imaging   anatomy & histology   MeSH
• Check Tag
• Adult MeSH
• Humans MeSH
• Young Adult MeSH
• Male MeSH
• Female MeSH
• Publication type
• Journal Article MeSH

In this article, we evaluated the variations of the brain and muscle activations while subjects are exposed to different perturbations to walking and standing balance. Since EEG and EMG signals have complex structures, we utilized the complexity-based analysis. Specifically, we analyzed the fractal dimension and sample entropy of Electroencephalogram (EEG) and Electromyogram (EMG) signals while subjects walked and stood, and received different perturbations in the form of pulling and rotation (via virtual reality). The results showed that the complexity of EEG signals was higher in walking than standing as the result of different perturbations. However, the complexity of EMG signals was higher in standing than walking as the result of different perturbations. Therefore, the alterations in the complexity of EEG and EMG signals are inversely correlated. This analysis could be extended to investigate simultaneous variations of rhythmic patterns of other physiological signals while subjects perform different activities.

• Publication type
• Journal Article MeSH

BACKGROUND: Understanding the underlying architecture of mood regulation in bipolar disorder (BD) is important, as we are starting to conceptualize BD as a more complex disorder than one of recurring manic or depressive episodes. Nonlinear techniques are employed to understand and model the behavior of complex systems. Our aim was to assess the underlying nonlinear properties that account for mood and energy fluctuations in patients with BD; and to compare whether these processes were different in healthy controls (HC) and unaffected first-degree relatives (FDR). We used three different nonlinear techniques: Lyapunov exponent, detrended fluctuation analysis and fractal dimension to assess the underlying behavior of mood and energy fluctuations in all groups; and subsequently to assess whether these arise from different processes in each of these groups. RESULTS: There was a positive, short-term autocorrelation for both mood and energy series in all three groups. In the mood series, the largest Lyapunov exponent was found in HC (1.84), compared to BD (1.63) and FDR (1.71) groups [F (2, 87) = 8.42, p < 0.005]. A post-hoc Tukey test showed that Lyapunov exponent in HC was significantly higher than both the BD (p = 0.003) and FDR groups (p = 0.03). Similarly, in the energy series, the largest Lyapunov exponent was found in HC (1.85), compared to BD (1.76) and FDR (1.67) [F (2, 87) = 11.02; p < 0.005]. There were no significant differences between groups for the detrended fluctuation analysis or fractal dimension. CONCLUSIONS: The underlying nature of mood variability is in keeping with that of a chaotic system, which means that fluctuations are generated by deterministic nonlinear process(es) in HC, BD, and FDR. The value of this complex modeling lies in analyzing the nature of the processes involved in mood regulation. It also suggests that the window for episode prediction in BD will be inevitably short.

• Publication type
• Journal Article MeSH

BACKGROUND AND PURPOSE: A reduction of retinal thickness and an alteration of retinal perfusion have been found in Alzheimer disease (AD). Nowadays, retinal layers and retinal perfusion can be evaluated by means of noninvasive imaging techniques, namely, optical coherence tomography (OCT) and OCT-angiography (OCT-A). Here, we have compared the retinal thickness and the perfusion index, measured by means of OCT and OCT-A, in patients with mild cognitive impairment due to AD (MCI-AD) and in age- and sex-matched cognitively healthy controls. METHODS: Twenty-four MCI-AD patients and 13 control subjects were enrolled. MCI-AD patients underwent lumbar puncture; all of them showed a cerebrospinal fluid (CSF) profile compatible with AD. OCT was used for evaluating retinal volumes and thicknesses, whereas with OCT-A we measured fractal dimension (FD), vascular perfusion density (VPD), and vessel length density (VLD) of superficial capillary plexus (SCP), intermediate capillary plexus (ICP), deep capillary plexus (DCP), and choriocapillaris. The comparisons between groups were made after adjustment for age, diabetes, and hypertension. RESULTS: A significant reduction of SCP-VLD (p = 0.012), ICP-VPD (p = 0.015), ICP-VLD (p = 0.004), DCP-VPD (p = 0.012), and DCP-VLD (p = 0.009) was found in MCI-AD patients compared to controls. Conversely, FD was higher in MCI-AD than in controls (p = 0.044). CSF Aβ42/total tau negatively correlated with FD (r = -0.51, p = 0.010). CONCLUSIONS: OCT-A might have a potential role in detecting new noninvasive biomarkers for early AD detection. Retinal VPD might identify amyloid angiopathy-related chronic injury, and FD could show early vessel recruitment as a compensative mechanism at disease onset. Further studies will be needed to confirm these findings.

• MeSH
• Alzheimer Disease * diagnostic imaging   MeSH
• Biomarkers MeSH
• Fluorescein Angiography MeSH
• Humans MeSH
• Tomography, Optical Coherence * MeSH
• Retinal Vessels diagnostic imaging   MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH

Walking is an everyday activity in our daily life. Because walking affects heart rate variability, in this research, for the first time, we analyzed the coupling among the alterations of the complexity of walking paths and heart rate. We benefited from the fractal theory and sample entropy to evaluate the influence of the complexity of paths on the complexity of heart rate variability (HRV) during walking. We calculated the fractal exponent and sample entropy of the R-R time series for nine participants who walked on four paths with various complexities. The findings showed a strong coupling among the alterations of fractal dimension (an indicator of complexity) of HRV and the walking paths. Besides, the result of the analysis of sample entropy also verified the obtained results from the fractal analysis. In further studies, we can analyze the coupling among the alterations of the complexities of other physiological signals and walking paths.

• Publication type
• Journal Article MeSH

One of the most recent non-invasive technologies to examine the gastrointestinal tract is wireless capsule endoscopy (WCE). As there are thousands of endoscopic images in an 8-15 h long video, an evaluator has to pay constant attention for a relatively long time (60-120 min). Therefore the possibility of the presence of pathological findings in a few images (displayed for evaluation for a few seconds only) brings a significant risk of missing the pathology with all negative consequences for the patient. Hence, manually reviewing a video to identify abnormal images is not only a tedious and time consuming task that overwhelms human attention but also is error prone. In this paper, a method is proposed for the automatic detection of abnormal WCE images. The differential box counting method is used for the extraction of fractal dimension (FD) of WCE images and the random forest based ensemble classifier is used for the identification of abnormal frames. The FD is a well-known technique for extraction of features related to texture, smoothness, and roughness. In this paper, FDs are extracted from pixel-blocks of WCE images and are fed to the classifier for identification of images with abnormalities. To determine a suitable pixel block size for FD feature extraction, various sizes of blocks are considered and are fed into six frequently used classifiers separately, and the block size of 7×7 giving the best performance is empirically determined. Further, the selection of the random forest ensemble classifier is also done using the same empirical study. Performance of the proposed method is evaluated on two datasets containing WCE frames. Results demonstrate that the proposed method outperforms some of the state-of-the-art methods with AUC of 85% and 99% on Dataset-I and Dataset-II respectively.

• MeSH
• Fractals MeSH
• Gastrointestinal Tract MeSH
• Capsule Endoscopy * MeSH
• Humans MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH

Colloid deposition in granular media is relevant to numerous environmental problems. Classic filtration models assume a homogeneous pore space and largely ignore colloid aggregation. However, substantial evidence exists on the ubiquity of aggregation within porous media, suggesting that deposition is enhanced by it. This work studies the deposition process in relation to aggregate size and structure. We demonstrate that aggregation is induced at typical groundwater velocities by comparing the repulsive DLVO force between particle pairs to the hydrodynamic shear force opposing it. Column experiments imaged with high-resolution X-ray computed tomography are used to measure aggregate structure and describe their morphology probability distribution and spatial distribution. Aggregate volume and surface area are found to be power-law distributed, while Feret diameter is exponentially distributed with some flow rate dependencies caused by erosion and restructuring by the fluid shear. Furthermore, size and shape of aggregates are heterogeneous in depth, where a small number of large aggregates control the concentration versus depth profile shape. The range of aggregate fractal dimensions found (2.22-2.42) implies a high potential for restructuring or breaking during transport. Shear-induced aggregation is not currently considered in macroscopic models for particle filtration, yet is critical to consider in the processes that control deposition.

• MeSH
• Filtration * MeSH
• Fractals MeSH
• Colloids * MeSH
• Porosity MeSH
• Particle Size MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH

Coagulation followed by floc separation is a key process for the removal of algal organic matter (AOM) in water treatment. Besides optimizing coagulation parameters, knowledge of the properties of AOM-flocs is essential to maximizing AOM removal. However, the impact of AOM on the floc properties remains unclear. This study investigated how peptides/proteins derived from the cellular organic matter (COM) of the cyanobacterium Microcystis aeruginosa influenced the size, structure, and shape of flocs formed at different shear rates (G). Flocs formed by kaolinite, COM-peptides/proteins and a mixture of the same were studied, and the effect of intermolecular interactions between floc components on floc properties was assessed. The coagulation experiments were performed in a Taylor-Couette reactor, with aluminum (Al) or ferric sulphate (Fe) utilized as coagulants. Image analysis was performed to gauge floc size and obtain data on fractal dimension. It was found that floc properties were affected by the presence of the COM-peptides/proteins and the coagulant used. COM-peptides/proteins increased floc size and porosity and widened floc size distributions. The Fe coagulant produced larger and less compact flocs than Al coagulant. Moreover, the decrease in floc size that occurred in parallel with increase in shear rate was not smooth in progress. A rapid change for the kaolinite-coagulant suspension and two rapid changes for the suspensions containing COM were observed. These were attributed to various intermolecular interactions between floc components participating in coagulation at different G. Based on the results obtained, shear rates suitable for efficient separation of flocs containing COM were suggested.

• MeSH
• Bacterial Proteins MeSH
• Water Purification methods   MeSH
• Flocculation MeSH
• Microcystis * MeSH
• Water Microbiology * MeSH
• Peptides MeSH
• Publication type
• Journal Article MeSH

The microvascular pattern in the histological section, i.e. the point-pattern composed of capillaries perpendicular to the plane of section, contains information about the three-dimensional structure of the capillary network. Histological processing is followed by the shrinkage of tissue of uncertain magnitude. In order to obtain relevant information, the scale-independent analysis is necessary. We used an approach based on the Minkowski cover of measured set. The true fractal dimension of the point pattern is obviously of zero, but the artificial result of the algorithm can be related to the complexity of shape. We fitted the log-log plot by the modified rounded ramp function and the slope of the oblique part was used as the fractal based descriptor. We demonstrated on histological samples of the heart that this fractal-based parameter has the property of scale and rotation invariance.

The microvascular pattern in the histological section, i.e. the point-pattern composed of capillaries perpendicular to the plane of section, contains information about the three-dimensional structure of the capillary network. Histological processing is followed by the shrinkage of tissue of uncertain magnitude. In order to obtain relevant information, the scale-independent analysis is necessary. We used an approach based on the Minkowski cover of measured set. The true fractal dimension of the point pattern is obviously of zero, but the artificial result of the algorithm can be related to the complexity of shape. We fitted the log-log plot by the modified rounded ramp function and the slope of the oblique part was used as the fractal based descriptor. We demonstrated on histological samples of the heart that this fractal-based parameter has the property of scale and rotation invariance.

• MeSH
• Fractals MeSH
• Histological Techniques * MeSH
• Image Interpretation, Computer-Assisted * MeSH
• Humans MeSH
• Pattern Recognition, Automated MeSH
• Check Tag
• Humans MeSH
• Publication type
• Research Support, Non-U.S. Gov't MeSH

In recent years, several computer-aided diagnosis systems emerged for the diagnosis of thyroid gland disorders using ultrasound imaging. These systems based on machine learning algorithms may offer a second opinion to radiologists by evaluating a malignancy risk of thyroid tissue, thus increasing the overall diagnostic accuracy of ultrasound imaging. Although current computer-aided diagnosis systems exhibit promising results, their use in clinical practice is limited. One of the main limitations is that the majority of them use direction-dependent features. Our intention has been to design a computer-aided diagnosis system, which will use only direction-independent features, that is, it will not be dependent on the orientation and the inclination angle of the ultrasound probe when acquiring the image. We have, therefore, applied histogram analysis and segmentation-based fractal texture analysis algorithm, which calculates direction-independent features only. In our study, 40 thyroid nodules (20 malignant and 20 benign) were used to extract several features, such as histogram parameters, fractal dimension, and mean brightness value in different grayscale bands (obtained by 2-threshold binary decomposition). The features were then used in support vector machine and random forests classifiers to differentiate nodules into malignant and benign classes. Using leave-one-out cross-validation method, the overall accuracy was 92.42% for random forests and 94.64% for support vector machine. Results show that both methods are useful in practice; however, support vector machine provides better results for this application. Proposed computer-aided diagnosis system can provide support to radiologists in their current diagnosis of thyroid nodules, whereby it can optimize the overall accuracy of ultrasound imaging.

• MeSH
• Algorithms * MeSH
• Diagnosis, Computer-Assisted methods   MeSH
• Diagnosis, Differential MeSH
• Image Interpretation, Computer-Assisted methods   MeSH
• Middle Aged MeSH
• Humans MeSH
• Thyroid Gland diagnostic imaging   pathology   MeSH
• Support Vector Machine MeSH
• Ultrasonography methods   MeSH
• Thyroid Nodule classification   diagnostic imaging   pathology   MeSH
• Check Tag
• Middle Aged MeSH
• Humans MeSH
• Male MeSH
• Female MeSH
• Publication type
• Journal Article MeSH