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1.
Sci Rep ; 12(1): 13170, 2022 Aug 01.
Artigo em Inglês | MEDLINE | ID: mdl-35915125

RESUMO

The present understanding of the mechanisms responsible for postural deficit in adolescent idiopathic scoliosis (AIS) is still insufficient. This is important because some authors see one of the causes of this disease in the impaired postural control. Moreover, there is a reciprocal link between the level of postural imbalance and the clinical picture of these people. Therefore, we compared the center-of-pressure (COP) indices of 24 patients with AIS to 48 controls (CON) during four 20-s quiet stance trials with eyes open (EO) or closed (EC) and on firm or foam surface. This included sway amplitude, speed, sample entropy and fractal dimension. AIS had poorer postural steadiness only in the most difficult trial. In the remaining trials, AIS did as well as CON, while presenting a greater COP entropy than CON. Thus, the factor that made both groups perform equally could be the increased sway irregularity in AIS, which is often linked to higher automaticity and lower attention involvement in balance control. After changing the surface from hard to foam, puzzling changes in sway fractality were revealed. The patients decreased the fractal dimension in the sagittal plane identically to the CON in the frontal plane. This may suggest some problems with the perception of body axes in patients and reveals a hitherto unknown cause of their balance deficit.


Assuntos
Cifose , Escoliose , Adolescente , Entropia , Feminino , Fractais , Humanos , Equilíbrio Postural
2.
PLoS One ; 17(8): e0268908, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-35917299

RESUMO

We investigate the splitting and incorporation of optical fractal states in one-dimensional photonic quasi-crystals. The aperiodic crystals which are composed of two different dielectrics submit to Cantor sequence. Defects in Cantor crystals can greatly enhance the localization of electric field, which induces the optical fractal effect. The number of optical fractal states increases exponentially with the generation number of Cantor sequence. Moreover, the optical fractal characteristics depend on the incident angle of light, of which the fractal states may split/incorporate by modulating the value of incident angle. This study could be utilized for band-pass filters and reflectors.


Assuntos
Fractais , Fótons , Óptica e Fotônica , Piridazinas
3.
Sensors (Basel) ; 22(13)2022 Jun 30.
Artigo em Inglês | MEDLINE | ID: mdl-35808446

RESUMO

Pavement texture characteristics can reflect early performance decay, skid resistance, and other information. However, most statistical texture indicators cannot express this difference. This study adopts 3D image camera equipment to collect texture data from laboratory asphalt mixture specimens and actual pavement. A pre-processing method was carried out, including data standardisation, slope correction, missing value and outlier processing, and envelope processing. Then the texture data were calculated based on texture separation, texture power spectrum, grey level co-occurrence matrix, and fractal theory to acquire six leading texture indicators and eight extended indicators. The Pearson correlation coefficient was used to analyse the correlation of different texture indicators. The distinction vector based on the information entropy is calculated to analyse the distinction of the indicators. High correlations between ENE (energy) and ENT (entropy), ENT and D (Minkowski dimension) were found. The CON (contrast) has low correlations with HT (macro-texture power spectrum area), ENT and D. However, the differentiation of ENE and HT is more prominent, and the differentiation of the CON is smaller. ENE, ENT, CON and D indicators based on macro-texture and the corresponding original texture have strong linear correlations. However, the microtexture indicators are not linearly correlated with the corresponding original texture indicators. D, WT (micro-texture power spectrum area) and ENT exhibit high degrees of numerical concentration for the same road sections and may be more statistically helpful in distinguishing the characteristics of the pavement performance decay of the road sections.


Assuntos
Processamento de Imagem Assistida por Computador , Imageamento Tridimensional , Entropia , Fractais , Processamento de Imagem Assistida por Computador/métodos , Tecnologia
4.
Sci Rep ; 12(1): 12339, 2022 Jul 19.
Artigo em Inglês | MEDLINE | ID: mdl-35853929

RESUMO

Diagnosing osteosarcoma (OS) is very challenging and OS is often misdiagnosed as osteomyelitis (OM) due to the nonspecificity of its symptoms upon initial presentation. This study investigated the possibility of detecting OS-induced trabecular bone changes on panoramic radiographs and differentiating OS from OM by analyzing fractal dimensions (FDs) and degrees of anisotropy (DAs). Panoramic radiographs of patients with histopathologically proven OS and OM of the jaw were obtained. A total of 23 patients with OS and 40 patients with OM were enrolled. To investigate whether there was a microarchitectural difference between OS lesions and normal trabecular areas in each patient, two regions of interest (ROIs) were located on the CT images. Three microarchitectural parameters (box-counting FD, fast Fourier transform-based FD, and DA) were calculated. For both OS and OM, significant differences were found for all three microarchitectural parameters. Compared to normal trabecular bone, trabecular bone affected by OS and OM became isotropic and more complex. When comparing OS and OM, a statistically significant difference was found only in DA. Trabecular bones affected by OS became more isotropic than those affected by OM. Microarchitectural analysis, especially DA, could be useful for detecting OS-induced trabecular alterations and differentiating OS from OM.


Assuntos
Osteomielite , Osteossarcoma , Anisotropia , Fractais , Humanos , Mandíbula , Osteomielite/diagnóstico por imagem , Osteossarcoma/diagnóstico por imagem , Radiografia Panorâmica
5.
Sci Rep ; 12(1): 11780, 2022 Jul 11.
Artigo em Inglês | MEDLINE | ID: mdl-35821514

RESUMO

Cerebral small vessel disease is a neurological disease frequently found in the elderly and detected on neuroimaging, often as an incidental finding. White matter hyperintensity is one of the most commonly reported neuroimaging markers of CSVD and is linked with an increased risk of future stroke and vascular dementia. Recent attention has focused on the search of CSVD biomarkers. The objective of this study is to explore the potential of fractal dimension as a vascular neuroimaging marker in asymptomatic CSVD with low WMH burden. Df is an index that measures the complexity of a self-similar and irregular structure such as circle of Willis and its tributaries. This exploratory cross-sectional study involved 22 neurologically asymptomatic adult subjects (42 ± 12 years old; 68% female) with low to moderate 10-year cardiovascular disease risk prediction score (QRISK2 score) who underwent magnetic resonance imaging/angiography (MRI/MRA) brain scan. Based on the MRI findings, subjects were divided into two groups: subjects with low WMH burden and no WMH burden, (WMH+; n = 8) and (WMH-; n = 14) respectively. Maximum intensity projection image was constructed from the 3D time-of-flight (TOF) MRA. The complexity of the CoW and its tributaries observed in the MIP image was characterised using Df. The Df of the CoW and its tributaries, i.e., Df (w) was significantly lower in the WMH+ group (1.5172 ± 0.0248) as compared to WMH- (1.5653 ± 0.0304, p = 0.001). There was a significant inverse relationship between the QRISK2 risk score and Df (w), (rs = - .656, p = 0.001). Df (w) is a promising, non-invasive vascular neuroimaging marker for asymptomatic CSVD with WMH. Further study with multi-centre and long-term follow-up is warranted to explore its potential as a biomarker in CSVD and correlation with clinical sequalae of CSVD.


Assuntos
Doenças de Pequenos Vasos Cerebrais , Fractais , Biomarcadores , Doenças de Pequenos Vasos Cerebrais/diagnóstico por imagem , Estudos Transversais , Feminino , Humanos , Masculino , Neuroimagem
6.
Gait Posture ; 96: 351-356, 2022 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-35820239

RESUMO

BACKGROUND: Incorporating variability within gait rehabilitation offers a promising approach to restore functional capacity. However, it's success requires adequate synchronization, a parameter that lacks report in most of the literature regarding cued gait training. RESEARCH QUESTION: How changes to synchronization performance during fractal-like and isochronous cueing impacts gait variability measures? METHODS: We asked twelve young male participants to walk in synchronization to two different temporally structure cueing (isochronous [ISO] and fractal [FRC]). We have also manipulated the cueing's tempo by increasing and decreasing it by 5% to manipulate synchronization, resulting in six conditions (stimuli [ISO,FRC] x tempo [SLOW, NORMAL, FAST]). The normal condition was set from an uncued trial through the participant's self-paced stride time. Synchronization performance (ASYNC) and gait variability (fractal scaling and coefficient of variation) were calculated from stride time data ( -ISIs,CV-ISIs). Repeated measures analysis of variance or Aligned Rank Transform were conducted to determine significant differences between metronome tempo and stimuli for the dependent variables RESULTS: Our results showed a FAST tempo decreases synchronization performance (ASYNC) and leads to lower -ISIs, for both ISO and FRC stimuli. This indicates that when an individual exhibits poor synchronization during cued gait training, his/her gait variability patterns will not follow the temporal structure of the presented metronome. Specifically, if the individual poorly synchronizes to the cues, the gait patterns become more random, a condition typically observed in older adults and neurological patients, which runs contrary to the hypothesis when using fractal-like metronomes. SIGNIFICANCE: This study provides supporting evidence that measuring synchronization performance in cued training is fundamental for a proper clinical interpretation of its effects. This is particularly relevant for the recent and ongoing clinical research using fractal-like metronomes since the expected gait patterns are dependent on the synchronization performance. Randomized control trials must incorporate synchronization performance related measures.


Assuntos
Sinais (Psicologia) , Marcha , Idoso , Feminino , Fractais , Humanos , Masculino , Caminhada
7.
Neuroimage ; 259: 119433, 2022 Oct 01.
Artigo em Inglês | MEDLINE | ID: mdl-35781077

RESUMO

Dynamic functional connectivity (dFC) in resting-state fMRI holds promise to deliver candidate biomarkers for clinical applications. However, the reliability and interpretability of dFC metrics remain contested. Despite a myriad of methodologies and resulting measures, few studies have combined metrics derived from different conceptualizations of brain functioning within the same analysis - perhaps missing an opportunity for improved interpretability. Using a complexity-science approach, we assessed the reliability and interrelationships of a battery of phase-based dFC metrics including tools originating from dynamical systems, stochastic processes, and information dynamics approaches. Our analysis revealed novel relationships between these metrics, which allowed us to build a predictive model for integrated information using metrics from dynamical systems and information theory. Furthermore, global metastability - a metric reflecting simultaneous tendencies for coupling and decoupling - was found to be the most representative and stable metric in brain parcellations that included cerebellar regions. Additionally, spatiotemporal patterns of phase-locking were found to change in a slow, non-random, continuous manner over time. Taken together, our findings show that the majority of characteristics of resting-state fMRI dynamics reflect an interrelated dynamical and informational complexity profile, which is unique to each acquisition. This finding challenges the interpretation of results from cross-sectional designs for brain neuromarker discovery, suggesting that individual life-trajectories may be more informative than sample means.


Assuntos
Encéfalo , Fractais , Encéfalo/diagnóstico por imagem , Mapeamento Encefálico/métodos , Estudos Transversais , Humanos , Imageamento por Ressonância Magnética/métodos , Reprodutibilidade dos Testes
8.
Int J Neural Syst ; 32(7): 2250031, 2022 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-35818925

RESUMO

An accurate diagnosis of the disorder of consciousness (DOC) is essential for generating tailored treatment programs. Accurately diagnosing patients with a vegetative state (VS) and patients in a minimally conscious state (MCS), however, might be very complicated, reaching a misdiagnosis of approximately 40% if clinical scales are not carefully administered and continuously repeated. To improve diagnostic accuracy for those patients, tools such as electroencephalography (EEG) might be used in the clinical setting. Many linear indices have been developed to improve the diagnosis in DOC patients, such as spectral power in different EEG frequency bands, spectral power ratios between these bands, and the difference between eyes-closed and eyes-open conditions (i.e. alpha-blocking). On the other hand, much less has been explored using nonlinear approaches. Therefore, in this work, we aim to discriminate between MCS and VS groups using a nonlinear method called Higuchi's Fractal Dimension (HFD) and show that HFD is more sensitive than linear methods based on spectral power methods. For the sake of completeness, HFD has also been tested against another nonlinear approach widely used in EEG research, the Entropy (E). To our knowledge, this is the first time that HFD has been used in EEG data at rest to discriminate between MCS and VS patients. A comparison of Bayes factors found that differences between MCS and VS were 11 times more likely to be detected using HFD than the best performing linear method tested and almost 32 times with respect to the E. Machine learning has also been tested for HFD, reaching an accuracy of 88.6% in discriminating among VS, MCS and healthy controls. Furthermore, correlation analysis showed that HFD was more robust to outliers than spectral power methods, showing a clear positive correlation between the HFD and Coma Recovery Scale-Revised (CRS-R) values. In conclusion, our work suggests that HFD could be used as a sensitive marker to discriminate between MCS and VS patients and help decrease misdiagnosis in clinical practice when combined with commonly used clinical scales.


Assuntos
Estado de Consciência , Fractais , Teorema de Bayes , Eletroencefalografia/métodos , Humanos , Estado Vegetativo Persistente/diagnóstico
9.
Sci Rep ; 12(1): 11868, 2022 Jul 13.
Artigo em Inglês | MEDLINE | ID: mdl-35831401

RESUMO

Automated fundus screening is becoming a significant programme of telemedicine in ophthalmology. Instant quality evaluation of uploaded retinal images could decrease unreliable diagnosis. In this work, we propose fractal dimension of retinal vasculature as an easy, effective and explainable indicator of retinal image quality. The pipeline of our approach is as follows: utilize image pre-processing technique to standardize input retinal images from possibly different sources to a uniform style; then, an improved deep learning empowered vessel segmentation model is employed to extract retinal vessels from the pre-processed images; finally, a box counting module is used to measure the fractal dimension of segmented vessel images. A small fractal threshold (could be a value between 1.45 and 1.50) indicates insufficient image quality. Our approach has been validated on 30,644 images from four public database.


Assuntos
Fractais , Vasos Retinianos , Algoritmos , Fundo de Olho , Processamento de Imagem Assistida por Computador/métodos , Retina/diagnóstico por imagem , Vasos Retinianos/diagnóstico por imagem
10.
Chaos ; 32(6): 063123, 2022 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-35778122

RESUMO

There is little attention paid to stochastic tree networks in comparison with the corresponding deterministic analogs in the current study of fractal trees. In this paper, we propose a principled framework for producing a family of stochastic growth tree networks T possessing fractal characteristic, where t represents the time step and parameter m is the number of vertices newly created for each existing vertex at generation. To this end, we introduce two types of generative ways, i.e., Edge-Operation and Edge-Vertex-Operation. More interestingly, the resulting stochastic trees turn out to have an identical fractal dimension d = ln ⁡ 2 ( m + 1 ) / ln ⁡ 2 regardless of the introduction of randomness in the growth process. At the same time, we also study many other structural parameters including diameter and degree distribution. In both extreme cases, our tree networks are deterministic and follow multiple-point degree distribution and power-law degree distribution, respectively. Additionally, we consider random walks on stochastic growth tree networks T and derive an expectation estimation for mean hitting time ⟨ H ⟩ in an effective combinatorial manner instead of commonly used spectral methods. The result shows that on average, the scaling of mean hitting time ⟨ H ⟩ obeys ⟨ H ⟩ = | T |, where | T | represents vertex number and exponent λ is equivalent to 1 + ln ⁡ 2 / ln ⁡ 2 ( m + 1 ). In the meantime, we conduct extensive experimental simulations and observe that empirical analysis is in strong agreement with theoretical results.


Assuntos
Fractais
11.
Sci Rep ; 12(1): 10743, 2022 Jun 24.
Artigo em Inglês | MEDLINE | ID: mdl-35750777

RESUMO

The complexity in the styles of 1200 Byzantine icons painted between 13th and 16th from Greece, Russia and Romania was investigated through the Kolmogorov algorithmic information theory. The aim was to identify specific quantitative patterns which define the key characteristics of the three different painting schools. Our novel approach using the artificial surface images generated with Inverse FFT and the Midpoint Displacement (MD) algorithms, was validated by comparison of results with eight fractal and non-fractal indices. From the analyzes performed, normalized Kolmogorov compression complexity (KC) proved to be the best solution because it had the best complexity pattern differentiations, is not sensitive to the image size and the least affected by noise. We conclude that normalized KC methodology does offer capability to differentiate the icons within a School and amongst the three Schools.


Assuntos
Compressão de Dados , Algoritmos , Fractais , Teoria da Informação , Instituições Acadêmicas
12.
Sci Rep ; 12(1): 10481, 2022 Jun 21.
Artigo em Inglês | MEDLINE | ID: mdl-35729173

RESUMO

Fractal scaling in animal behavioral activity, where similar temporal patterns appear repeatedly over a series of magnifications among time scales, governs the complex behavior of various animal species and, in humans, can be altered by neurodegenerative diseases and aging. However, the mechanism underlying fractal scaling remains unknown. Here, we cultured C. elegans in a microfluidic device for 3 days and analyzed temporal patterns of C. elegans activity by fractal analyses. The residence-time distribution of C. elegans behaviors shared a common feature with those of human and mice. Specifically, the residence-time power-law distribution of the active state changed to an exponential-like decline at a longer time scale, whereas the inactive state followed a power-law distribution. An exponential-like decline appeared with nutrient supply in wild-type animals, whereas this decline disappeared in insulin-signaling-defective daf-2 and daf-16 mutants. The absolute value of the power-law exponent of the inactive state distribution increased with nutrient supply in wild-type animals, whereas the value decreased in daf-2 and daf-16 mutants. We conclude that insulin signaling differentially affects mechanisms that determine the residence time in active and inactive states in C. elegans behavior. In humans, diabetes mellitus, which is caused by defects in insulin signaling, is associated with mood disorders that affect daily behavioral activities. We hypothesize that comorbid behavioral defects in patients with diabetes may be attributed to altered fractal scaling of human behavior.


Assuntos
Proteínas de Caenorhabditis elegans , Caenorhabditis elegans , Animais , Proteínas de Caenorhabditis elegans/genética , Fatores de Transcrição Forkhead/genética , Fractais , Humanos , Insulina , Longevidade , Camundongos , Mutação , Receptor de Insulina/genética
13.
Ageing Res Rev ; 79: 101651, 2022 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-35643264

RESUMO

Sensitive and specific antemortem biomarkers of neurodegenerative disease and dementia are crucial to the pursuit of effective treatments, required both to reliably identify disease and to track its progression. Atrophy is the structural magnetic resonance imaging (MRI) hallmark of neurodegeneration. However in most cases it likely indicates a relatively advanced stage of disease less susceptible to treatment as some disease processes begin decades prior to clinical onset. Among emerging metrics that characterise brain shape rather than volume, fractal dimension (FD) quantifies shape complexity. FD has been applied in diverse fields of science to measure subtle changes in elaborate structures. We review its application thus far to structural MRI of the brain in neurodegenerative disease and dementia. We identified studies involving subjects who met criteria for mild cognitive impairment, Alzheimer's Disease, Vascular Dementia, Lewy Body Dementia, Frontotemporal Dementia, Amyotrophic Lateral Sclerosis, Parkinson's Disease, Huntington's Disease, Multiple Systems Atrophy, Spinocerebellar Ataxia and Multiple Sclerosis. The early literature suggests that neurodegenerative disease processes are usually associated with a decline in FD of the brain. The literature includes examples of disease-related change in FD occurring independently of atrophy, which if substantiated would represent a valuable advantage over other structural imaging metrics. However, it is likely to be non-specific and to exhibit complex spatial and temporal patterns. A more harmonious methodological approach across a larger number of studies as well as careful attention to technical factors associated with image processing and FD measurement will help to better elucidate the metric's utility.


Assuntos
Doença de Alzheimer , Doenças Neurodegenerativas , Doença de Alzheimer/patologia , Atrofia/patologia , Encéfalo/diagnóstico por imagem , Encéfalo/patologia , Fractais , Humanos , Imageamento por Ressonância Magnética/métodos , Doenças Neurodegenerativas/diagnóstico por imagem , Doenças Neurodegenerativas/patologia
14.
Transl Vis Sci Technol ; 11(5): 1, 2022 05 02.
Artigo em Inglês | MEDLINE | ID: mdl-35499823

RESUMO

Purpose: To identify the ocular factors of microvascular fractal dimension (FD) and blood vessel tortuosity (BVT) of macula measured with optical coherence tomography angiography (OCTA) in a healthy Chinese population. Methods: Healthy subjects without ocular disorders were recruited at Zhongshan Ophthalmic Center. The FD and BVT in the superficial capillary plexus (SCP) and deep capillary plexus (DCP) at the macula were obtained from OCTA images. The FD was calculated using the box-counting method, and the BVT was defined as the ratio of the actual distance between two points to the straight distance on the skeletonized image. Univariate and stepwise multivariate linear regression analyses were performed to identify the ocular factors of FD and BVT, and the results are presented as coefficients and 95% confidence intervals (CIs). Only the right eye of each subject was included. Results: A total of 2189 healthy individuals (2189 eyes) were included with a mean age of 49.9 ± 13.2 years; 54.4% were female. In the multivariate model, the FD in the SCP was significantly associated with higher intraocular pressure (IOP) (ß = 0.204; 95% CI, 0.073-0.335; P < 0.001), axial length (AL) (ß = -0.875; 95% CI, -1.197 to -0.552; P < 0.001; R2 = 0.26; root mean square error [RMSE] = 7.78). The FD in the DCP was significantly associated with best-corrected visual acuity (ß = -6.170; 95% CI, -10.175 to -2.166; P = 0.003) and anterior chamber depth (ß = -0.348; 95% CI, -0.673 to -0.023; P = 0.036; R2 = 0.10; RMSE = 2.58). Superficial BVT was independently associated with IOP (ß = -0.044; 95% CI, -0.079 to -0.009; P = 0.012) and AL (ß = 0.097; 95% CI, 0.014-0.181; P = 0.022; R2 = 0.15; RMSE = 2.02). Deep BVT was independently associated with IOP (ß = -0.004; 95% CI, -0.009 to -0.0005; P = 0.028) and lens thickness (ß = 0.036, 95% CI, 0.003-0.060; P = 0.028; R2 = 0.07, RMSE = 0.25). Conclusions: The IOP and AL were dependent ocular parameters variables of FD and BVT in the SCP in this healthy population. The FD in the DCP was also influenced by visual acuity and anterior chamber depth. These factors should be considered when microvascular geometrics are used in the future studies. Translational Relevance: This work discovered the influence factors of OCTA geometrics parameters for further establishment of diagnostic model or method for glaucoma and other microvasculature-related ocular diseases.


Assuntos
Vasos Retinianos , Tomografia de Coerência Óptica , Adulto , China , Feminino , Angiofluoresceinografia/métodos , Fractais , Humanos , Masculino , Pessoa de Meia-Idade , Vasos Retinianos/diagnóstico por imagem , Tomografia de Coerência Óptica/métodos
15.
Sensors (Basel) ; 22(9)2022 Apr 19.
Artigo em Inglês | MEDLINE | ID: mdl-35590793

RESUMO

The resting-state functional magnetic resonance imaging (rs-fMRI) modality has gained widespread acceptance as a promising method for analyzing a variety of neurological and psychiatric diseases. It is established that resting-state neuroimaging data exhibit fractal behavior, manifested in the form of slow-decaying auto-correlation and power-law scaling of the power spectrum across low-frequency components. With this property, the rs-fMRI signal can be broken down into fractal and nonfractal components. The fractal nature originates from several sources, such as cardiac fluctuations, respiration and system noise, and carries no information on the brain's neuronal activities. As a result, the conventional correlation of rs-fMRI signals may not accurately reflect the functional dynamic of spontaneous neuronal activities. This problem can be solved by using a better representation of neuronal activities provided by the connectivity of nonfractal components. In this work, the nonfractal connectivity of rs-fMRI is used to distinguish Alzheimer's patients from healthy controls. The automated anatomical labeling (AAL) atlas is used to extract the blood-oxygenation-level-dependent time series signals from 116 brain regions, yielding a 116 × 116 nonfractal connectivity matrix. From this matrix, significant connections evaluated using the p-value are selected as an input to a classifier for the classification of Alzheimer's vs. normal controls. The nonfractal-based approach provides a good representation of the brain's neuronal activity. It outperformed the fractal and Pearson-based connectivity approaches by 16.4% and 17.2%, respectively. The classification algorithm developed based on the nonfractal connectivity feature and support vector machine classifier has shown an excellent performance, with an accuracy of 90.3% and 83.3% for the XHSLF dataset and ADNI dataset, respectively. For further validation of our proposed work, we combined the two datasets (XHSLF+ADNI) and still received an accuracy of 90.2%. The proposed work outperformed the recently published work by a margin of 8.18% and 11.2%, respectively.


Assuntos
Doença de Alzheimer , Imageamento por Ressonância Magnética , Doença de Alzheimer/patologia , Encéfalo/fisiologia , Mapeamento Encefálico , Fractais , Humanos , Imageamento por Ressonância Magnética/métodos
16.
Int J Neural Syst ; 32(6): 2250028, 2022 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-35579974

RESUMO

Over the last decades, the exuberant development of next-generation sequencing has revolutionized gene discovery. These technologies have boosted the mapping of single nucleotide polymorphisms (SNPs) across the human genome, providing a complex universe of heterogeneity characterizing individuals worldwide. Fractal dimension (FD) measures the degree of geometric irregularity, quantifying how "complex" a self-similar natural phenomenon is. We compared two FD algorithms, box-counting dimension (BCD) and Higuchi's fractal dimension (HFD), to characterize genome-wide patterns of SNPs extracted from the HapMap data set, which includes data from 1184 healthy subjects of eleven populations. In addition, we have used cluster and classification analysis to relate the genetic distances within chromosomes based on FD similarities to the geographical distances among the 11 global populations. We found that HFD outperformed BCD at both grand average clusterization analysis by the cophenetic correlation coefficient, in which the closest value to 1 represents the most accurate clustering solution (0.981 for the HFD and 0.956 for the BCD) and classification (79.0% accuracy, 61.7% sensitivity, and 96.4% specificity for the HFD with respect to 69.1% accuracy, 43.2% sensitivity, and 94.9% specificity for the BCD) of the 11 populations present in the HapMap data set. These results support the evidence that HFD is a reliable measure helpful in representing individual variations within all chromosomes and categorizing individuals and global populations.


Assuntos
Fractais , Genoma Humano , Algoritmos , Variação Genética , Projeto HapMap , Humanos
17.
Comput Intell Neurosci ; 2022: 7543429, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-35571692

RESUMO

The detection of brain tumors using magnetic resonance imaging is currently one of the biggest challenges in artificial intelligence and medical engineering. It is important to identify these brain tumors as early as possible, as they can grow to death. Brain tumors can be classified as benign or malignant. Creating an intelligent medical diagnosis system for the diagnosis of brain tumors from MRI imaging is an integral part of medical engineering as it helps doctors detect brain tumors early and oversee treatment throughout recovery. In this study, a comprehensive approach to diagnosing benign and malignant brain tumors is proposed. The proposed method consists of four parts: image enhancement to reduce noise and unify image size, contrast, and brightness, image segmentation based on morphological operators, feature extraction operations including size reduction and selection of features based on the fractal model, and eventually, feature improvement according to segmentation and selection of optimal class with a fuzzy deep convolutional neural network. The BraTS data set is used as magnetic resonance imaging data in experimental results. A series of evaluation criteria is also compared with previous methods, where the accuracy of the proposed method is 98.68%, which has significant results.


Assuntos
Neoplasias Encefálicas , Processamento de Imagem Assistida por Computador , Algoritmos , Inteligência Artificial , Neoplasias Encefálicas/diagnóstico por imagem , Fractais , Humanos , Processamento de Imagem Assistida por Computador/métodos , Imageamento por Ressonância Magnética/métodos , Redes Neurais de Computação
18.
J Vis ; 22(6): 7, 2022 05 03.
Artigo em Inglês | MEDLINE | ID: mdl-35587355

RESUMO

Natural scenes contain several statistical regularities despite their superficially diverse appearances (e.g., mountains, rainforests, deserts). First, they exhibit a unique distribution of luminance intensities decreasing across spatial frequency, known as the 1/fα amplitude spectrum (α ≈ 1). Additionally, natural scenes share consistent geometric properties, comprising similar densities of structure across multiple scales-a property classifying them as fractal (e.g., how the branching patterns of rivers and trees appear similar irrespective of scale). These two properties are intimately related and correlate strongly in natural scenes. However, research using thresholded noise images suggests that spatially, the human visual system is preferentially tuned to natural scene structure more so than 1/fα spectra. It is currently unclear whether this dependency on natural geometry extends to the temporal domain. We used a psychophysics task to measure discrimination sensitivity toward two types of synthetic noise movies: gray scale and thresholded (N = 60). Each movie type shared the same geometric properties (measured fractal D), but substantially differing spectral properties (measured α). In both space and time, we observe a characteristic dependency on stimulus structure across movie types, with sensitivity peaking for stimuli with natural geometry despite having altered 1/fα spectra. Although only measured behaviorally, our findings may imply that the neural processes underlying this tuning have developed to be sensitive to the most stable signal in our natural environment-structure (e.g., the structural properties of a tree are consistent from morning to night despite illumination changes across time points).


Assuntos
Fractais , Humanos , Movimento (Física) , Estimulação Luminosa/métodos , Psicofísica
19.
Retina ; 42(6): 1005-1011, 2022 06 01.
Artigo em Inglês | MEDLINE | ID: mdl-35594074

RESUMO

PURPOSE: To compare quantitative optical coherence tomography angiography parameters between polypoidal choroidal neovascularizations (PCNVs) and Type 1 choroidal neovascularizations (CNVs) in patients with age-related macular degeneration. METHODS: PCNV and Type 1 CNV lesions were retrospectively recruited in a cohort of patients with age-related macular degeneration. All the patients underwent a comprehensive ophthalmic evaluation, including best-corrected visual acuity, fluorescein and indocyanine green angiography, structural optical coherence tomography (OCT), and optical coherence tomography angiography.Vascular perfusion density, fractal dimension, and lacunarity were computed by means of fractal analysis of neovascular en face optical coherence tomography angiography slabs. RESULTS: Sixty-eight eyes were included in the analysis. Of them, 35 of 68 eyes (51.5%) had PCNV and 33 of 68 (48.5%) had Type 1 CNV. Patients with PCNV were significantly younger (P = 0.0003) and had a higher best-corrected visual acuity (P < 0.0001). The mean vascular perfusion density was 0.83 ± 0.11% in PCNVs and 0.46 ± 0.10% in Type 1 CNVs (P < 0.0001). The mean fractal dimension was 1.44 ± 0.1 in PCNVs and 1.45 ± 0.09 in Type 1 CNVs (P = 0.86) while the mean lacunarity was 2.46 ± 1.03 in PCNVs and 1.86 ± 0.52 in Type 1 CNVs (P = 0.006). CONCLUSION: PCNVs resulted to be more heterogeneous and characterized by higher vascular perfusion density and lacunarity values than Type 1 CNVs. These interesting findings seem to support the idea that PCNVs and Type 1 CNVs are two separate clinical entities. However, future studies based on optical coherence tomography angiography fractal analysis, but also involving other relevant parameters such as demographics, presentation, morphology on multimodal imaging, and response to treatment, are necessary before drawing any definitive conclusions on whether PCNV is a specific clinical entity or a neovascular age-related macular degeneration variant.


Assuntos
Neovascularização de Coroide , Degeneração Macular , Degeneração Macular Exsudativa , Neovascularização de Coroide/diagnóstico , Neovascularização de Coroide/tratamento farmacológico , Angiofluoresceinografia/métodos , Fractais , Humanos , Verde de Indocianina , Degeneração Macular/complicações , Degeneração Macular/diagnóstico , Degeneração Macular/tratamento farmacológico , Estudos Retrospectivos , Tomografia de Coerência Óptica/métodos , Acuidade Visual , Degeneração Macular Exsudativa/complicações , Degeneração Macular Exsudativa/diagnóstico
20.
Methods Mol Biol ; 2399: 277-341, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-35604562

RESUMO

The temporal dynamics in biological systems displays a wide range of behaviors, from periodic oscillations, as in rhythms, bursts, long-range (fractal) correlations, chaotic dynamics up to brown and white noise. Herein, we propose a comprehensive analytical strategy for identifying, representing, and analyzing biological time series, focusing on two strongly linked dynamics: periodic (oscillatory) rhythms and chaos. Understanding the underlying temporal dynamics of a system is of fundamental importance; however, it presents methodological challenges due to intrinsic characteristics, among them the presence of noise or trends, and distinct dynamics at different time scales given by molecular, dcellular, organ, and organism levels of organization. For example, in locomotion circadian and ultradian rhythms coexist with fractal dynamics at faster time scales. We propose and describe the use of a combined approach employing different analytical methodologies to synergize their strengths and mitigate their weaknesses. Specifically, we describe advantages and caveats to consider for applying probability distribution, autocorrelation analysis, phase space reconstruction, Lyapunov exponent estimation as well as different analyses such as harmonic, namely, power spectrum; continuous wavelet transforms; synchrosqueezing transform; and wavelet coherence. Computational harmonic analysis is proposed as an analytical framework for using different types of wavelet analyses. We show that when the correct wavelet analysis is applied, the complexity in the statistical properties, including temporal scales, present in time series of signals, can be unveiled and modeled. Our chapter showcase two specific examples where an in-depth analysis of rhythms and chaos is performed: (1) locomotor and food intake rhythms over a 42-day period of mice subjected to different feeding regimes; and (2) chaotic calcium dynamics in a computational model of mitochondrial function.


Assuntos
Locomoção , Análise de Ondaletas , Animais , Biologia , Fractais , Camundongos
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