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Computers in Biology and Medicine

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https://www.readbyqxmd.com/read/28719805/seizure-detection-from-eeg-signals-using-multivariate-empirical-mode-decomposition
#1
Asmat Zahra, Nadia Kanwal, Naveed Ur Rehman, Shoaib Ehsan, Klaus D McDonald-Maier
We present a data driven approach to classify ictal (epileptic seizure) and non-ictal EEG signals using the multivariate empirical mode decomposition (MEMD) algorithm. MEMD is a multivariate extension of empirical mode decomposition (EMD), which is an established method to perform the decomposition and time-frequency (T-F) analysis of non-stationary data sets. We select suitable feature sets based on the multiscale T-F representation of the EEG data via MEMD for the classification purposes. The classification is achieved using the artificial neural networks...
July 8, 2017: Computers in Biology and Medicine
https://www.readbyqxmd.com/read/28711767/fully-automated-subchondral-bone-segmentation-from-knee-mr-images-data-from-the-osteoarthritis-initiative
#2
Akash Gandhamal, Sanjay Talbar, Suhas Gajre, Ruslan Razak, Ahmad Fadzil M Hani, Dileep Kumar
Knee osteoarthritis (OA) progression can be monitored by measuring changes in the subchondral bone structure such as area and shape from MR images as an imaging biomarker. However, measurements of these minute changes are highly dependent on the accurate segmentation of bone tissue from MR images and it is challenging task due to the complex tissue structure and inadequate image contrast/brightness. In this paper, a fully automated method for segmenting subchondral bone from knee MR images is proposed. Here, the contrast of knee MR images is enhanced using a gray-level S-curve transformation followed by automatic seed point detection using a three-dimensional multi-edge overlapping technique...
July 8, 2017: Computers in Biology and Medicine
https://www.readbyqxmd.com/read/28711766/a-tool-for-automated-diabetic-retinopathy-pre-screening-based-on-retinal-image-computer-analysis
#3
Manuel E Gegundez-Arias, Diego Marin, Beatriz Ponte, Fatima Alvarez, Javier Garrido, Carlos Ortega, Manuel J Vasallo, Jose M Bravo
AIM: This paper presents a methodology and first results of an automatic detection system of first signs of Diabetic Retinopathy (DR) in fundus images, developed for the Health Ministry of the Andalusian Regional Government (Spain). MATERIAL AND METHODS: The system detects the presence of microaneurysms and haemorrhages in retinography by means of techniques of digital image processing and supervised classification. Evaluation was conducted on 1058 images of 529 diabetic patients at risk of presenting evidence of DR (an image of each eye is provided)...
July 8, 2017: Computers in Biology and Medicine
https://www.readbyqxmd.com/read/28709145/diagnosis-of-attention-deficit-hyperactivity-disorder-using-imaging-and-signal-processing-techniques
#4
REVIEW
Chaitra Sridhar, Shreya Bhat, U Rajendra Acharya, Hojjat Adeli, G Muralidhar Bairy
Attention Deficit Hyperactivity Disorder (ADHD) is the most common childhood psychiatric disorder that may continue through adolescence and adulthood. Hyperactivity, inattention and impulsivity are the key behavioral features observed in children with ADHD. ADHD is normally diagnosed only when a child continues to have symptoms of hyperactivity, impulsivity and inattention at a greater degree than the normal for six months or more. In recent years there has been significant research to diagnose ADHD in a quantitative way using medical imaging and signal processing techniques...
July 8, 2017: Computers in Biology and Medicine
https://www.readbyqxmd.com/read/28705417/multi-label-classification-methods-for-improving-comorbidities-identification
#5
A Wosiak, K Glinka, D Zakrzewska
The medical diagnostic process may be supported by computational classification techniques. In many cases, patients are affected by multiple illnesses, and more than one classification label is required to improve medical decision-making. In this paper, we consider a multi-perspective classification problem for medical diagnostics, where cases are described by labels from separate sets. We attempt to improve the identification of comorbidities using multi-label classification techniques. Several investigated methods, which provide label dependencies, are analysed and evaluated...
July 8, 2017: Computers in Biology and Medicine
https://www.readbyqxmd.com/read/28700903/computer-based-classification-of-chromoendoscopy-images-using-homogeneous-texture-descriptors
#6
Hussam Ali, Muhammad Sharif, Mussarat Yasmin, Mubashir Husain Rehmani
Computer-aided analysis of clinical pathologies is a challenging task in the field of medical imaging. Specifically, the detection of abnormal regions in the frames collected during an endoscopic session is difficult. The variations in the conditions of image acquisition, such as field of view or illumination modification, make it more demanding. Therefore, the design of a computer-assisted diagnostic system for the recognition of gastric abnormalities requires features that are robust to scale, rotation, and illumination variations of the images...
July 5, 2017: Computers in Biology and Medicine
https://www.readbyqxmd.com/read/28715667/spectral-and-spatiotemporal-variability-ecg-parameters-linked-to-catheter-ablation-outcome-in-persistent-atrial-fibrillation
#7
Antonio R Hidalgo-Muñoz, Decebal G Latcu, Marianna Meo, Olivier Meste, Irina Popescu, Nadir Saoudi, Vicente Zarzoso
With the increasing prevalence of atrial fibrillation (AF), there is a strong clinical interest in determining whether a patient suffering from persistent AF will benefit from catheter ablation (CA) therapy at long term. This work presents several regression models based on noninvasive measures automatically computed from the standard 12-lead electrocardiogram (ECG) such as AF dominant frequency (DF), spectral concentration and spatiotemporal variability (STV). Sixty-two AF patients referred to CA were enrolled in this study...
July 4, 2017: Computers in Biology and Medicine
https://www.readbyqxmd.com/read/28692930/evaluation-of-dynamic-scaling-of-growing-interfaces-in-eeg-fluctuations-of-seizures-in-animal-model-of-temporal-lobe-epilepsy
#8
Claudia Lizbeth Martínez-González, Alexander Balankin, Tessy López, Joaquín Manjarrez-Marmolejo, Efraín José Martínez-Ortiz
Epileptic seizures, as a dynamic phenomenon in brain behavior, obey a scale-free behavior, frequently analyzed by electrical activity recording. This recording can be seen as a surface that roughens with time. Dynamic scaling studies roughening processes or growing interfaces. In this theory, a set of exponents -obtained from scale invariance properties- characterize rough interfaces growth. The aim of the present study was to investigate scaling behavior in EEG time series fluctuations of a chemical animal model of temporal lobe epilepsy, with dynamic scaling to detect changes on seizure onset...
July 4, 2017: Computers in Biology and Medicine
https://www.readbyqxmd.com/read/28692931/automatic-discrimination-of-actinic-keratoses-from-clinical-photographs
#9
Panagiota Spyridonos, Georgios Gaitanis, Aristidis Likas, Ioannis D Bassukas
BACKGROUND AND OBJECTIVE: Actinic keratoses (AK) are common premalignant skin lesions that can progress to invasive skin squamous cell carcinoma (sSCC). The subtle accumulation of multiple AK in aging individuals increases the risk of sSCC development, and this underscores the need for efficient treatment and patient follow-up. Our objectives were to develop a method based on color texture analysis of standard clinical photographs for the discrimination of AK from healthy skin and subsequently to test the developed approach in the quantification of field-directed treatment interventions...
July 3, 2017: Computers in Biology and Medicine
https://www.readbyqxmd.com/read/28700902/a-novel-algorithm-to-detect-glaucoma-risk-using-texton-and-local-configuration-pattern-features-extracted-from-fundus-images
#10
U Rajendra Acharya, Shreya Bhat, Joel E W Koh, Sulatha V Bhandary, Hojjat Adeli
Glaucoma is an optic neuropathy defined by characteristic damage to the optic nerve and accompanying visual field deficits. Early diagnosis and treatment are critical to prevent irreversible vision loss and ultimate blindness. Current techniques for computer-aided analysis of the optic nerve and retinal nerve fiber layer (RNFL) are expensive and require keen interpretation by trained specialists. Hence, an automated system is highly desirable for a cost-effective and accurate screening for the diagnosis of glaucoma...
June 29, 2017: Computers in Biology and Medicine
https://www.readbyqxmd.com/read/28666179/computing-dispersion-curves-of-elastic-viscoelastic-transversely-isotropic-bone-plates-coupled-with-soft-tissue-and-marrow-using-semi-analytical-finite-element-safe-method
#11
Vu-Hieu Nguyen, Tho N H T Tran, Mauricio D Sacchi, Salah Naili, Lawrence H Le
We present a semi-analytical finite element (SAFE) scheme for accurately computing the velocity dispersion and attenuation in a trilayered system consisting of a transversely-isotropic (TI) cortical bone plate sandwiched between the soft tissue and marrow layers. The soft tissue and marrow are mimicked by two fluid layers of finite thickness. A Kelvin-Voigt model accounts for the absorption of all three biological domains. The simulated dispersion curves are validated by the results from the commercial software DISPERSE and published literature...
June 27, 2017: Computers in Biology and Medicine
https://www.readbyqxmd.com/read/28672176/a-type-2-fuzzy-data-fusion-approach-for-building-reliable-weighted-protein-interaction-networks-with-application-in-protein-complex-detection
#12
Adele Mehranfar, Nasser Ghadiri, Morteza Kouhsar, Ashkan Golshani
Detecting the protein complexes is an important task in analyzing the protein interaction networks. Although many algorithms predict protein complexes in different ways, surveys on the interaction networks indicate that about 50% of detected interactions are false positives. Consequently, the accuracy of existing methods needs to be improved. In this paper we propose a novel algorithm to detect the protein complexes in 'noisy' protein interaction data. First, we integrate several biological data sources to determine the reliability of each interaction and determine more accurate weights for the interactions...
June 23, 2017: Computers in Biology and Medicine
https://www.readbyqxmd.com/read/28667939/validation-of-a-novel-nonlinear-black-box-wiener-system-model-for-arterial-pulse-transmission
#13
Amit M Patel, John K-J Li
Numerous linear dynamic models exist for describing the arterial pulse transmission phenomenon. We introduce a novel Wiener system based model in which a linear filter representing large arteries is coupled with a hysteresis-free nonlinear function representing complex wave transmission of branching arteries and the periphery. Experimental datasets (n = 7) are used to first estimate the Wiener model with linear, quadratic and cubic function for the aorta to radial artery pulse transmission and aorta to femoral artery pulse transmission...
June 23, 2017: Computers in Biology and Medicine
https://www.readbyqxmd.com/read/28700901/hyperspectral-image-analysis-for-rapid-and-accurate-discrimination-of-bacterial-infections-a-benchmark-study
#14
Simone Arrigoni, Giovanni Turra, Alberto Signoroni
With the rapid diffusion of Full Laboratory Automation systems, Clinical Microbiology is currently experiencing a new digital revolution. The ability to capture and process large amounts of visual data from microbiological specimen processing enables the definition of completely new objectives. These include the direct identification of pathogens growing on culturing plates, with expected improvements in rapid definition of the right treatment for patients affected by bacterial infections. In this framework, the synergies between light spectroscopy and image analysis, offered by hyperspectral imaging, are of prominent interest...
June 21, 2017: Computers in Biology and Medicine
https://www.readbyqxmd.com/read/28658649/simultaneous-ocular-and-muscle-artifact-removal-from-eeg-data-by-exploiting-diverse-statistics
#15
Xun Chen, Aiping Liu, Qiang Chen, Yu Liu, Liang Zou, Martin J McKeown
Electroencephalography (EEG) recordings are frequently contaminated by both ocular and muscle artifacts. These are normally dealt with separately, by employing blind source separation (BSS) techniques relying on either second-order or higher-order statistics (SOS & HOS respectively). When HOS-based methods are used, it is usually in the setting of assuming artifacts are statistically independent to the EEG. When SOS-based methods are used, it is assumed that artifacts have autocorrelation characteristics distinct from the EEG...
June 21, 2017: Computers in Biology and Medicine
https://www.readbyqxmd.com/read/28728059/iterative-variational-mode-decomposition-based-automated-detection-of-glaucoma-using-fundus-images
#16
Shishir Maheshwari, Ram Bilas Pachori, Vivek Kanhangad, Sulatha V Bhandary, U Rajendra Acharya
Glaucoma is one of the leading causes of permanent vision loss. It is an ocular disorder caused by increased fluid pressure within the eye. The clinical methods available for the diagnosis of glaucoma require skilled supervision. They are manual, time consuming, and out of reach of common people. Hence, there is a need for an automated glaucoma diagnosis system for mass screening. In this paper, we present a novel method for an automated diagnosis of glaucoma using digital fundus images. Variational mode decomposition (VMD) method is used in an iterative manner for image decomposition...
June 19, 2017: Computers in Biology and Medicine
https://www.readbyqxmd.com/read/28651071/an-independent-active-contours-segmentation-framework-for-bone-micro-ct-images
#17
Vasileios Ch Korfiatis, Simone Tassani, George K Matsopoulos
Micro-CT is an imaging technique for small tissues and objects that is gaining increased popularity especially as a pre-clinical application. Nevertheless, there is no well-established micro-CT segmentation method, while typical procedures lack sophistication and frequently require a degree of manual intervention, leading to errors and subjective results. To address these issues, a novel segmentation framework, called Independent Active Contours Segmentation (IACS), is proposed in this paper. The proposed IACS is based on two autonomous modules, namely automatic ROI extraction and IAC Evolution, which segments the ROI image using multiple Active Contours that evolve simultaneously and independently of one another...
June 19, 2017: Computers in Biology and Medicine
https://www.readbyqxmd.com/read/28672177/a-novel-method-to-precisely-detect-apnea-and-hypopnea-events-by-airflow-and-oximetry-signals
#18
Wu Huang, Bing Guo, Yan Shen, Xiangdong Tang
Sleep apnea hypopnea syndrome (SAHS) affects people's quality of life. The apnea hypopnea index (AHI) is the key indicator for diagnosing SAHS. The determination of the AHI is based on accurate detection of apnea and hypopnea events. This paper provides a novel method to detect apnea and hypopnea events based on the respiratory nasal airflow signal and the oximetry signal. The method uses sliding window and short time slice methods to eliminate systematic and sporadic noise of the airflow signal for improving the detection precision...
June 17, 2017: Computers in Biology and Medicine
https://www.readbyqxmd.com/read/28651070/assessment-of-temporal-predictive-models-for-health-care-using-a-formal-method
#19
Ward van Breda, Mark Hoogendoorn, A E Eiben, Matthias Berking
Recent developments in the field of sensor devices provide new possibilities to measure a variety of health related aspects in a precise and fine-grained manner. Subsequently, more empirical data will be generated than ever before. While this greatly improves the opportunities for creating accurate predictive models, other types of models besides the more traditional machine learning approaches can provide insights into temporal relationships in the data. Models that express temporal relationships between states in a mathematical manner are examples of such models...
June 17, 2017: Computers in Biology and Medicine
https://www.readbyqxmd.com/read/28649031/noise-detection-on-ecg-based-on-agglomerative-clustering-of-morphological-features
#20
João Rodrigues, David Belo, Hugo Gamboa
Biosignals are usually contaminated with artifacts from limb movements, muscular contraction or electrical interference. Many algorithms of the literature, such as threshold methods and adaptive filters, focus on detecting these noisy patterns. This study introduces a novel method for noise and artifact detection in electrocardiogram based on time series clustering. The algorithm starts with the extraction of features that best characterize the shape and behaviour of the signal over time and groups its samples in separated clusters by means of an agglomerative clustering approach...
June 15, 2017: Computers in Biology and Medicine
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