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Computers in Biology and Medicine

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https://www.readbyqxmd.com/read/27915127/mindedit-a-p300-based-text-editor-for-mobile-devices
#1
Amr S Elsawy, Seif Eldawlatly, Mohamed Taher, Gamal M Aly
Practical application of Brain-Computer Interfaces (BCIs) requires that the whole BCI system be portable. The mobility of BCI systems involves two aspects: making the electroencephalography (EEG) recording devices portable, and developing software applications with low computational complexity to be able to run on low computational-power devices such as tablets and smartphones. This paper addresses the development of MindEdit; a P300-based text editor for Android-based devices. Given the limited resources of mobile devices and their limited computational power, a novel ensemble classifier is utilized that uses Principal Component Analysis (PCA) features to identify P300 evoked potentials from EEG recordings...
November 27, 2016: Computers in Biology and Medicine
https://www.readbyqxmd.com/read/27915126/stroke-risk-stratification-and-its-validation-using-ultrasonic-echolucent-carotid-wall-plaque-morphology-a-machine-learning-paradigm
#2
Tadashi Araki, Pankaj K Jain, Harman S Suri, Narendra D Londhe, Nobutaka Ikeda, Ayman El-Baz, Vimal K Shrivastava, Luca Saba, Andrew Nicolaides, Shoaib Shafique, John R Laird, Ajay Gupta, Jasjit S Suri
Stroke risk stratification based on grayscale morphology of the ultrasound carotid wall has recently been shown to have a promise in classification of high risk versus low risk plaque or symptomatic versus asymptomatic plaques. In previous studies, this stratification has been mainly based on analysis of the far wall of the carotid artery. Due to the multifocal nature of atherosclerotic disease, the plaque growth is not restricted to the far wall alone. This paper presents a new approach for stroke risk assessment by integrating assessment of both the near and far walls of the carotid artery using grayscale morphology of the plaque...
November 27, 2016: Computers in Biology and Medicine
https://www.readbyqxmd.com/read/27915125/artificial-neural-networks-as-a-powerful-numerical-tool-to-classify-specific-features-of-a-tooth-based-on-3d-scan-data
#3
Stefan Raith, Eric Per Vogel, Naeema Anees, Christine Keul, Jan-Frederik Güth, Daniel Edelhoff, Horst Fischer
Chairside manufacturing based on digital image acquisition is gainingincreasing importance in dentistry. For the standardized application of these methods, it is paramount to have highly automated digital workflows that can process acquired 3D image data of dental surfaces. Artificial Neural Networks (ANNs) arenumerical methods primarily used to mimic the complex networks of neural connections in the natural brain. Our hypothesis is that an ANNcan be developed that is capable of classifying dental cusps with sufficient accuracy...
November 27, 2016: Computers in Biology and Medicine
https://www.readbyqxmd.com/read/27893991/saclab-a-toolbox-for-saccade-analysis-to-increase-usability-of-eye-tracking-systems-in-clinical-ophthalmology-practice
#4
Laura Cercenelli, Guido Tiberi, Ivan Corazza, Giuseppe Giannaccare, Michela Fresina, Emanuela Marcelli
PURPOSE: Many open source software packages have been recently developed to expand the usability of eye tracking systems to study oculomotor behavior, but none of these is specifically designed to encompass all the main functions required for creating eye tracking tests and for providing the automatic analysis of saccadic eye movements. The aim of this study is to introduce SacLab, an intuitive, freely-available MATLAB toolbox based on Graphical User Interfaces (GUIs) that we have developed to increase the usability of the ViewPoint EyeTracker (Arrington Research, Scottsdale, AZ, USA) in clinical ophthalmology practice...
November 22, 2016: Computers in Biology and Medicine
https://www.readbyqxmd.com/read/27889431/multiclass-cancer-classification-using-a-feature-subset-based-ensemble-from-microrna-expression-profiles
#5
Yongjun Piao, Minghao Piao, Keun Ho Ryu
Cancer classification has been a crucial topic of research in cancer treatment. In the last decade, messenger RNA (mRNA) expression profiles have been widely used to classify different types of cancers. With the discovery of a new class of small non-coding RNAs; known as microRNAs (miRNAs), various studies have shown that the expression patterns of miRNA can also accurately classify human cancers. Therefore, there is a great demand for the development of machine learning approaches to accurately classify various types of cancers using miRNA expression data...
November 21, 2016: Computers in Biology and Medicine
https://www.readbyqxmd.com/read/27888794/custom-fpga-processing-for-real-time-fetal-ecg-extraction-and-identification
#6
E Torti, D Koliopoulos, M Matraxia, G Danese, F Leporati
Monitoring the fetal cardiac activity during pregnancy is of crucial importance for evaluating fetus health. However, there is a lack of automatic and reliable methods for Fetal ECG (FECG) monitoring that can perform this elaboration in real-time. In this paper, we present a hardware architecture, implemented on the Altera Stratix V FPGA, capable of separating the FECG from the maternal ECG and to correctly identify it. We evaluated our system using both synthetic and real tracks acquired from patients beyond the 20th pregnancy week...
November 17, 2016: Computers in Biology and Medicine
https://www.readbyqxmd.com/read/27875741/a-contrast-enhancement-method-for-improving-the-segmentation-of-breast-lesions-on-ultrasonography
#7
Wilfrido Gómez Flores, Wagner Coelho de Albuquerque Pereira
PURPOSE: This paper presents an adaptive contrast enhancement method based on sigmoidal mapping function (SACE) used for improving the computerized segmentation of breast lesions on ultrasound. METHODS: First, from the original ultrasound image an intensity variation map is obtained, which is used to generate local sigmoidal mapping functions related to distinct contextual regions. Then, a bilinear interpolation scheme is used to transform every original pixel to a new gray level value...
November 16, 2016: Computers in Biology and Medicine
https://www.readbyqxmd.com/read/27871012/algorithm-based-on-the-short-term-r%C3%A3-nyi-entropy-and-if-estimation-for-noisy-eeg-signals-analysis
#8
Jonatan Lerga, Nicoletta Saulig, Vladimir Mozetič
Stochastic electroencephalogram (EEG) signals are known to be nonstationary and often multicomponential. Detecting and extracting their components may help clinicians to localize brain neurological dysfunctionalities for patients with motor control disorders due to the fact that movement-related cortical activities are reflected in spectral EEG changes. A new algorithm for EEG signal components detection from its time-frequency distribution (TFD) has been proposed in this paper. The algorithm utilizes the modification of the Rényi entropy-based technique for number of components estimation, called short-term Rényi entropy (STRE), and upgraded by an iterative algorithm which was shown to enhance existing approaches...
November 15, 2016: Computers in Biology and Medicine
https://www.readbyqxmd.com/read/27893992/prediction-of-myocardial-infarction-by-assessing-regional-cardiac-wall-in-cmr-images-through-active-mesh-modeling
#9
Hossein Yousefi-Banaem, Saeed Kermani, Sasan Asiaei, Hamid Sanei
Myocardial infarction is a leading cause of morbidity and mortality. In this study, using Cine MRI images, the infarct region was precisely determined by examining the local migration path length of critical points on myocardium borders and the fractional thickening effects. First, MRI Cine images of Epi/Endocardium were processed in 3D for all slices, and then incorporated in all frames to build a dynamic model. Epi/Endocardium images were segmented using Heiberg algorithm, and then by a robust restricted block matching algorithm, the sparse points were tracked...
November 14, 2016: Computers in Biology and Medicine
https://www.readbyqxmd.com/read/27889430/classification-of-teeth-in-cone-beam-ct-using-deep-convolutional-neural-network
#10
Yuma Miki, Chisako Muramatsu, Tatsuro Hayashi, Xiangrong Zhou, Takeshi Hara, Akitoshi Katsumata, Hiroshi Fujita
Dental records play an important role in forensic identification. To this end, postmortem dental findings and teeth conditions are recorded in a dental chart and compared with those of antemortem records. However, most dentists are inexperienced at recording the dental chart for corpses, and it is a physically and mentally laborious task, especially in large scale disasters. Our goal is to automate the dental filing process by using dental x-ray images. In this study, we investigated the application of a deep convolutional neural network (DCNN) for classifying tooth types on dental cone-beam computed tomography (CT) images...
November 12, 2016: Computers in Biology and Medicine
https://www.readbyqxmd.com/read/27836120/computationally-efficient-analysis-of-particle-transport-and-deposition-in-a-human-whole-lung-airway-model-part-ii-dry-powder-inhaler-application
#11
Arun V Kolanjiyil, Clement Kleinstreuer, Ruxana T Sadikot
Pulmonary drug delivery is becoming a favored route for administering drugs to treat both lung and systemic diseases. Examples of lung diseases include asthma, cystic fibrosis and chronic obstructive pulmonary disease (COPD) as well as respiratory distress syndrome (ARDS) and pulmonary fibrosis. Special respiratory drugs are administered to the lungs, using an appropriate inhaler device. Next to the pressurized metered-dose inhaler (pMDI), the dry powder inhaler (DPI) is a frequently used device because of the good drug stability and a minimal need for patient coordination...
November 3, 2016: Computers in Biology and Medicine
https://www.readbyqxmd.com/read/27838533/structuralizing-biomedical-abstracts-with-discriminative-linguistic-features
#12
Sejin Nam, Senator Jeong, Sang-Kyun Kim, Hong-Gee Kim, Victoria Ngo, Nansu Zong
OBJECTIVE: Nearly 75% of the abstracts in MEDLINE papers present in an unstructured format. This study aims to automate the reformatting of unstructured abstracts into the Introduction, Methods, Results, and Discussion (IMRAD) format. The quality of this reformatting relies on the features used in sentence classification. Therefore, we explored the most effective linguistic features in MEDLINE papers. METHODS: We constructed a feature set consisting of bag of words, linguistic features, grammatical features, and structural features...
November 2, 2016: Computers in Biology and Medicine
https://www.readbyqxmd.com/read/27825039/esophageal-stent-migration-testing-few-hypothesis-with-a-simplified-mathematical-model
#13
Marc Garbey, Remi Salmon, Vid Fikfak, Claude O Clerc
Esophageal stent placement has significantly improved the quality of life in patients with malignant as well as benign esophageal obstructing lesions. Despite its early success and rapid adoption, stent migration still occurs in as many as 30% of cases especially with fully covered stents. To date, few models of interaction between the stent and the esophageal wall have been published and these have only focused on the deployment of the stent or the static mechanical stress distribution of the stent material...
November 2, 2016: Computers in Biology and Medicine
https://www.readbyqxmd.com/read/27821265/tetrahedral-node-for-transmission-line-modeling-tlm-applied-to-bio-heat-transfer
#14
Hugo F M Milan, Kifle G Gebremedhin
Transmission-Line Modeling (TLM) is a numerical method used to solve complex and time-domain bio-heat transfer problems. In TLM, parallelepipeds are used to discretize three-dimensional problems. The drawback in using parallelepiped shapes is that instead of refining only the domain of interest, a large additional domain would also have to be refined, which results in increased computational time and memory space. In this paper, we developed a tetrahedral node for TLM applied to bio-heat transfer that does not have the drawback associated with the parallelepiped node...
October 31, 2016: Computers in Biology and Medicine
https://www.readbyqxmd.com/read/27825038/automated-characterization-of-fatty-liver-disease-and-cirrhosis-using-curvelet-transform-and-entropy-features-extracted-from-ultrasound-images
#15
U Rajendra Acharya, U Raghavendra, Hamido Fujita, Yuki Hagiwara, Joel Ew Koh, Tan Jen Hong, Vidya K Sudarshan, Anushya Vijayananthan, Chai Hong Yeong, Anjan Gudigar, Kwan Hoong Ng
Fatty liver disease (FLD) is reversible disease and can be treated, if it is identified at an early stage. However, if diagnosed at the later stage, it can progress to an advanced liver disease such as cirrhosis which may ultimately lead to death. Therefore, it is essential to detect it at an early stage before the disease progresses to an irreversible stage. Several non-invasive computer-aided techniques are proposed to assist in the early detection of FLD and cirrhosis using ultrasound images. In this work, we are proposing an algorithm to discriminate automatically the normal, FLD and cirrhosis ultrasound images using curvelet transform (CT) method...
October 29, 2016: Computers in Biology and Medicine
https://www.readbyqxmd.com/read/27810625/computationally-efficient-analysis-of-particle-transport-and-deposition-in-a-human-whole-lung-airway-model-part-i-theory-and-model-validation
#16
Arun V Kolanjiyil, Clement Kleinstreuer
Computational predictions of aerosol transport and deposition in the human respiratory tract can assist in evaluating detrimental or therapeutic health effects when inhaling toxic particles or administering drugs. However, the sheer complexity of the human lung, featuring a total of 16 million tubular airways, prohibits detailed computer simulations of the fluid-particle dynamics for the entire respiratory system. Thus, in order to obtain useful and efficient particle deposition results, an alternative modeling approach is necessary where the whole-lung geometry is approximated and physiological boundary conditions are implemented to simulate breathing...
October 27, 2016: Computers in Biology and Medicine
https://www.readbyqxmd.com/read/27810627/numerical-study-for-mhd-peristaltic-flow-in-a-rotating-frame
#17
T Hayat, Hina Zahir, Anum Tanveer, A Alsaedi
The aim of present investigation is to model and analyze the magnetohydrodynamic (MHD) peristaltic transport of Prandtl fluid in a channel with flexible walls. The whole system consisting of fluid and channel are in a rotating frame of reference with uniform angular velocity. Viscous dissipation in thermal equation is not ignored. The channel boundaries satisfy the convective conditions in terms of temperature. The arising complicated problems are reduced in solvable form using large wavelength and small Reynolds number assumptions...
October 22, 2016: Computers in Biology and Medicine
https://www.readbyqxmd.com/read/27810626/unsupervised-domain-adaptation-techniques-based-on-auto-encoder-for-non-stationary-eeg-based-emotion-recognition
#18
Xin Chai, Qisong Wang, Yongping Zhao, Xin Liu, Ou Bai, Yongqiang Li
In electroencephalography (EEG)-based emotion recognition systems, the distribution between the training samples and the testing samples may be mismatched if they are sampled from different experimental sessions or subjects because of user fatigue, different electrode placements, varying impedances, etc. Therefore, it is difficult to directly classify the EEG patterns with a conventional classifier. The domain adaptation method, which is aimed at obtaining a common representation across training and test domains, is an effective method for reducing the distribution discrepancy...
October 22, 2016: Computers in Biology and Medicine
https://www.readbyqxmd.com/read/27810624/developing-new-vo2max-prediction-models-from-maximal-submaximal-and-questionnaire-variables-using-support-vector-machines-combined-with-feature-selection
#19
Fatih Abut, Mehmet Fatih Akay, James George
Maximal oxygen uptake (VO2max) is an essential part of health and physical fitness, and refers to the highest rate of oxygen consumption an individual can attain during exhaustive exercise. In this study, for the first time in the literature, we combine the triple of maximal, submaximal and questionnaire variables to propose new VO2max prediction models using Support Vector Machines (SVM's) combined with the Relief-F feature selector to predict and reveal the distinct predictors of VO2max. For comparison purposes, hybrid models based on double combinations of maximal, submaximal and questionnaire variables have also been developed...
October 20, 2016: Computers in Biology and Medicine
https://www.readbyqxmd.com/read/27810622/generic-feature-learning-for-wireless-capsule-endoscopy-analysis
#20
Santi Seguí, Michal Drozdzal, Guillem Pascual, Petia Radeva, Carolina Malagelada, Fernando Azpiroz, Jordi Vitrià
The interpretation and analysis of wireless capsule endoscopy (WCE) recordings is a complex task which requires sophisticated computer aided decision (CAD) systems to help physicians with video screening and, finally, with the diagnosis. Most CAD systems used in capsule endoscopy share a common system design, but use very different image and video representations. As a result, each time a new clinical application of WCE appears, a new CAD system has to be designed from the scratch. This makes the design of new CAD systems very time consuming...
October 19, 2016: Computers in Biology and Medicine
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