Chemotherapy-induced fatigue estimation using hidden Markov model
Publication date: Available online 15 November 2018Source: Biocybernetics and Biomedical EngineeringAuthor(s): Sina Ameli, Fazel Naghdy, David Stirling, Golshah Naghdy, Morteza AghmeshehAbstractChemotherapy-induced fatigue undermines the physical performance and alter gait behaviour of patients. In routine clinical oncology, there is not a well-established method to objectively assess the effects of chemotherapy-induced fatigue on gait characteristics. Clinical trials commonly use 6-min walking tests (6MWT) to assess the gait of patients. However, these studies only measure the distance that a patient can walk. The distanc...
Source: Biocybernetics and Biomedical Engineering - November 16, 2018 Category: Biomedical Engineering Source Type: research

Heart rate extraction from PPG signals using variational mode decomposition
Publication date: Available online 14 November 2018Source: Biocybernetics and Biomedical EngineeringAuthor(s): Hemant SharmaAbstractMonitoring of vital signs using the photoplethysmography (PPG) signal is desirable for the development of home-based healthcare systems in the aspect of feasibility, mobility, comfort, and cost-effectiveness of the PPG device. In this paper, a new technique based on the variational mode decomposition (VMD) for estimating heart rate (HR) from the PPG signal is proposed. The VMD decomposes an input PPG signal into a number of modes or sub-signals. Afterward, the modes which are dominantly influe...
Source: Biocybernetics and Biomedical Engineering - November 15, 2018 Category: Biomedical Engineering Source Type: research

Support vector machine classification of brain states exposed to social stress test using EEG-based brain network measures
In this study, the brain network states exposed to stress were monitored based on electroencephalography (EEG) measures extracted by complex network analysis. To this regard, 23 healthy male participants aged 18–28 were exposed to a stress test. EEG data and salivary cortisol level were recorded for three different conditions including before, right after, and 20 min after exposure to stress. Then, synchronization likelihood (SL) was calculated for the set of EEG data to construct complex networks, which are scale reduced datasets acquired from multi-channel signals. These networks with weighted connectivity mat...
Source: Biocybernetics and Biomedical Engineering - November 14, 2018 Category: Biomedical Engineering Source Type: research

Automatic mitosis detection in breast histopathology images using Convolutional Neural Network based deep transfer learning
Publication date: Available online 10 November 2018Source: Biocybernetics and Biomedical EngineeringAuthor(s): Beevi K. Sabeena, Madhu S. Nair, G.R. BinduAbstractThe exact measure of mitotic count is one of the crucial parameters in breast cancer grading and prognosis. Detection of mitosis in standard H & E stained histopathology images is challenging due to diffused intensities along object boundaries and shape variation in different stages of mitosis. This paper explores the feasibility of transfer learning for mitosis detection. A pre-trained Convolutional Neural Network is transformed by coupling random forest clas...
Source: Biocybernetics and Biomedical Engineering - November 11, 2018 Category: Biomedical Engineering Source Type: research

Gray-level co-occurrence matrix of Fourier synchro-squeezed transform for epileptic seizure detection
Publication date: Available online 6 November 2018Source: Biocybernetics and Biomedical EngineeringAuthor(s): Shamzin Mamli, Hashem KalbkhaniAbstractEpilepsy is a brain disorder that many persons of different ages in the world suffer from it. According to the world health organization, epilepsy is characterized by repetitive seizures and more electrical discharge in a group of brain neurons results in sudden physical actions. The aim of this paper is to introduce a new method to classify epileptic phases based on Fourier synchro-squeezed transform (FSST) of electroencephalogram (EEG) signals. FSST is a time-frequency (TF) ...
Source: Biocybernetics and Biomedical Engineering - November 7, 2018 Category: Biomedical Engineering Source Type: research

Computer-aided detection of mesial temporal sclerosis based on hippocampus and cerebrospinal fluid features in MR images
Publication date: Available online 28 October 2018Source: Biocybernetics and Biomedical EngineeringAuthor(s): Huiquan Wang, S. Nizam Ahmed, Mrinal MandalAbstractMesial temporal sclerosis (MTS) is the commonest brain abnormalities in patients with intractable epilepsy. Its diagnosis is usually performed by neuroradiologists based on visual inspection of magnetic resonance imaging (MRI) scans, which is a subjective and time-consuming process with inter-observer variability. In order to expedite the identification of MTS, an automated computer-aided method based on brain MRI characteristics is proposed in this paper. It inclu...
Source: Biocybernetics and Biomedical Engineering - October 29, 2018 Category: Biomedical Engineering Source Type: research

Accurate automated detection of congestive heart failure using eigenvalue decomposition based features extracted from HRV signals
This study aims to diagnose the CHF accurately using heart rate variability (HRV) signals. The HRV signals are non-stationary and nonlinear in nature. We have used eigenvalue decomposition of Hankel matrix (EVDHM) method to analyze the HRV signals. The lowest frequency component (LFC) and the highest frequency component (HFC) are extracted from the eigenvalue decomposed components of HRV signals. After that, the mean and standard deviation in time domain, mean frequency calculated from Fourier-Bessel series expansion, k-nearest neighbor (k-NN) entropy, and correntropy features are evaluated from the decomposed components. ...
Source: Biocybernetics and Biomedical Engineering - October 20, 2018 Category: Biomedical Engineering Source Type: research

Magnetic resonance imaging-based brain tumor grades classification and grading via convolutional neural networks and genetic algorithms
Publication date: Available online 18 October 2018Source: Biocybernetics and Biomedical EngineeringAuthor(s): Amin Kabir Anaraki, Moosa Ayati, Foad KazemiAbstractGliomas are the most common type of primary brain tumors in adults and their early detection is of great importance. In this paper, a method based on convolutional neural networks (CNNs) and genetic algorithm (GA) is proposed in order to noninvasively classify different grades of Glioma using magnetic resonance imaging (MRI). In the proposed method, the architecture (structure) of the CNN is evolved using GA, unlike existing methods of selecting a deep neural netw...
Source: Biocybernetics and Biomedical Engineering - October 19, 2018 Category: Biomedical Engineering Source Type: research

Assessment of despeckle filtering algorithms for segmentation of breast tumours from ultrasound images
Publication date: Available online 12 October 2018Source: Biocybernetics and Biomedical EngineeringAuthor(s): Kriti, Jitendra Virmani, Ravinder AgarwalAbstractIn the present work, the breast ultrasound images are pre-processed with various despeckle filtering algorithms to analyze the effect of despeckling on segmentation of benign and malignant breast tumours from ultrasound images. The despeckle filtering algorithms are broadly classified into eight categories namely local statistics based filters, fuzzy filters, Fourier filters, multiscale filters, non-linear iterative filters, total variation filters, non-local mean fi...
Source: Biocybernetics and Biomedical Engineering - October 14, 2018 Category: Biomedical Engineering Source Type: research

Detection of type-2 diabetes using characteristics of toe photoplethysmogram by applying support vector machine
Publication date: Available online 12 October 2018Source: Biocybernetics and Biomedical EngineeringAuthor(s): Neelamshobha Nirala, R. Periyasamy, B.K. Singh, Awanish KumarAbstractDiabetes mellitus (DM) is one of the most widespread and rapidly growing diseases. With its advancement, DM-related complications are also increasing. We used characteristic features of toe photoplethysmogram for the detection of type-2 DM using support vector machine (SVM). We collected toe PPG signal, from 58 healthy and 83 type-2 DM subjects. From each PPG signal 37 different features were extracted for further classification. To improve the pe...
Source: Biocybernetics and Biomedical Engineering - October 12, 2018 Category: Biomedical Engineering Source Type: research

Design factors of lumbar pedicle screws under bending load: A finite element analysis
In this study, 84 finite element (FE) models of the pedicle screw were generated having 7 pitch lengths, 3 major diameters, 2 thread profiles and 2 geometries. The assembly of pedicle screw and CT scan based half section FE model of 4th lumbar vertebra was loaded with a 200 N force on the screw head which is equivalent to a bending moment of 11 Nm.With triangular thread profile and cylindrical geometry, for 300% increase in pitch length (1 mm to 4 mm), von Mises stress in screw and von Mises strain in bone increased by 65% and 117% respectively, for a 26% decrease in major diameter (7.6 mm to 5.6&n...
Source: Biocybernetics and Biomedical Engineering - October 12, 2018 Category: Biomedical Engineering Source Type: research

Granular filter in medical image noise suppression and edge preservation
Publication date: Available online 6 October 2018Source: Biocybernetics and Biomedical EngineeringAuthor(s): Wieclawek Wojciech, Pietka EwaAbstractAn alternative non-linear filtering technique for medical image denoising while preserving edge is introduced. Two different variants of the approach i.e. crisp and fuzzy are developed. The solution is demonstrated based on US breast images as well as CT studies and gave promising results in comparison with commonly known and popular filtering techniques (i.e. spatial averaging and median, bilateral filter, anisotropic diffusion). Many different measures were used to evaluate th...
Source: Biocybernetics and Biomedical Engineering - October 7, 2018 Category: Biomedical Engineering Source Type: research

Extraction of fuzzy rules at different concept levels related to image features of mammography for diagnosis of breast cancer
Publication date: Available online 27 September 2018Source: Biocybernetics and Biomedical EngineeringAuthor(s): Mahsa Goudarzi, Keivan MaghooliAbstractMammography is an inexpensive and non-invasive method through which one can diagnose breast cancer in its early stages. As these images need interpretation by a radiologist, this may develop some problems due to fatigue, repetition, and need for a great deal of attention to details and other factors. Thus, a method capable of diagnosing breast cancer should be employed to help physicians in this regard.In this paper, The mini Mammographic Image Analysis Society (mini-MIAS) d...
Source: Biocybernetics and Biomedical Engineering - October 4, 2018 Category: Biomedical Engineering Source Type: research

Automatic method for assessment of proliferation index in digital images of DLBCL tissue section
Publication date: Available online 29 September 2018Source: Biocybernetics and Biomedical EngineeringAuthor(s): Ryszard S. Gomolka, Anna Korzynska, Krzysztof Siemion, Karolina Gabor-Siatkowska, Wlodzimierz KlonowskiAbstractDiffuse large B-cell lymphoma (DLBCL) is a fast-growing and aggressive neoplasm originating from B lymphocytes. Evaluation of proliferation index (PI) based on Ki67 immunohistochemical nuclear staining is used to distinguish proliferating (immunopositive) from nonproliferating (immunonegative) lymphoma cells. Human interpretation of PI varies and is time-consuming, therefore automatic computer-assisted a...
Source: Biocybernetics and Biomedical Engineering - October 4, 2018 Category: Biomedical Engineering Source Type: research

Geometrical parameters of the mandible in 3D CBCT imaging
Publication date: Available online 1 October 2018Source: Biocybernetics and Biomedical EngineeringAuthor(s): A.M. Ryniewicz, W. Ryniewicz, Ł. BojkoAbstractThe aim of the study is to report on a method for the measurement and analysis of the accuracy in mapping the shape of the mandible spatially modeled based on cone beam imaging. To achieve this goal, the geometrical determinants of the mandible shape were identified; in addition, the accuracy of their cone beam in computer tomography (CBCT) images was verified. The latter – verification of images – was based on reference measures made by a coordinate measuri...
Source: Biocybernetics and Biomedical Engineering - October 4, 2018 Category: Biomedical Engineering Source Type: research

Detection of Modic changes in MR images of spine using local binary patterns
ConclusionA novel approach to identify MC in vertebrae by exploiting textural features is proposed. This shall assist radiologists in detecting abnormalities and in treatment planning. (Source: Biocybernetics and Biomedical Engineering)
Source: Biocybernetics and Biomedical Engineering - October 4, 2018 Category: Biomedical Engineering Source Type: research

Evaluation of filters over different stimulation models in evoked potentials
In this study, data were recorded from university students whose age between 18 and 25 years with visual and auditory stimuli. Discrete wavelet transforms, singular spectrum analysis, empirical mode decomposition and discrete Fourier transform based filters were used and compared with raw data on classification performance. Higuchi fractal dimension and entropy features were extracted from EEG; P300 features were extracted from EP signals. Classification was applied with support vector machines. All filtered data gave better scores than raw data. Empirical mode decomposition (EMD) and Fourier-based filter yielded lower res...
Source: Biocybernetics and Biomedical Engineering - September 18, 2018 Category: Biomedical Engineering Source Type: research

Statistical methods for constructing gestational age-related charts for fetal size and pregnancy dating using longitudinal data
This article suggests how this method can be extended to longitudinal data using fractional polynomials in linear mixed effect regression. The presented approach includes maximum likelihood estimation for fitting first- and second-order fractional polynomial models, and multimodel inference using Akaike's information criterion and related tools as a suitable strategy for model selection. Finally, an example of the suggested approach is presented. (Source: Biocybernetics and Biomedical Engineering)
Source: Biocybernetics and Biomedical Engineering - September 18, 2018 Category: Biomedical Engineering Source Type: research

Fuzzy genetic-based noise removal filter for digital panoramic X-ray images
Publication date: Available online 5 September 2018Source: Biocybernetics and Biomedical EngineeringAuthor(s): Mehravar Rafati, Fateme Farnia, Mahdi Erfanian Taghvaei, Ali Mohammad NickfarjamAbstractThis paper proposed a novel fuzzy genetic-based noise removal filter and surveyed the gain of popular filters for noise removal in the digital orthopantomography (OPG) images. The proposed filter is a non-invasive technique for attaining sub-clinical information from the areas of interest in each tooth, both jaws and maxillofacial.The proposed Poisson removal filter combines 4th-order partial differential equations (PDE), total...
Source: Biocybernetics and Biomedical Engineering - September 6, 2018 Category: Biomedical Engineering Source Type: research

A hybrid gene selection method for microarray recognition
Publication date: Available online 5 September 2018Source: Biocybernetics and Biomedical EngineeringAuthor(s): Alok Kumar Shukla, Pradeep Singh, Manu VardhanAbstractDNA microarray data is expected to be a great help in the development of efficient diagnosis and tumor classification. However, due to the small number of instances compared to a large number of genes, many of the computational learning methods encounter difficulties to select the low subgroups. In order to select significant genes from the high dimensional data for tumor classification, nowadays, several researchers are exploring microarray data using various ...
Source: Biocybernetics and Biomedical Engineering - September 5, 2018 Category: Biomedical Engineering Source Type: research

Towards in-vivo assessment of fluorescence lifetime: Imaging using time-gated intensified CCD camera
Publication date: Available online 3 September 2018Source: Biocybernetics and Biomedical EngineeringAuthor(s): Piotr Sawosz, Stanislaw Wojtkiewicz, Michal Kacprzak, Elzbieta Zieminska, Magdalena Morawiec, Roman Maniewski, Adam LiebertAbstractA novel technique for imaging of a small animal with application of time-gated intensified CCD camera was proposed. The time-resolved method based on emission of picosecond light pulses and detection of the light penetrating in tissues was applied. In this technique, the fluorescence photons, excited in the dye circulating in the tissue, that diffusely penetrate in the optically turbid...
Source: Biocybernetics and Biomedical Engineering - September 5, 2018 Category: Biomedical Engineering Source Type: research

Fast statistical model-based classification of epileptic EEG signals
Publication date: Available online 21 August 2018Source: Biocybernetics and Biomedical EngineeringAuthor(s): Antonio Quintero-Rincón, Marcelo Pereyra, Carlos D’Giano, Marcelo Risk, Hadj BatatiaAbstractThis paper presents a supervised classification method to accurately detect epileptic brain activity in real-time from electroencephalography (EEG) data. The proposed method has three main strengths: it has low computational cost, making it suitable for real-time implementation in EEG devices; it performs detection separately for each brain rhythm or EEG spectral band, following the current medical practices; and...
Source: Biocybernetics and Biomedical Engineering - August 21, 2018 Category: Biomedical Engineering Source Type: research

Automated fuzzy optic disc detection algorithm using branching of vessels and color properties in fundus images
This study is comprised of two successive fundamental steps. At the first step, an algorithm finding the approximate convergent point of the vessels is used in order to roughly localize OD. At the second step, three new features are suggested and a fuzzy logic controller (FLC) whose input membership functions are designed based on these features is proposed. The proposed method is applied to the DRIVE, STARE, DIARETDB0 and DIRETDB1 datasets and the obtained results validate the improvement in the performance by attaining success rate of 100%, 91,35%, 90% and 100% respectively and detecting OD centers and contours precisely...
Source: Biocybernetics and Biomedical Engineering - August 20, 2018 Category: Biomedical Engineering Source Type: research

Extracting tumor in MR brain and breast image with Kapur’s entropy based Cuckoo Search Optimization and morphological reconstruction filters
Publication date: Available online 20 August 2018Source: Biocybernetics and Biomedical EngineeringAuthor(s): R. Sumathi, M. Venkatesuslu, Sridhar P. Arjunan (Source: Biocybernetics and Biomedical Engineering)
Source: Biocybernetics and Biomedical Engineering - August 20, 2018 Category: Biomedical Engineering Source Type: research

Eye and EEG activity markers for visual comfort level of images
Publication date: Available online 13 August 2018Source: Biocybernetics and Biomedical EngineeringAuthor(s): Vytautas Abromavičius, Artūras SerackisAbstractDepth perception by binocular cues is based on the matching of image features from one retina with corresponding elements from the second retina. However, high disparities are related to the higher visual discomfort levels and may cause the eye fatigue during extended stereoscopic perception time. The goal of the investigation was to find a set of measurable features for stereoscopic image visual comfort level prediction. The investigation involved gaze, pupillometric...
Source: Biocybernetics and Biomedical Engineering - August 13, 2018 Category: Biomedical Engineering Source Type: research

A miniature and low-cost glucose measurement system
Publication date: Available online 8 August 2018Source: Biocybernetics and Biomedical EngineeringAuthor(s): S.D. Adams, E. Buber, T.C. Bicak, Y. Yagci, L. Toppare, A. Kaynak, A.Z. KouzaniAbstractOne of the bottlenecks in widespread adoption of biosensors is the large and sophisticated bioanalytical system that is required to perform signal transduction and analysis. A miniaturized bioanalytical system facilitates biosensing techniques that are portable, easy to handle and inexpensive for fast and reliable measurements of biochemical species. Thus, downscaling the bioanalytical system has become a highly active research are...
Source: Biocybernetics and Biomedical Engineering - August 9, 2018 Category: Biomedical Engineering Source Type: research

Modeling the 2D space of emotions based on the poincare plot of heart rate variability signal
In this study, the two-dimensional space-based emotion model was introduced on the basis of Poincare's two-dimensional plot of the signal of heart rate variability. Four main colors of psychology, blue, red, green, and yellow were used as a stimulant of emotion, and the ECG signals from 70 female students were recorded. Using extracted features of Poincare plot and heart rate asymmetry, two tree based models estimated the levels of arousal and valence with 0.05 mean square errors, determined an appropriate estimation of these two parameters of emotion. In the next stage of the study, four different emotions mean pleasure, ...
Source: Biocybernetics and Biomedical Engineering - August 3, 2018 Category: Biomedical Engineering Source Type: research

RASIT: Region shrinking based accurate segmentation of inflammatory areas from thermograms
Publication date: Available online 3 August 2018Source: Biocybernetics and Biomedical EngineeringAuthor(s): Bardhana Shawli, Kanti Bhowmika Mrinal, Debnatha Tathagata, Debotosh BhattacharjeeAbstractEffective segmentation of thermal images reflecting the inflamed region in human body to assist medical diagnosis is a challenging task. In this paper we propose a method for thermal image segmentation, named as “Region shrinking based Accurate Segmentation of Inflammatory areas from Thermograms”, in short RASIT. The method comprising of four steps encompassing thermal image contextual electrostatic force extraction,...
Source: Biocybernetics and Biomedical Engineering - August 3, 2018 Category: Biomedical Engineering Source Type: research

Formulation and statistical evaluation of an automated algorithm for locating small bowel tumours in wireless capsule endoscopy
Publication date: Available online 31 July 2018Source: Biocybernetics and Biomedical EngineeringAuthor(s): A. Jagadeesan, J. SivaramanAbstractWireless capsule endoscopy (WCE) is an imaging modality which is highly reliable in the diagnosis of small bowel tumors. But locating the frames carrying tumors manually from the lengthy WCE is cumbersome and time consuming. A simple algorithm for the automated detection of tumorous frames from WCE is proposed in this work. In the proposed algorithm, local binary pattern (LBP) of the contrast enhanced green channel is used as the textural descriptor of the WCE frames. The features em...
Source: Biocybernetics and Biomedical Engineering - July 31, 2018 Category: Biomedical Engineering Source Type: research

Glossokinetic potential based tongue–machine interface for 1-D extraction using neural networks
This study may serve disabled people to control assistive devices in natural, unobtrusive, speedy and reliable manner. Moreover, it is expected that GKP-based TMI could be a collaboration channel for traditional electroencephalography (EEG)-based brain computer interfaces which have significant inadequacies arisen from the EEG signals. (Source: Biocybernetics and Biomedical Engineering)
Source: Biocybernetics and Biomedical Engineering - July 31, 2018 Category: Biomedical Engineering Source Type: research

Validation of Emotiv EPOC+ for extracting ERP correlates of emotional face processing
Publication date: Available online 27 July 2018Source: Biocybernetics and Biomedical EngineeringAuthor(s): Krzysztof Kotowski, Katarzyna Stapor, Jacek Leski, Marian KotasAbstractThe article presents our proposed adaptation of the commercially available Emotiv EPOC+ EEG headset for neuroscience research based on event-related brain potentials (ERP). It solves Emotiv EPOC+ synchronization problems (common to most low-cost systems) by applying our proposed stimuli marking circuit. The second goal was to check the capabilities of our modification in neuroscience experiments on emotional face processing. Results of our experime...
Source: Biocybernetics and Biomedical Engineering - July 28, 2018 Category: Biomedical Engineering Source Type: research

Predicting the success of wart treatment methods using decision tree based fuzzy informative images
This study provides a method for simple and more accurate interpretation of rules for medical experts. The success of treatment methods is now predictable as a percentage. (Source: Biocybernetics and Biomedical Engineering)
Source: Biocybernetics and Biomedical Engineering - July 18, 2018 Category: Biomedical Engineering Source Type: research

The ADHD effect on the actions obtained from the EEG signals
In this study, we considered the EEG signals as a biotic process according to these opposites and examined the ADHD effect on the brain activity by defining the dual sets of transitions between states in the complement plots of quantized EEG segments. The results of this study generally indicated that the complement plots of quantized EEG signal have a surprising regularity similar to the Mandala patterns compared to the chaotic processes. These results also indicated that the probability of occurrence of dual sets in the complement plots of ADHD children was averagely different (p 
Source: Biocybernetics and Biomedical Engineering - July 10, 2018 Category: Biomedical Engineering Source Type: research

Bayesian HCS-based multi-SVNN: A classification approach for brain tumor segmentation and classification using Bayesian fuzzy clustering
Publication date: 2018Source: Biocybernetics and Biomedical Engineering, Volume 38, Issue 3Author(s): A. Ratna Raju, P. Suresh, R. Rajeswara RaoAbstractBrain tumor segmentation and classification is the interesting area for differentiating the tumerous and the non-tumerous cells in the brain and to classify the tumerous cells for identifying its level. The conventional methods lack the automatic classification and they consumed huge time and are ineffective in decision-making. To overcome the challenges faced by the conventional methods, this paper proposes the automatic method of classification using the Harmony-Crow Sear...
Source: Biocybernetics and Biomedical Engineering - July 10, 2018 Category: Biomedical Engineering Source Type: research

Object detection based on deep learning for urine sediment examination
Publication date: 2018Source: Biocybernetics and Biomedical Engineering, Volume 38, Issue 3Author(s): Yixiong Liang, Zhihong Tang, Meng Yan, Jianfeng LiuAbstractUrine sediment examination (USE) is an important topic in kidney disease analysis and it is often the prerequisite for subsequent diagnostic procedures. We propose DFPN(Feature Pyramid Network with DenseNet) method to overcome the problem of class confusion in the USE images that it is hard to be solved by baseline model which is the state-of-the-art object detection model FPN with RoIAlign pooling. We explored the importance of two parts of baseline model for the ...
Source: Biocybernetics and Biomedical Engineering - July 10, 2018 Category: Biomedical Engineering Source Type: research

Representation learning-based unsupervised domain adaptation for classification of breast cancer histopathology images
Publication date: 2018Source: Biocybernetics and Biomedical Engineering, Volume 38, Issue 3Author(s): Pendar Alirezazadeh, Behzad Hejrati, Alireza Monsef-Esfahani, Abdolhossein FathiAbstractBreast cancer has high incidence rate compared to the other cancers among women. This disease leads to die if it does not diagnosis early. Fortunately, by means of modern imaging procedure such as MRI, mammography, thermography, etc., and computer systems, it is possible to diagnose all kind of breast cancers in a short time. One type of BC images is histology images. They are obtained from the entire cut-off texture by use of digital c...
Source: Biocybernetics and Biomedical Engineering - July 10, 2018 Category: Biomedical Engineering Source Type: research

Discriminant analysis of neural style representations for breast lesion classification in ultrasound
Publication date: 2018Source: Biocybernetics and Biomedical Engineering, Volume 38, Issue 3Author(s): Michał ByraAbstractUltrasound imaging is widely used for breast lesion differentiation. In this paper we propose a neural transfer learning method for breast lesion classification in ultrasound. As reported in several papers, the content and the style of a particular image can be separated with a convolutional neural network. The style, coded by the Gram matrix, can be used to perform neural transfer of artistic style. In this paper we extract the neural style representations of malignant and benign breast lesions using t...
Source: Biocybernetics and Biomedical Engineering - July 10, 2018 Category: Biomedical Engineering Source Type: research

Automatic detection of tuberculosis bacilli from microscopic sputum smear images using deep learning methods
Publication date: 2018Source: Biocybernetics and Biomedical Engineering, Volume 38, Issue 3Author(s): Rani Oomman Panicker, Kaushik S. Kalmady, Jeny Rajan, M.K. SabuAbstractAn automatic method for the detection of Tuberculosis (TB) bacilli from microscopic sputum smear images is presented in this paper. According to WHO, TB is the ninth leading cause of death all over the world. There are various techniques to diagnose TB, of which conventional microscopic sputum smear examination is considered to be the gold standard. However, the aforementioned method of diagnosis is time intensive and error prone, even in experienced ha...
Source: Biocybernetics and Biomedical Engineering - July 10, 2018 Category: Biomedical Engineering Source Type: research

Estimation of severity level of non-proliferative diabetic retinopathy for clinical aid
Publication date: 2018Source: Biocybernetics and Biomedical Engineering, Volume 38, Issue 3Author(s): Jaskirat Kaur, Deepti MittalAbstractDiabetic retinopathy, a symptomless complication of diabetes, is one of the significant causes of vision impairment in the world. The early detection and diagnosis can reduce the occurrence of severe vision loss due to diabetic retinopathy. The diagnosis of diabetic retinopathy depends on the reliable detection and classification of bright and dark lesions present in retinal fundus images. Therefore, in this work, reliable segmentation of lesions has been performed using iterative cluste...
Source: Biocybernetics and Biomedical Engineering - July 10, 2018 Category: Biomedical Engineering Source Type: research

Editorial Board
Publication date: 2018Source: Biocybernetics and Biomedical Engineering, Volume 38, Issue 2Author(s): (Source: Biocybernetics and Biomedical Engineering)
Source: Biocybernetics and Biomedical Engineering - July 10, 2018 Category: Biomedical Engineering Source Type: research

Comparative assessment of texture features for the identification of cancer in ultrasound images: a review
Publication date: 2018Source: Biocybernetics and Biomedical Engineering, Volume 38, Issue 2Author(s): Oliver Faust, U. Rajendra Acharya, Kristen M. Meiburger, Filippo Molinari, Joel E.W. Koh, Chai Hong Yeong, Pailin Kongmebhol, Kwan Hoong NgAbstractIn this paper, we review the use of texture features for cancer detection in Ultrasound (US) images of breast, prostate, thyroid, ovaries and liver for Computer Aided Diagnosis (CAD) systems. This paper shows that texture features are a valuable tool to extract diagnostically relevant information from US images. This information helps practitioners to discriminate normal from ab...
Source: Biocybernetics and Biomedical Engineering - July 10, 2018 Category: Biomedical Engineering Source Type: research

Review on plantar data analysis for disease diagnosis
Publication date: 2018Source: Biocybernetics and Biomedical Engineering, Volume 38, Issue 2Author(s): Julian Andres Ramirez-Bautista, Antonio Hernández-Zavala, Silvia L. Chaparro-Cárdenas, Jorge A. Huerta-RuelasAbstractForce distribution on foot surface allows to understand the human mechanical behavior, providing detailed information for the evaluation of foot alterations. In diagnosis for diseases related to plantar pathologies, there are many devices for plantar pressure measurement, and corresponding algorithms for data analyzing, providing medical tools for assisting in treatment, early detection, and th...
Source: Biocybernetics and Biomedical Engineering - July 10, 2018 Category: Biomedical Engineering Source Type: research

Entropies for automated detection of coronary artery disease using ECG signals: A review
Publication date: 2018Source: Biocybernetics and Biomedical Engineering, Volume 38, Issue 2Author(s): Udyavara Rajendra Acharya, Yuki Hagiwara, Joel En Wei Koh, Shu Lih Oh, Jen Hong Tan, Muhammad Adam, Ru San TanAbstractCoronary artery disease (CAD) develops when coronary arteries are unable to supply oxygen-rich blood to the heart due to the accumulation of cholesterol plaque on the inner walls of the arteries. Chronic insufficient blood flow leads to the complications, including angina and heart failure. In addition, acute plaque rupture may lead to vessel occlusion, causing a heart attack. Thus, it is encouraged to have...
Source: Biocybernetics and Biomedical Engineering - July 10, 2018 Category: Biomedical Engineering Source Type: research

An epileptic seizure detection system based on cepstral analysis and generalized regression neural network
This study introduces a new and effective epileptic seizure detection system based on cepstral analysis utilizing generalized regression neural network for classifying electroencephalogram (EEG) recordings. The EEG recordings are obtained from an open database which has been widely studied with many different combinations of feature extraction and classification techniques. Cepstral analysis technique is mainly used for speech recognition, seismological problems, mechanical part tests, etc. Utility of cepstral analysis based features in EEG signal classification is explored in the paper. In the proposed study, mel frequenc...
Source: Biocybernetics and Biomedical Engineering - July 10, 2018 Category: Biomedical Engineering Source Type: research

A segment-wise reconstruction method based on bidirectional long short term memory for Power Line Interference suppression
In this study, we propose a novel segment-wise reconstruction method to suppress the PLI in biomedical signals based on the Bidirectional Recurrent Neural Networks with Long Short Term Memory (Bi-LSTM). Experiments are conducted on both synthetic and real signals, and quantitative comparisons are made with a traditional IIR notch filter and two state-of-the-art methods in the literature. The results show that by our method, the output Signal-to-Noise Ratio (SNR) is improved by more than 7 dB and the settling time for step response is reduced to 0.09 s on average. The results also demonstrate that our method has e...
Source: Biocybernetics and Biomedical Engineering - July 10, 2018 Category: Biomedical Engineering Source Type: research

Numerical simulations of the pulsatile blood flow in the different types of arterial fenestrations: Comparable analysis of multiple vascular geometries
Publication date: 2018Source: Biocybernetics and Biomedical Engineering, Volume 38, Issue 2Author(s): Zbigniew Tyfa, Damian Obidowski, Piotr Reorowicz, Ludomir Stefańczyk, Jan Fortuniak, Krzysztof JóźwikAbstractIn medical terms, fenestration stands for an anomaly within the circulatory system in which the blood vessel lumen is divided into two separate channels that rejoin in the distal part of this vessel. The primary objective of this research was to analyze the impact of the left vertebral artery (LVA) and basilar artery (BA) fenestrations on the blood flow characteristics in their regions and downstream, in th...
Source: Biocybernetics and Biomedical Engineering - July 10, 2018 Category: Biomedical Engineering Source Type: research

Use of the surface electromyography for a quantitative trend validation of estimated muscle forces
Publication date: 2018Source: Biocybernetics and Biomedical Engineering, Volume 38, Issue 2Author(s): Magdalena Żuk, Małgorzata Syczewska, Celina PezowiczAbstractSurface EMG is a non-invasive measurement of an individual muscle activity and it can be used as the indirect form of a simulated muscle forces validation. The quantitative curves comparison has some potential, which has not been fully exploited yet [13]. The purpose of current study was to quantitatively compare muscle forces predicted using musculoskeletal models to measured surface electromyography signals. A metrics based on correlation and an electromechani...
Source: Biocybernetics and Biomedical Engineering - July 10, 2018 Category: Biomedical Engineering Source Type: research

Detection of valvular heart diseases using impedance cardiography ICG
Publication date: 2018Source: Biocybernetics and Biomedical Engineering, Volume 38, Issue 2Author(s): Souhir Chabchoub, Sofienne Mansouri, Ridha Ben SalahAbstractImpedance cardiography (ICG) is a simple, non-invasive and cost effective tool for monitoring hemodynamic parameters. It has been successfully used to diagnose several cardiovascular diseases, like the heart failure and myocardial infarction. In particular, valvular heart disease (VHD) is characterized by the affection of one or more heart valves: mitral, aortic, tricuspid or pulmonary valves and it is usually diagnosed using the Doppler echocardiography. However,...
Source: Biocybernetics and Biomedical Engineering - July 10, 2018 Category: Biomedical Engineering Source Type: research

Nonsubsampled shearlet domain fusion techniques for CT–MR neurological images using improved biological inspired neural model
Publication date: 2018Source: Biocybernetics and Biomedical Engineering, Volume 38, Issue 2Author(s): Deep GuptaAbstractThe fusion of multimodality medical images performs a very crucial role in the clinical diagnosis, analysis and the treatment of especially in critical diseases. It is considered as an assisted approach for the radiologist by providing the composite images having significant diagnostic information acquired from the source images. The main purpose of this work is to develop an efficient framework for fusing the multimodal medical images. Three different fusion techniques are proposed in this paper that pre...
Source: Biocybernetics and Biomedical Engineering - July 10, 2018 Category: Biomedical Engineering Source Type: research

Denoising of Electrocardiogram (ECG) signal by using empirical mode decomposition (EMD) with non-local mean (NLM) technique
Publication date: 2018Source: Biocybernetics and Biomedical Engineering, Volume 38, Issue 2Author(s): Shailesh Kumar, Damodar Panigrahy, P.K. SahuAbstractIn this paper, the investigation on effectiveness of the empirical mode decomposition (EMD) with non-local mean (NLM) technique by using the value of differential standard deviation for denoising of ECG signal is performed. Differential standard deviation is calculated for collecting information related to the input noise so that appropriate formation in EMD and NLM framework can be performed. EMD framework in the proposed methodology is used for reduction of the noise fr...
Source: Biocybernetics and Biomedical Engineering - July 10, 2018 Category: Biomedical Engineering Source Type: research