Biocybernetics and Biomedical Engineering This is an RSS file. You can use it to subscribe to this data in your favourite RSS reader or to display this data on your own website or blog.

Adaptive shrinkage on dual-tree complex wavelet transform for denoising real-time MR images
Publication date: Available online 17 November 2018Source: Biocybernetics and Biomedical EngineeringAuthor(s): V.R. Simi, Damodar Reddy EdlaAbstractPerformance of denoising filters which are based on the principle of wavelet thresholding greatly depends upon selection of the threshold value. An objective method is proposed in this paper for computing the optimum value of threshold in DTCWT based denoising. At optimum threshold, annoying intensity transitions of pixels in the homogeneous regions of the images, contributed by noise get completely suppressed and the true edges remain unaffected. For finding optimum value of t...
Source: Biocybernetics and Biomedical Engineering - November 17, 2018 Category: Biomedical Engineering Source Type: research

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 matrice...
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 classifi...
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