Mechanical model of orthopaedic drilling for augmented-haptics-based training
In this study, augmented-haptic feedback is used to combine a physical object with virtual elements in order to simulate anatomic variability in bone. This requires generating levels of force/torque consistent with clinical bone drilling, which exceed the capabilities of commercially available haptic devices. Accurate total force generation is facilitated by a predictive model of axial force during simulated orthopaedic drilling. This model is informed by kinematic data collected while drilling into synthetic bone samples using an instrumented linkage attached to the orthopaedic drill. (Source: Computers in Biology and Medicine)
Source: Computers in Biology and Medicine - June 29, 2017 Category: Bioinformatics Authors: Ashkan Pourkand, Naghmeh Zamani, David Grow Source Type: research

A novel algorithm to detect glaucoma risk using texton and local configuration pattern features extracted from fundus images
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. (Source: Computers in Biology and Medicine)
Source: Computers in Biology and Medicine - June 29, 2017 Category: Bioinformatics Authors: U. Rajendra Acharya, Shreya Bat, Joel E.W. Koh, Sulatha V. Bhandary, Hojjat Adeli Source Type: research

Validation of a novel nonlinear black box Wiener System model for arterial pulse transmission
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. (Source: Computers in Biology and Medicine)
Source: Computers in Biology and Medicine - June 24, 2017 Category: Bioinformatics Authors: Amit M. Patel, John K-J. Li Source Type: research

A type-2 fuzzy data fusion approach for building reliable weighted protein interaction networks with application in protein complex detection
Detecting the protein complexes is an important task in analyzing the protein interaction network. Although many algorithms predict protein complexes in different ways, surveys on the interaction networks indicate that about 50 percent 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. (Sou...
Source: Computers in Biology and Medicine - June 22, 2017 Category: Bioinformatics Authors: Adele Mehranfar, Nasser Ghadiri, Morteza Kouhsar, Ashkan Golshani Source Type: research

Simultaneous ocular and muscle artifact removal from EEG data by exploiting diverse statistics
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. (Source: Computers in Biology and Medicine)
Source: Computers in Biology and Medicine - June 21, 2017 Category: Bioinformatics Authors: Xun Chen, Aiping Liu, Qiang Chen, Yu Liu, Liang Zou, Martin J. McKeown Source Type: research

Hyperspectral image analysis for rapid and accurate discrimination of bacterial infections: A benchmark study
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 inte...
Source: Computers in Biology and Medicine - June 21, 2017 Category: Bioinformatics Authors: Simone Arrigoni, Giovanni Turra, Alberto Signoroni Source Type: research

An Independent Active Contours Segmentation framework for bone micro-CT images
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 imag...
Source: Computers in Biology and Medicine - June 19, 2017 Category: Bioinformatics Authors: Vasileios Ch. Korfiatis, Simone Tassani, George K. Matsopoulos Source Type: research

Iterative variational mode decomposition based automated detection of glaucoma using fundus images
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 a iterative manner for image decomposition. (Source: Computers in Biology and Medicine)
Source: Computers in Biology and Medicine - June 19, 2017 Category: Bioinformatics Authors: Shishir Maheshwari, Ram Bilas Pachori, Vivek Kanhangad, Sulatha V. Bhandary, U. Rajendra Acharya Source Type: research

Editorial Board & Publication information
(Source: Computers in Biology and Medicine)
Source: Computers in Biology and Medicine - June 18, 2017 Category: Bioinformatics Source Type: research

Assessment of temporal predictive models for health care using a formal method
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. (Source: Computers in Biology and Medicine)
Source: Computers in Biology and Medicine - June 17, 2017 Category: Bioinformatics Authors: Ward van Breda, Mark Hoogendoorn, A.E. Eiben, Matthias Berking Source Type: research

A novel method to precisely detect apnea and hypopnea events by airflow and oximetry signals
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. (Source: Computers in Biology and Medicine)
Source: Computers in Biology and Medicine - June 17, 2017 Category: Bioinformatics Authors: Wu Huang, Bing Guo, Yan Shen, Xiangdong Tang Source Type: research

Improved boundary segmentation of skin lesions in high-frequency 3D ultrasound
In this article, we propose a segmentation algorithm for skin lesions in 3D high-frequency ultrasound images. The segmentation is done on melanoma and Basal-cell carcinoma tumors, the most common skin cancer types, and could be used for diagnosis and surgical excision planning in a clinical context. Compared with previously proposed algorithms, which tend to underestimate the size of the lesion, we propose two new boundary terms which provide significant improvements of the accuracy. The first is a probabilistic boundary expansion (PBE) term designed to broaden the segmented area at the boundaries, which uses the feature a...
Source: Computers in Biology and Medicine - June 15, 2017 Category: Bioinformatics Authors: B. Sciolla, P. Delachartre, L. Cowell, T. Dambry, B. Guibert Source Type: research

Noise detection on ECG based on agglomerative clustering of morphological features
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. (Source: Computers in Biology and Medicine)
Source: Computers in Biology and Medicine - June 14, 2017 Category: Bioinformatics Authors: Jo ão Rodrigues, David Belo, Hugo Gamboa Source Type: research

Computer – Aided training sensorimotor cortex functions in humans before the upper limb transplantation using virtual reality and sensory feedback
One of the biggest problems of upper limb transplantation is lack of certainty as to whether a patient will be able to control voluntary movements of transplanted hands. Based on findings of the recent research on brain cortex plasticity, a premise can be drawn that mental training supported with visual and sensory feedback can cause structural and functional reorganization of the sensorimotor cortex, which leads to recovery of function associated with the control of movements performed by the upper limbs. (Source: Computers in Biology and Medicine)
Source: Computers in Biology and Medicine - June 14, 2017 Category: Bioinformatics Authors: Marek Kurzynski, Anna Jaskolska, Jaroslaw Marusiak, Andrzej Wolczowski, Przemyslaw Bierut, Lukasz Szumowski, Jerzy Witkowski, Katarzyna Kisiel-Sajewicz Source Type: research

Automatic MPST-cut for segmentation of carpal bones from MR volumes
In the context of rheumatic diseases, several studies suggest that Magnetic Resonance Imaging (MRI) allows the detection of the three main signs of Rheumatoid Arthritis (RA) at higher sensitivities than available through conventional radiology. The rapid, accurate segmentation of bones is an essential preliminary step for quantitative diagnosis, erosion evaluation, and multi-temporal data fusion. In the present paper, a new, semi-automatic, 3D graph-based segmentation method to extract carpal bone data is proposed. (Source: Computers in Biology and Medicine)
Source: Computers in Biology and Medicine - June 14, 2017 Category: Bioinformatics Authors: Laura Gemme, Sonia Nardotto, Silvana G. Dellepiane Source Type: research