A new deformation simulation algorithm for elastic-plastic objects based on splat primitives
To achieve high computational efficiency and realistic visual effects, a new simulation algorithm for soft tissue deformation, which is based on a shape-matching scheme using splat primitives, is presented for interactive real-time applications, such as surgery simulation and video games. The most important novelty of the proposed approach lies in the fact that surface splats instead of points are employed in the computation of the deformation and fracturing of an elastic-plastic object. By controlling the sampling density and automatically adjusting the size of the circular splats, the surface of the simulated object can ...
Source: Computers in Biology and Medicine - February 19, 2017 Category: Bioinformatics Authors: Yanni Zou, Peter X. Liu Source Type: research
Identification of SNP-SNP interaction for chronic dialysis patients
This study proposes an effective algorithm named dynamic center particle swarm optimization k-nearest neighbors (DCPSO-KNN) to detect the SNP-SNP interaction. DCPSO-KNN uses dynamic center particle swarm optimization (DCPSO) to generate SNP combinations with a fitness function designed using the KNN method and statistical verification. (Source: Computers in Biology and Medicine)
Source: Computers in Biology and Medicine - February 15, 2017 Category: Bioinformatics Authors: Cheng-Hong Yang, Zi-Jie Weng, Li-Yeh Chuang, Cheng-San Yang Source Type: research
Analysis of the sEMG/Force Relationship using HD-sEMG Technique and Data Fusion: A Simulation Study
In this study, we present a global investigation of the factors governing the shape of this relationship. Accordingly, we conducted a focused sensitivity analysis of the sEMG/force relationship form with respect to neural, functional and physiological parameters variation. (Source: Computers in Biology and Medicine)
Source: Computers in Biology and Medicine - February 13, 2017 Category: Bioinformatics Authors: Mariam Al Harrach, Vincent Carriou, Sofiane Boudaoud, Jeremy Laforet, Frederic Marin Source Type: research
An Interactive Medical Image Segmentation Framework Using Iterative Refinement
Segmentation is often performed on medical images for identifying diseases in clinical evaluation. Hence it has become one of the major research areas. Conventional image segmentation techniques are unable to provide satisfactory segmentation results for medical images as they contain irregularities. They need to be pre-processed before segmentation. In order to obtain the most suitable method for medical image segmentation, we propose MIST (Medical Image Segmentation Tool), a two stage algorithm. (Source: Computers in Biology and Medicine)
Source: Computers in Biology and Medicine - February 11, 2017 Category: Bioinformatics Authors: Pratik Kalshetti, Manas Bundele, Parag Rahangdale, Dinesh Jangra, Chiranjoy Chattopadhyay, Gaurav Harit, Abhay Elhence Source Type: research
Automated Diagnosis of Congestive Heart Failure Using Dual Tree Complex Wavelet Transform and Statistical Features Extracted from 2 Seconds of ECG Signals
Identification of alarming features in the electrocardiogram (ECG) signal is extremely significant for the prediction of congestive heart failure (CHF). ECG signal analysis carried out using computer-aided techniques can speed up the diagnosis process and aid in the proper management of CHF patients. Therefore, in this work, dual tree complex wavelets transform (DTCWT)-based methodology is proposed for an automated identification of ECG signals exhibiting CHF from normal. In the experiment, we have performed a DTCWT on ECG segments of 2seconds duration up to six levels to obtain the coefficients. (Source: Computers in Biology and Medicine)
Source: Computers in Biology and Medicine - February 6, 2017 Category: Bioinformatics Authors: Vidya K Sudarshan, U Rajendra Acharya, Oh Shu Lih, Muhammad Adam, Tan Jen Hong, Chua Kuang Chua, Chua Kok Poo, Tan Ru San Source Type: research
Ontology-based Automatic Identification of Public Health-Related Turkish Tweets
Social media analysis, such as the analysis of tweets, is a promising research topic for tracking public health concerns including epidemics. In this paper, we present an ontology-based approach to automatically identify public health-related Turkish tweets. The system is based on a public health ontology that we have constructed through a semi-automated procedure. The ontology concepts are expanded through a linguistically motivated relaxation scheme as the last stage of ontology development, before being integrated into our system to increase its coverage. (Source: Computers in Biology and Medicine)
Source: Computers in Biology and Medicine - February 3, 2017 Category: Bioinformatics Authors: Emine Ela K üçük, Kürşad Yapar, Dilek Küçük, Doğan Küçük Source Type: research
Development of an Updated Normative Data Table for Hand Grip and Pinch Strength: A Pilot Study
Pilot cross-sectional clinical measurement. (Source: Computers in Biology and Medicine)
Source: Computers in Biology and Medicine - January 31, 2017 Category: Bioinformatics Authors: Camilla C. Larson, Zhan Ye Source Type: research
Efficient Blood Flow Visualization using Flowline Extraction and Opacity Modulation based on Vascular Structure Analysis
With the recent advances regarding the acquisition and simulation of blood flow data, blood flow visualization has been widely used in medical imaging for the diagnosis and treatment of pathological vessels. In this paper, we present a novel method for the visualization of the blood flow in vascular structures. The vessel inlet or outlet is first identified using the orthogonality metric between the normal vectors of the flow velocity and vessel surface. Then, seed points are generated on the identified inlet or outlet by Poisson disk sampling. (Source: Computers in Biology and Medicine)
Source: Computers in Biology and Medicine - January 30, 2017 Category: Bioinformatics Authors: Ohjae Kwon, Jeongjin Lee, Bohyoung Kim, Juneseuk Shin, Yeong-Gil Shin Source Type: research
An Integrative Framework for 3D Cobb Angle Measurement on CT Images
Objective: Measuring the Cobb angle on computed tomography (CT) images remains a challenging but requisite task for clinical diagnoses of scoliosis. Traditionally, clinical practitioners resort to manual demarcation, but this approach is inefficient and subjective. Most of the existing computerized algorithms are two-dimensional (2D) and incapable of multi-angle calibration.Methods: A novel integrative framework based on curvature features and geometric constraints is proposed to measure three-dimensional (3D)Cobb angles on CT images. (Source: Computers in Biology and Medicine)
Source: Computers in Biology and Medicine - January 27, 2017 Category: Bioinformatics Authors: Xing Huo, Jie Qing Tan, Jun Qian, Li Cheng, Jue Hua Jing, Kun Shao, Bing Nan Li Source Type: research
CKM-CT: Comprehensible knowledge model creation for cancer treatment decision making
Background: A wealth of clinical data exists in clinical documents in the form of electronic health records (EHRs). This data can be used for developing knowledge-based recommendation systems that can assist clinicians in clinical decision making and education. One of the big hurdles in developing such systems is the lack of automated mechanisms for knowledge acquisition to enable and educate clinicians in informed decision making. Materials and Methods: An automated knowledge acquisition methodology with a comprehensible knowledge model for cancer treatment (CKM-CT) is proposed. (Source: Computers in Biology and Medicine)
Source: Computers in Biology and Medicine - January 27, 2017 Category: Bioinformatics Authors: Muhammad Afzal, Maqbool Hussain, Wajahat Ali Khan, Taqdir Ali, Sungyoung Lee, Eui-Nam Huh, Hafiz Farooq Ahmad, Arif Jamshed, Hassan Iqbal, Muhammad Irfan, Manzar Abbas Source Type: research
Mixed convection peristaltic flow of Eyring-Powell nanofluid in a curved channel with compliant walls
The novel features of nanofluids made them potentially significant in heat transfer mechanism occurring in medical and industrial processes like microelectronics, pharmaceutical processes, hybrid engines, thermal management of vehicles, refrigerator, chiller, gas temperature reduction and so forth. These processes bear tendency to enhance thermal conductivity and the convective heat transfer more efficiently than base fluid. This unique aspect made nanofluids the topic of interest in recent time via different fluid flow models. (Source: Computers in Biology and Medicine)
Source: Computers in Biology and Medicine - January 26, 2017 Category: Bioinformatics Authors: Anum Tanveer, T. Hayat, Fuad Alsaadi, A. Alsaedi Source Type: research
3D-SSF: A bio-inspired approach for dynamic multi-subject clustering of white matter tracts
There is growing interest in the study of white matter (WM) variation across subjects, and in particular the analysis of specific WM bundles, to better understand brain development and aging, as well as to improve early detection of some diseases. Several WM multi-subject clustering methods have been proposed to study WM bundles. These methods aim to overcome the complexity of the problem, which includes the huge size of the WM tractography datasets generated from multiple subjects, the existence of various streamlines with different positions, lengths and geometric forms, as well as the presence of outliers. (Source: Comp...
Source: Computers in Biology and Medicine - January 26, 2017 Category: Bioinformatics Authors: A. Chekir, S. Hassas, M. Descoteaux, M. C ôté, E. Garyfallidis, F. Oulebsir-Boumghar Source Type: research
Comparing Humans and Deep Learning Performance for Grading AMD: A Study in Using Universal Deep Features and Transfer Learning for Automated AMD Analysis
When left untreated, age-related macular degeneration (AMD) is the leading cause of vision loss in people over fifty in the US. Currently it is estimated that about eight million US individuals have the intermediate stage of AMD that is often asymptomatic with regard to visual deficit. These individuals are at high risk for progressing to the advanced stage where the often treatable choroidal neovascular form of AMD can occur. Careful monitoring to detect the onset and prompt treatment of the neovascular form as well as dietary supplementation can reduce the risk of vision loss from AMD, therefore, preferred practice patte...
Source: Computers in Biology and Medicine - January 26, 2017 Category: Bioinformatics Authors: Philippe Burlina, Katia D. Pacheco, Neil Joshi, David E. Freund, Neil M Bressler Source Type: research
Exploring temporal information in neonatal seizures using a dynamic time warping based SVM kernel
Seizure events in newborns change in frequency, morphology, and propagation. This contextual information is explored at the classifier level in the proposed patient-independent neonatal seizure detection system. The system is based on the combination of a static and a sequential SVM classifier. A Gaussian dynamic time warping based kernel is used in the sequential classifier. The system is validated on a large dataset of EEG recordings from 17 neonates. The obtained results show an increase in the detection rate at very low false detections per hour, particularly achieving a 12% improvement in the detection of short seizur...
Source: Computers in Biology and Medicine - January 25, 2017 Category: Bioinformatics Authors: Rehan Ahmed, Andriy Temko, William P. Marnane, Geraldine Boylan, Gordon Lightbody Source Type: research
Automated seizure detection using limited-channel EEG and non-linear dimension reduction
Electroencephalography (EEG) is an essential component in evaluation of epilepsy. However, full-channel EEG signals recorded from 18 –23 electrodes on the scalp is neither wearable nor computationally effective. This paper presents advantages of both channel selection and nonlinear dimension reduction for accurate automatic seizure detection. We first extract the frequency domain features from the full-channel EEG signals. Then , we use a random forest algorithm to determine which channels contribute the most in discriminating seizure from non-seizure events. (Source: Computers in Biology and Medicine)
Source: Computers in Biology and Medicine - January 24, 2017 Category: Bioinformatics Authors: Javad Birjandtalab, Maziyar Baran Pouyan, Diana Cogan, Mehrdad Nourani, Jay Harvey Source Type: research
