http://www.hindawi.com The latest articles from Hindawi Publishing Corporation © 2013 , Hindawi Publishing Corporation . All rights reserved. Thu, 23 May 2013 15:42:17 +0000 http://www.hindawi.com/journals/cmmm/2013/174342/ Innervation zone (IZ) has been identified as the origin of action potential propagation in isometric contraction. However, IZ shifts with changes in muscle length during muscle activity. The IZ shift has been estimated using raw EMG signals. This study aimed to investigate the movement of IZ location during continuous dynamic muscle contraction, using a computer program. Subjects flexed their elbow joint as repetitive dynamic muscle contractions. EMG signals were recorded from the biceps brachii muscle using an eight-channel surface electrode array. Approximately 100 peaks from EMG signals were detected for each channel and summed to estimate the IZ location. For each subject, the estimated IZ locations were subtracted from the IZ location during isometric contractions with the elbow flexed at 90°. The results showed that the IZ moved significantly with elbow joint movement from 45° to 135°. However, IZ movement was biased with only a 3.9 mm IZ shift on average when the elbow angle was acute but a 16 mm IZ shift on average when it was obtuse. The movement of IZ location during continuous dynamic muscle contraction can be investigated using this signal processing procedure without subjective judgment. Ken Nishihara, Hisashi Kawai, Yu Chiba, Naohiko Kanemura, and Toshiaki Gomi Copyright © 2013 Ken Nishihara et al. All rights reserved. Thu, 23 May 2013 13:33:44 +0000 http://www.hindawi.com/journals/cmmm/2013/609857/ The Stanford Heart Transplant data were collected to model survival in patients using penalized smoothing splines for covariates whose values change over the course of the study. The basic idea of the present study is to use a logistic regression model and a generalized additive model with -splines to estimate the survival function. We model survival time as a function of patient covariates and transplant status and compare the results obtained using smoothing spline, partial logistic, Cox's proportional hazards, and piecewise exponential models. Masaaki Tsujitani and Yusuke Tanaka Copyright © 2013 Masaaki Tsujitani and Yusuke Tanaka. All rights reserved. Wed, 22 May 2013 15:53:03 +0000 http://www.hindawi.com/journals/cmmm/2013/713174/ A novel method is proposed to establish the classifier which can classify the pancreatic images into normal or abnormal. Firstly, the brightness feature is used to construct high-order tensors, then using multilinear principal component analysis (MPCA) extracts the eigentensors, and finally, the classifier is constructed based on support vector machine (SVM) and the classifier parameters are optimized with quantum simulated annealing algorithm (QSA). In order to verify the effectiveness of the proposed algorithm, the normal SVM method has been chosen as comparing algorithm. The experimental results show that the proposed method can effectively extract the eigenfeatures and improve the classification accuracy of pancreatic images. Huiyan Jiang, Di Zhao, Tianjiao Feng, Shiyang Liao, and Yenwei Chen Copyright © 2013 Huiyan Jiang et al. All rights reserved. Wed, 22 May 2013 10:59:54 +0000 http://www.hindawi.com/journals/cmmm/2013/264246/ Breast cancer is one of the leading causes of death among women worldwide. There are a number of techniques used for diagnosing this disease: mammography, ultrasound, and biopsy, among others. Each of these has well-known advantages and disadvantages. A relatively new method, based on the temperature a tumor may produce, has recently been explored: thermography. In this paper, we will evaluate the diagnostic power of thermography in breast cancer using Bayesian network classifiers. We will show how the information provided by the thermal image can be used in order to characterize patients suspected of having cancer. Our main contribution is the proposal of a score, based on the aforementioned information, that could help distinguish sick patients from healthy ones. Our main results suggest the potential of this technique in such a goal but also show its main limitations that have to be overcome to consider it as an effective diagnosis complementary tool. Cruz-Ramírez Nicandro, Mezura-Montes Efrén, Ameca-Alducin María Yaneli, Martín-Del-Campo-Mena Enrique, Acosta-Mesa Héctor Gabriel, Pérez-Castro Nancy, Guerra-Hernández Alejandro, Hoyos-Rivera Guillermo de Jesús, and Barrientos-Martínez Rocío Erandi Copyright © 2013 Cruz-Ramírez Nicandro et al. All rights reserved. Mon, 20 May 2013 15:39:48 +0000 http://www.hindawi.com/journals/cmmm/2013/376152/ Phonocardiography has shown a great potential for developing low-cost computer-aided diagnosis systems for cardiovascular monitoring. So far, most of the work reported regarding cardiosignal analysis using multifractals is oriented towards heartbeat dynamics. This paper represents a step towards automatic detection of one of the most common pathological syndromes, so-called mitral valve prolapse (MVP), using phonocardiograms and multifractal analysis. Subtle features characteristic for MVP in phonocardiograms may be difficult to detect. The approach for revealing such features should be locally based rather than globally based. Nevertheless, if their appearances are specific and frequent, they can affect a multifractal spectrum. This has been the case in our experiment with the click syndrome. Totally, 117 pediatric phonocardiographic recordings (PCGs), 8 seconds long each, obtained from 117 patients were used for PMV automatic detection. We propose a two-step algorithm to distinguish PCGs that belong to children with healthy hearts and children with prolapsed mitral valves (PMVs). Obtained results show high accuracy of the method. We achieved 96.91% accuracy on the dataset (97 recordings). Additionally, 90% accuracy is achieved for the evaluation dataset (20 recordings). Content of the datasets is confirmed by the echocardiographic screening. Ana Gavrovska, Goran Zajić, Irini Reljin, and Branimir Reljin Copyright © 2013 Ana Gavrovska et al. All rights reserved. Mon, 20 May 2013 08:39:41 +0000 http://www.hindawi.com/journals/cmmm/2013/470390/ A group of intrinsically disordered, hydrophilic proteins—Late Embryogenesis Abundant (LEA) proteins—has been linked to survival in plants and animals in periods of stress, putatively through safeguarding enzymatic function and prevention of aggregation in times of dehydration/heat. Yet despite decades of effort, the molecular-level mechanisms defining this protective function remain unknown. A recent effort to understand LEA functionality began with the unique application of phage display, wherein phage display and biopanning over recombinant Seed Maturation Protein homologs from Arabidopsis thaliana and Glycine max were used to retrieve client proteins at two different temperatures, with one intended to represent heat stress. From this previous study, we identified 21 client proteins for which clones were recovered, sometimes repeatedly. Here, we use sequence analysis and homology modeling of the client proteins to ascertain common sequence and structural properties that may contribute to binding affinity with the protective LEA protein. Our methods uncover what appears to be a predilection for protein-nucleic acid interactions among LEA client proteins, which is suggestive of subcellular residence. The results from this initial computational study will guide future efforts to uncover the protein protective mechanisms during heat stress, potentially leading to phage-display-directed evolution of synthetic LEA molecules. Rekha Kushwaha, A. Bruce Downie, and Christina M. Payne Copyright © 2013 Rekha Kushwaha et al. All rights reserved. Sun, 19 May 2013 14:16:45 +0000 http://www.hindawi.com/journals/cmmm/2013/137392/ The automatic detection of white blood cells (WBCs) still remains as an unsolved issue in medical imaging. The analysis of WBC images has engaged researchers from fields of medicine and computer vision alike. Since WBC can be approximated by an ellipsoid form, an ellipse detector algorithm may be successfully applied in order to recognize such elements. This paper presents an algorithm for the automatic detection of WBC embedded in complicated and cluttered smear images that considers the complete process as a multiellipse detection problem. The approach, which is based on the differential evolution (DE) algorithm, transforms the detection task into an optimization problem whose individuals represent candidate ellipses. An objective function evaluates if such candidate ellipses are actually present in the edge map of the smear image. Guided by the values of such function, the set of encoded candidate ellipses (individuals) are evolved using the DE algorithm so that they can fit into the WBCs which are enclosed within the edge map of the smear image. Experimental results from white blood cell images with a varying range of complexity are included to validate the efficiency of the proposed technique in terms of its accuracy and robustness. Erik Cuevas, Margarita Díaz, Miguel Manzanares, Daniel Zaldivar, and Marco Perez-Cisneros Copyright © 2013 Erik Cuevas et al. All rights reserved. Sun, 19 May 2013 11:43:08 +0000 http://www.hindawi.com/journals/cmmm/2013/375641/ Bairong Shen, Hong-Bin Shen, Tianhai Tian, Qiang Lü, and Guang Hu Copyright © 2013 Bairong Shen et al. All rights reserved. Thu, 16 May 2013 17:45:26 +0000 http://www.hindawi.com/journals/cmmm/2013/347238/ The geometry of some medical images of tissues, obtained by elastography and ultrasonography, is characterized in terms of complexity parameters such as the fractal dimension (FD). It is well known that in any image there are very subtle details that are not easily detectable by the human eye. However, in many cases like medical imaging diagnosis, these details are very important since they might contain some hidden information about the possible existence of certain pathological lesions like tissue degeneration, inflammation, or tumors. Therefore, an automatic method of analysis could be an expedient tool for physicians to give a faultless diagnosis. The fractal analysis is of great importance in relation to a quantitative evaluation of “real-time” elastography, a procedure considered to be operator dependent in the current clinical practice. Mathematical analysis reveals significant discrepancies among normal and pathological image patterns. The main objective of our work is to demonstrate the clinical utility of this procedure on an ultrasound image corresponding to a submandibular diffuse pathology. Alexandru Florin Badea, Monica Lupsor Platon, Maria Crisan, Carlo Cattani, Iulia Badea, Gaetano Pierro, Gianpaolo Sannino, and Grigore Baciut Copyright © 2013 Alexandru Florin Badea et al. All rights reserved. Thu, 16 May 2013 08:56:07 +0000 http://www.hindawi.com/journals/cmmm/2013/804573/ 3D medical images are widely used to assist diagnosis and surgical planning in clinical applications, where quantitative measurement of interesting objects in the image is of great importance. Volume rendering is widely used for qualitative visualization of 3D medical images. In this paper, we introduce a volume-rendering-based interactive 3D measurement framework for quantitative analysis of 3D medical images. In the framework, 3D widgets and volume clipping are integrated with volume rendering. Specifically, 3D plane widgets are manipulated to clip the volume to expose interesting objects. 3D plane widgets, 3D line widgets, and 3D angle widgets are then manipulated to measure the areas, distances, and angles of interesting objects. The methodology of the proposed framework is described. Experimental results indicate the performance of the interactive 3D measurement framework. Yakang Dai, Jian Zheng, Yuetao Yang, Duojie Kuai, and Xiaodong Yang Copyright © 2013 Yakang Dai et al. All rights reserved. Wed, 15 May 2013 12:57:58 +0000 http://www.hindawi.com/journals/cmmm/2013/618025/ In recent years, the advances in information and communication technology (ICT) have resulted in the development of systems and applications aimed at supporting rehabilitation therapy that contributes to enrich patients’ life quality. This work is focused on the improvement of the telemedicine systems with the purpose of customizing therapies according to the profile and disability of patients. For doing this, as salient contribution, this work proposes the adoption of user-centered design (UCD) methodology for the design and development of telemedicine systems in order to support the rehabilitation of patients with neurological disorders. Finally, some applications of the UCD methodology in the telemedicine field are presented as a proof of concept. Claudia I. Martínez-Alcalá, Mirna Muñoz, and Josep Monguet-Fierro Copyright © 2013 Claudia I. Martínez-Alcalá et al. All rights reserved. Wed, 15 May 2013 11:06:44 +0000 http://www.hindawi.com/journals/cmmm/2013/530696/ Knowledge about the protein composition of phage virions is a key step to understand the functions of phage virion proteins. However, the experimental method to identify virion proteins is time consuming and expensive. Thus, it is highly desirable to develop novel computational methods for phage virion protein identification. In this study, a Naïve Bayes based method was proposed to predict phage virion proteins using amino acid composition and dipeptide composition. In order to remove redundant information, a novel feature selection technique was employed to single out optimized features. In the jackknife test, the proposed method achieved an accuracy of 79.15% for phage virion and nonvirion proteins classification, which are superior to that of other state-of-the-art classifiers. These results indicate that the proposed method could be as an effective and promising high-throughput method in phage proteomics research. Peng-Mian Feng, Hui Ding, Wei Chen, and Hao Lin Copyright © 2013 Peng-Mian Feng et al. All rights reserved. Tue, 14 May 2013 16:44:56 +0000 http://www.hindawi.com/journals/cmmm/2013/179761/ There has been recent success in identifying disease-causing variants in Mendelian disorders by exome sequencing followed by simple filtering techniques. Studies generally assume complete or high penetrance. However, there are likely many failed and unpublished studies due in part to incomplete penetrance or phenocopy. In this study, the expected number of candidate single-nucleotide variants (SNVs) in exome data for autosomal dominant or recessive Mendelian disorders was investigated under the assumption of “no genetic heterogeneity.” All variants were assumed to be under the “null model,” and sample allele frequencies were modeled using a standard population genetics theory. To investigate the properties of pedigree data, full-sibs were considered in addition to unrelated individuals. In both cases, particularly regarding full-sibs, the number of SNVs remained very high without controls. The high efficacy of controls was also confirmed. When controls were used with a relatively large total sample size (e.g., ), filtering incorporating of incomplete penetrance and phenocopy efficiently reduced the number of candidate SNVs. This suggests that filtering is useful when an assumption of no “genetic heterogeneity” is appropriate and could provide general guidelines for sample size determination. Jo Nishino and Shuhei Mano Copyright © 2013 Jo Nishino and Shuhei Mano. All rights reserved. Tue, 14 May 2013 14:36:52 +0000 http://www.hindawi.com/journals/cmmm/2013/679308/ Spontaneous pneumothorax, a prevalent medical challenge in most trauma cases, is a form of sudden lung collapse closely associated with risk factors such as lung cancer and emphysema. Our work seeks to explore and quantify the currently unknown pathological factors underlying lesion rupture in pneumothorax through biomechanical modeling. We hypothesized that lesion instability is closely associated with elastodynamic strain of the pleural membrane from pulsatile air flow and collagen-elastin dynamics. Based on the principles of continuum mechanics and fluid-structure interaction, our proposed model coupled isotropic tissue deformation with pressure from pulsatile air motion and the pleural fluid. Next, we derived mathematical instability criteria for our ordinary differential equation system and then translated these mathematical instabilities to physically relevant structural instabilities via the incorporation of a finite energy limiter. The introduction of novel biomechanical descriptions for collagen-elastin dynamics allowed us to demonstrate that changes in the protein structure can lead to a transition from stable to unstable domains in the material parameter space for a general lesion. This result allowed us to create a novel streamlined algorithm for detecting material instabilities in transient lung CT scan data via analyzing deformations in a local tissue boundary. Archis R. Bhandarkar, Rohan Banerjee, and Padmanabhan Seshaiyer Copyright © 2013 Archis R. Bhandarkar et al. All rights reserved. Tue, 14 May 2013 09:00:47 +0000 http://www.hindawi.com/journals/cmmm/2013/638563/ Current medical imaging systems provide excellent spatial resolution, high tissue contrast, and up to 65535 intensity levels. Thus, image processing techniques which aim to exploit the information contained in the images are necessary for using these images in computer-aided diagnosis (CAD) systems. Image segmentation may be defined as the process of parcelling the image to delimit different neuroanatomical tissues present on the brain. In this paper we propose a segmentation technique using 3D statistical features extracted from the volume image. In addition, the presented method is based on unsupervised vector quantization and fuzzy clustering techniques and does not use any a priori information. The resulting fuzzy segmentation method addresses the problem of partial volume effect (PVE) and has been assessed using real brain images from the Internet Brain Image Repository (IBSR). Andrés Ortiz, Antonio A. Palacio, Juan M. Górriz, Javier Ramírez, and Diego Salas-González Copyright © 2013 Andrés Ortiz et al. All rights reserved. Mon, 13 May 2013 11:00:01 +0000 http://www.hindawi.com/journals/cmmm/2013/591032/ Magnetic resonance imaging (MRI) data is an invaluable tool in brain morphology research. Here, we propose a novel statistical method for investigating the relationship between clinical characteristics and brain morphology based on three-dimensional MRI data via radial basis function-sparse partial least squares (RBF-sPLS). Our data consisted of MRI image intensities for multimillion voxels in a 3D array along with 73 clinical variables. This dataset represents a suitable application of RBF-sPLS because of a potential correlation among voxels as well as among clinical characteristics. Additionally, this method can simultaneously select both effective brain regions and clinical characteristics based on sparse modeling. This is in contrast to existing methods, which consider prespecified brain regions because of the computational difficulties involved in processing high-dimensional data. RBF-sPLS employs dimensionality reduction in order to overcome this obstacle. We have applied RBF-sPLS to a real dataset composed of 102 chronic kidney disease patients, while a comparison study used a simulated dataset. RBF-sPLS identified two brain regions of interest from our patient data: the temporal lobe and the occipital lobe, which are associated with aging and anemia, respectively. Our simulation study suggested that such brain regions are extracted with excellent accuracy using our method. Hisako Yoshida, Atsushi Kawaguchi, and Kazuhiko Tsuruya Copyright © 2013 Hisako Yoshida et al. All rights reserved. Sun, 12 May 2013 18:23:30 +0000 http://www.hindawi.com/journals/cmmm/2013/760903/ A procedure to improve the convergence rate for affine registration methods of medical brain images when the images differ greatly from the template is presented. The methodology is based on a histogram matching of the source images with respect to the reference brain template before proceeding with the affine registration. The preprocessed source brain images are spatially normalized to a template using a general affine model with 12 parameters. A sum of squared differences between the source images and the template is considered as objective function, and a Gauss-Newton optimization algorithm is used to find the minimum of the cost function. Using histogram equalization as a preprocessing step improves the convergence rate in the affine registration algorithm of brain images as we show in this work using SPECT and PET brain images. D. Salas-Gonzalez, J. M. Górriz, J. Ramírez, P. Padilla, and I. A. Illán Copyright © 2013 D. Salas-Gonzalez et al. All rights reserved. Sun, 12 May 2013 13:54:28 +0000 http://www.hindawi.com/journals/cmmm/2013/643129/ Brain state decoding or “mind reading” via multivoxel pattern analysis (MVPA) has become a popular focus of functional magnetic resonance imaging (fMRI) studies. In brain decoding, stimulus presentation rate is increased as fast as possible to collect many training samples and obtain an effective and reliable classifier or computational model. However, for extremely rapid event-related experiments, the blood-oxygen-level-dependent (BOLD) signals evoked by adjacent trials are heavily overlapped in the time domain. Thus, identifying trial-specific BOLD responses is difficult. In addition, voxel-specific hemodynamic response function (HRF), which is useful in MVPA, should be used in estimation to decrease the loss of weak information across voxels and obtain fine-grained spatial information. Regularization methods have been widely used to increase the efficiency of HRF estimates. In this study, we propose a regularization framework called mixed L2 norm regularization. This framework involves Tikhonov regularization and an additional L2 norm regularization term to calculate reliable HRF estimates. This technique improves the accuracy of HRF estimates and significantly increases the classification accuracy of the brain decoding task when applied to a rapid event-related four-category object classification experiment. At last, some essential issues such as the impact of low-frequency fluctuation (LFF) and the influence of smoothing are discussed for rapid event-related experiments. Yu Lei, Li Tong, and Bin Yan Copyright © 2013 Yu Lei et al. All rights reserved. Sun, 12 May 2013 08:07:43 +0000 http://www.hindawi.com/journals/cmmm/2013/719389/ Transplantation is often the only viable treatment for pediatric patients with end-stage liver disease. Making well-informed decisions on when to proceed with transplantation requires accurate predictors of transplant survival. The standard Cox proportional hazards (PH) model assumes that covariate effects are time-invariant on right-censored failure time; however, this assumption may not always hold. Gray’s piecewise constant time-varying coefficients (PC-TVC) model offers greater flexibility to capture the temporal changes of covariate effects without losing the mathematical simplicity of Cox PH model. In the present work, we examined the Cox PH and Gray PC-TVC models on the posttransplant survival analysis of 288 pediatric liver transplant patients diagnosed with cancer. We obtained potential predictors through univariable and multivariable models with forward selection for the Cox PH and Gray PC-TVC models, which coincide. While the Cox PH model provided reasonable average results in estimating covariate effects on posttransplant survival, the Gray model using piecewise constant penalized splines showed more details of how those effects change over time. Yi Ren, Chung-Chou H. Chang, Gabriel L. Zenarosa, Heather E. Tomko, Drew Michael S. Donnell, Hyung-joo Kang, Mark S. Roberts, and Cindy L. Bryce Copyright © 2013 Yi Ren et al. All rights reserved. Sun, 12 May 2013 08:01:40 +0000 http://www.hindawi.com/journals/cmmm/2013/381356/ We developed a method to reconstruct cell geometry from confocal fluorescence microscopy images of the cytoskeleton. In the method, region growing was implemented twice. First, it was applied to the extracellular regions to differentiate them from intracellular noncytoskeletal regions, which both appear black in fluorescence microscopy imagery, and then to cell regions for cell identification. Analysis of morphological parameters revealed significant changes in cell shape associated with cytoskeleton disruption, which offered insight into the mechanical role of the cytoskeleton in maintaining cell shape. The proposed segmentation method is promising for investigations on cell morphological changes with respect to internal cytoskeletal structures. Yoshihiro Ujihara, Masanori Nakamura, Hiroshi Miyazaki, and Shigeo Wada Copyright © 2013 Yoshihiro Ujihara et al. All rights reserved. Thu, 09 May 2013 15:20:10 +0000 http://www.hindawi.com/journals/cmmm/2013/648291/ We address the problem of long-term dynamics of tuberculosis (TB) and latent tuberculosis (LTB) in semiclosed communities. These communities are congregate settings with the potential for sustained daily contact for weeks, months, and even years between their members. Basic examples of these communities are prisons, but certain urban/rural communities, some schools, among others could possibly fit well into this definition. These communities present a sort of ideal conditions for TB spread. In order to describe key relevant dynamics of the disease in these communities, we consider a five compartments SEIR model with five possible routes toward TB infection: primary infection after a contact with infected and infectious individuals (fast TB), endogenous reactivation after a period of latency (slow TB), relapse by natural causes after a cure, exogenous reinfection of latently infected, and exogenous reinfection of recovered individuals. We discuss the possible existence of multiple endemic equilibrium states and the role that the two types of exogenous reinfections in the long-term dynamics of the disease could play. Mauricio Herrera, Paul Bosch, Manuel Nájera, and Ximena Aguilera Copyright © 2013 Mauricio Herrera et al. All rights reserved. Thu, 09 May 2013 15:10:23 +0000 http://www.hindawi.com/journals/cmmm/2013/598196/ The ARVmobile v1.0 is a multiplatform mobile personal health monitor (PHM) application for ambulatory blood pressure (ABP) monitoring that has the potential to aid in the acquisition and analysis of detailed profile of ABP and heart rate (HR), improve the early detection and intervention of hypertension, and detect potential abnormal BP and HR levels for timely medical feedback. The PHM system consisted of ABP sensor to detect BP and HR signals and smartphone as receiver to collect the transmitted digital data and process them to provide immediate personalized information to the user. Android and Blackberry platforms were developed to detect and alert of potential abnormal values, offer friendly graphical user interface for elderly people, and provide feedback to professional healthcare providers via e-mail. ABP data were obtained from twenty-one healthy individuals (>51 years) to test the utility of the PHM application. The ARVmobile v1.0 was able to reliably receive and process the ABP readings from the volunteers. The preliminary results demonstrate that the ARVmobile 1.0 application could be used to perform a detailed profile of ABP and HR in an ordinary daily life environment, bedsides of estimating potential diagnostic thresholds of abnormal BP variability measured as average real variability. Luis J. Mena, Vanessa G. Felix, Rodolfo Ostos, Jesus A. Gonzalez, Armando Cervantes, Armando Ochoa, Carlos Ruiz, Roberto Ramos, and Gladys E. Maestre Copyright © 2013 Luis J. Mena et al. All rights reserved. Thu, 09 May 2013 11:39:16 +0000 http://www.hindawi.com/journals/cmmm/2013/132953/ This paper presents a novel image segmentation method based on multiple active contours driven by particle swarm optimization (MACPSO). The proposed method uses particle swarm optimization over a polar coordinate system to increase the energy-minimizing capability with respect to the traditional active contour model. In the first stage, to evaluate the robustness of the proposed method, a set of synthetic images containing objects with several concavities and Gaussian noise is presented. Subsequently, MACPSO is used to segment the human heart and the human left ventricle from datasets of sequential computed tomography and magnetic resonance images, respectively. Finally, to assess the performance of the medical image segmentations with respect to regions outlined by experts and by the graph cut method objectively and quantifiably, a set of distance and similarity metrics has been adopted. The experimental results demonstrate that MACPSO outperforms the traditional active contour model in terms of segmentation accuracy and stability. I. Cruz-Aceves, J. G. Aviña-Cervantes, J. M. López-Hernández, and S. E. González-Reyna Copyright © 2013 I. Cruz-Aceves et al. All rights reserved. Thu, 09 May 2013 09:14:16 +0000 http://www.hindawi.com/journals/cmmm/2013/250915/ In the cochlear implant system, the distance between spiral ganglia and the electrodes within the volume of the scala tympani cavity significantly affects the efficiency of the electrical stimulation in terms of the threshold current level and spatial selectivity. Because the spiral ganglia are situated inside the modiolus, the central axis of the cochlea, it is desirable that the electrode array hugs the modiolus to minimize the distance between the electrodes and the ganglia. In the present study, we propose a shape-memory-alloy-(SMA-) embedded intracochlear electrode which gives a straight electrode a curved modiolus-hugging shape using the restoration force of the SMA as triggered by resistive heating after insertion into the cochlea. An eight-channel ball-type electrode array is fabricated with an embedded titanium-nickel SMA backbone wire. It is demonstrated that the electrode array changes its shape in a transparent plastic human cochlear model. To verify the safe insertion of the electrode array into the human cochlea, the contact pressures during insertion at the electrode tip and the contact pressures over the electrode length after insertion were calculated using a 3D finite element analysis. The results indicate that the SMA-embedded electrode is functionally and mechanically feasible for clinical applications. Kyou Sik Min, Sang Beom Jun, Yoon Seob Lim, Se-Ik Park, and Sung June Kim Copyright © 2013 Kyou Sik Min et al. All rights reserved. Wed, 08 May 2013 17:28:11 +0000 http://www.hindawi.com/journals/cmmm/2013/651091/ Visual assessments of mammographic breast density by radiologists are used in clinical practice; however, these assessments have shown weaker associations with breast cancer risk than area-based, quantitative methods. The purpose of this study is to present a statistical evaluation of a fully automated, area-based mammographic density measurement algorithm. Five radiologists estimated density in 5% increments for 138 “For Presentation” single MLO views; the median of the radiologists’ estimates was used as the reference standard. Agreement amongst radiologists was excellent, ICC = 0.884, 95% CI (0.854, 0.910). Similarly, the agreement between the algorithm and the reference standard was excellent, ICC = 0.862, falling within the 95% CI of the radiologists’ estimates. The Bland-Altman plot showed that the reference standard was slightly positively biased (+1.86%) compared to the algorithm-generated densities. A scatter plot showed that the algorithm moderately overestimated low densities and underestimated high densities. A box plot showed that 95% of the algorithm-generated assessments fell within one BI-RADS category of the reference standard. This study demonstrates the effective use of several statistical techniques that collectively produce a comprehensive evaluation of the algorithm and its potential to provide mammographic density measures that can be used to inform clinical practice. Mohamed Abdolell, Kaitlyn Tsuruda, Gerry Schaller, and Judy Caines Copyright © 2013 Mohamed Abdolell et al. All rights reserved. Tue, 07 May 2013 16:39:57 +0000 http://www.hindawi.com/journals/cmmm/2013/253670/ In this study, an MRI-based classification framework was proposed to distinguish the patients with AD and MCI from normal participants by using multiple features and different classifiers. First, we extracted features (volume and shape) from MRI data by using a series of image processing steps. Subsequently, we applied principal component analysis (PCA) to convert a set of features of possibly correlated variables into a smaller set of values of linearly uncorrelated variables, decreasing the dimensions of feature space. Finally, we developed a novel data mining framework in combination with support vector machine (SVM) and particle swarm optimization (PSO) for the AD/MCI classification. In order to compare the hybrid method with traditional classifier, two kinds of classifiers, that is, SVM and a self-organizing map (SOM), were trained for patient classification. With the proposed framework, the classification accuracy is improved up to 82.35% and 77.78% in patients with AD and MCI. The result achieved up to 94.12% and 88.89% in AD and MCI by combining the volumetric features and shape features and using PCA. The present results suggest that novel multivariate methods of pattern matching reach a clinically relevant accuracy for the a priori prediction of the progression from MCI to AD. Shih-Ting Yang, Jiann-Der Lee, Tzyh-Chyang Chang, Chung-Hsien Huang, Jiun-Jie Wang, Wen-Chuin Hsu, Hsiao-Lung Chan, Yau-Yau Wai, and Kuan-Yi Li Copyright © 2013 Shih-Ting Yang et al. All rights reserved. Tue, 07 May 2013 16:39:00 +0000 http://www.hindawi.com/journals/cmmm/2013/109497/ Human nervous system tries to minimize the effect of any external perturbing force by bringing modifications in the internal model. These modifications affect the subsequent motor commands generated by the nervous system. Adaptive compensation along with the appropriate modifications of internal model helps in reducing human movement errors. In the current study, we studied how motor imagery influences trial-to-trial learning in a robot-based adaptation task. Two groups of subjects performed reaching movements with or without motor imagery in a velocity-dependent force field. The results show that reaching movements performed with motor imagery have relatively a more focused generalization pattern and a higher learning rate in training direction. Muhammad Nabeel Anwar and Salman Hameed Khan Copyright © 2013 Muhammad Nabeel Anwar and Salman Hameed Khan. All rights reserved. Thu, 02 May 2013 13:53:15 +0000 http://www.hindawi.com/journals/cmmm/2013/235825/ In family-based genetic association studies, it is possible to encounter missing genotype information for one of the parents. This leads to a study consisting of both case-parent trios and case-parent pairs. One of the approaches to this problem is permutation-based combined transmission disequilibrium test statistic. However, it is still unknown how powerful this test statistic is with small sample sizes. In this paper, a simulation study is carried out to estimate the power and false positive rate of this test across different sample sizes for a family-based genome-wide association study. It is observed that a statistical power of over 80% and a reasonable false positive rate estimate can be achieved even with a combination of 50 trios and 30 pairs when 2% of the SNPs are assumed to be associated. Moreover, even smaller samples provide high power when smaller percentages of SNPs are associated with the disease. Farid Rajabli, Gul Inan, and Ozlem Ilk Copyright © 2013 Farid Rajabli et al. All rights reserved. Thu, 02 May 2013 08:38:23 +0000 http://www.hindawi.com/journals/cmmm/2013/706195/ A generic cardiomyocyte ionic model, whose complexity lies between a simple phenomenological formulation and a biophysically detailed ionic membrane current description, is presented. The model provides a user-defined number of ionic currents, employing two-gate Hodgkin-Huxley type kinetics. Its generic nature allows accurate reconstruction of action potential waveforms recorded experimentally from a range of cardiac myocytes. Using a multiobjective optimisation approach, the generic ionic model was optimised to accurately reproduce multiple action potential waveforms recorded from central and peripheral sinoatrial nodes and right atrial and left atrial myocytes from rabbit cardiac tissue preparations, under different electrical stimulus protocols and pharmacological conditions. When fitted simultaneously to multiple datasets, the time course of several physiologically realistic ionic currents could be reconstructed. Model behaviours tend to be well identified when extra experimental information is incorporated into the optimisation. Tianruo Guo, Amr Al Abed, Nigel H. Lovell, and Socrates Dokos Copyright © 2013 Tianruo Guo et al. All rights reserved. Tue, 30 Apr 2013 11:29:08 +0000 http://www.hindawi.com/journals/cmmm/2013/254507/ Rami K. Korhonen, Petro Julkunen, LePing Li, and Corrinus C. van Donkelaar Copyright © 2013 Rami K. Korhonen et al. All rights reserved.