http://www.hindawi.com The latest articles from Hindawi Publishing Corporation © 2013 , Hindawi Publishing Corporation . All rights reserved. Wed, 19 Jun 2013 18:27:25 +0000 http://www.hindawi.com/journals/cmmm/2013/368514/ We address the performance evaluation practices for developing medical image analysis methods, in particular, how to establish and share databases of medical images with verified ground truth and solid evaluation protocols. Such databases support the development of better algorithms, execution of profound method comparisons, and, consequently, technology transfer from research laboratories to clinical practice. For this purpose, we propose a framework consisting of reusable methods and tools for the laborious task of constructing a benchmark database. We provide a software tool for medical image annotation helping to collect class label, spatial span, and expert's confidence on lesions and a method to appropriately combine the manual segmentations from multiple experts. The tool and all necessary functionality for method evaluation are provided as public software packages. As a case study, we utilized the framework and tools to establish the DiaRetDB1 V2.1 database for benchmarking diabetic retinopathy detection algorithms. The database contains a set of retinal images, ground truth based on information from multiple experts, and a baseline algorithm for the detection of retinopathy lesions. Tomi Kauppi, Joni-Kristian Kämäräinen, Lasse Lensu, Valentina Kalesnykiene, Iiris Sorri, Hannu Uusitalo, and Heikki Kälviäinen Copyright © 2013 Tomi Kauppi et al. All rights reserved. Wed, 19 Jun 2013 18:22:45 +0000 http://www.hindawi.com/journals/cmmm/2013/250929/ This study aimed to investigate the influence of implant design (in terms of diameter, length, and thread shape), in-bone positioning depth, and bone posthealing crestal morphology on load transfer mechanisms of osseointegrated dental implants based on platform-switching concept. In order to perform an effective multiparametric comparative analysis, 11 implants different in dimensions and in thread features were analyzed by a linearly elastic 3-dimensional finite element approach, under a static load. Implant models were integrated with the detailed model of a maxillary premolar bone segment. Different implant in-bone positioning levels were modeled, considering also different posthealing crestal bone morphologies. Bone overloading risk was quantified by introducing proper local stress measures, highlighting that implant diameter is a more effective design parameter than the implant length, as well as that thread shape and thread details can significantly affect stresses at peri-implant bone, especially for short implants. Numerical simulations revealed that the optimal in-bone positioning depth results from the balance of 2 counteracting effects: cratering phenomena and bone apposition induced by platform-switching configuration. Proposed results contribute to identify the mutual influence of a number of factors affecting the bone-implant loading transfer mechanisms, furnishing useful insights and indications for choosing and/or designing threaded osseointegrated implants. Giuseppe Vairo and Gianpaolo Sannino Copyright © 2013 Giuseppe Vairo and Gianpaolo Sannino. All rights reserved. Wed, 19 Jun 2013 11:44:24 +0000 http://www.hindawi.com/journals/cmmm/2013/849674/ An expert system having two stages is proposed for cardiac arrhythmia diagnosis. In the first stage, Fisher score is used for feature selection to reduce the feature space dimension of a data set. The second stage is classification stage in which least squares support vector machines classifier is performed by using the feature subset selected in the first stage to diagnose cardiac arrhythmia. Performance of the proposed expert system is evaluated by using an arrhythmia data set which is taken from UCI machine learning repository. Ersen Yılmaz Copyright © 2013 Ersen Yılmaz. All rights reserved. Wed, 19 Jun 2013 11:28:02 +0000 http://www.hindawi.com/journals/cmmm/2013/282398/ Antibodies appear to be the first line of defence in the adaptive immune response of vertebrates and thereby are involved in a multitude of biochemical mechanisms, such as regulation of infection, autoimmunity, and cancer. It goes without saying that a full understanding of antibody function is required for the development of novel antibody-interacting drugs. These drugs are the Antibody Drug Conjugates (ADCs), which are a new type of targeted therapy, used for example for cancer. They consist of an antibody (or antibody fragment such as a single-chain variable fragment [scFv]) linked to a payload drug (often cytotoxic). Because of the targeting, the side effects should be lower and give a wider therapeutic window. Overall, the underlying principle of ADCs is to discern the delivery of a drug that is cytotoxic to a target that is cancerous, hoping to increase the antitumoural potency of the original drug by reducing adverse effects and side effects, such as toxicity of the cancer target. This is a pioneering field that employs state-of-the-art computational and molecular biology methods in the fight against cancer using ADCs. Dimitrios Vlachakis and Sophia Kossida Copyright © 2013 Dimitrios Vlachakis and Sophia Kossida. All rights reserved. Wed, 19 Jun 2013 11:19:56 +0000 http://www.hindawi.com/journals/cmmm/2013/295986/ In this study, the effect of Pilates training on the brain function was investigated through five case studies. Alpha rhythm changes during the Pilates training over the different regions and the whole brain were mainly analyzed, including power spectral density and global synchronization index (GSI). It was found that the neural network of the brain was more active, and the synchronization strength reduced in the frontal and temporal regions due to the Pilates training. These results supported that the Pilates training is very beneficial for improving brain function or intelligence. These findings maybe give us some line evidence to suggest that the Pilates training is very helpful for the intervention of brain degenerative diseases and cogitative dysfunction rehabilitation. Zhijie Bian, Hongmin Sun, Chengbiao Lu, Li Yao, Shengyong Chen, and Xiaoli Li Copyright © 2013 Zhijie Bian et al. All rights reserved. Wed, 19 Jun 2013 08:49:47 +0000 http://www.hindawi.com/journals/cmmm/2013/593175/ Quantification of regional -TRODAT-1 binding ratio in the striatum regions in SPECT images is essential for differential diagnosis between Alzheimer's and Parkinson's diseases. Defining the region of the striatum in the SPECT image is the first step toward success in the quantification of the TRODAT-1 binding ratio. However, because SPECT images reveal insufficient information regarding the anatomical structure of the brain, correct delineation of the striatum directly from the SPECT image is almost impossible. We present a method integrating the active contour model and the hybrid registration technique to extract regions from MR T1-weighted images and map them into the corresponding SPECT images. Results from three normal subjects suggest that the segmentation accuracy using the proposed method was compatible with the expert decision but has a higher efficiency and reproducibility than manual delineation. The binding ratio derived by this method correlated well (R2 = 0.76) with those values calculated by commercial software, suggesting the feasibility of the proposed method. Ching-Fen Jiang, Chiung-Chih Chang, Shu-Hua Huang, and Chia-Hsiang Wu Copyright © 2013 Ching-Fen Jiang et al. All rights reserved. Tue, 18 Jun 2013 13:13:37 +0000 http://www.hindawi.com/journals/cmmm/2013/283593/ The spatiotemporal evolution of stroke lesions, from acute injury to final tissue damage, is complex. Diffusion-weighted (DWI) and perfusion-weighted (PWI) imaging is commonly used to detect early ischemic changes and attempts to distinguish between permanently damaged and salvageable tissues. To date, 2D and 3D measures of diffusion/perfusion regions at individual timepoints have been widely used but may underestimate the true lesion spatio-temporal dynamics. Currently there is no spatio-temporal 4D dynamic model that simulates the continuous evolution of ischemic stroke from MR images. We determined whether a 4D current-based diffeomorphic model, developed in the field of statistical modeling for measuring the variability of anatomical surfaces, could estimate patient-specific spatio-temporal continuous evolution for MR PWI (measured as mean transit time, (MTT)) and DWI lesions. In our representative pilot sample, the model fitted the data well. Our dynamic analysis of lesion evolution showed different patterns; for example, some DWI/PWI dynamic changes corresponded with DWI lesion expansion into PWI lesions, but other patterns were much more complex and diverse. There was wide variation in the time when the final tissue damage was reached after stroke for DWI and MTT. Islem Rekik, Stéphanie Allassonnière, Stanley Durrleman, Trevor Carpenter, and Joanna Wardlaw Copyright © 2013 Islem Rekik et al. All rights reserved. Tue, 18 Jun 2013 08:14:20 +0000 http://www.hindawi.com/journals/cmmm/2013/106867/ Feature is important for many applications in biomedical signal analysis and living system analysis. A fast discriminative stochastic neighbor embedding analysis (FDSNE) method for feature extraction is proposed in this paper by improving the existing DSNE method. The proposed algorithm adopts an alternative probability distribution model constructed based on its -nearest neighbors from the interclass and intraclass samples. Furthermore, FDSNE is extended to nonlinear scenarios using the kernel trick and then kernel-based methods, that is, KFDSNE1 and KFDSNE2. FDSNE, KFDSNE1, and KFDSNE2 are evaluated in three aspects: visualization, recognition, and elapsed time. Experimental results on several datasets show that, compared with DSNE and MSNP, the proposed algorithm not only significantly enhances the computational efficiency but also obtains higher classification accuracy. Jianwei Zheng, Hong Qiu, Xinli Xu, Wanliang Wang, and Qiongfang Huang Copyright © 2013 Jianwei Zheng et al. All rights reserved. Mon, 17 Jun 2013 08:50:23 +0000 http://www.hindawi.com/journals/cmmm/2013/213563/ Tianruo Guo, Amr Al Abed, Nigel H. Lovell, and Socrates Dokos Copyright © 2013 Tianruo Guo et al. All rights reserved. Sat, 15 Jun 2013 16:10:16 +0000 http://www.hindawi.com/journals/cmmm/2013/519071/ This research focuses on creating a standardized nasal cavity model of adult Malaysian females. The methodology implemented in this research is a new approach compared to other methods used by previous researchers. This study involves 26 females who represent the test subjects for this preliminary study. Computational fluid dynamic (CFD) analysis was carried out to better understand the characteristics of the standardized model and to compare it to the available standardized Caucasian model. This comparison includes cross-sectional areas for both half-models as well as velocity contours along the nasal cavities. The Malaysian female standardized model is larger in cross-sectional area compared to the standardized Caucasian model thus leading to lower average velocity magnitudes. The standardized model was further evaluated with four more Malaysian female test subjects based on its cross-sectional areas and average velocity magnitudes along the nasal cavities. This evaluation shows that the generated model represents an averaged and standardized model of adult Malaysian females. Chih Fang Lee, Mohd. Zulkifly Abdullah, Kamarul Arifin Ahmad, and Ibrahim Lutfi Shuaib Copyright © 2013 Chih Fang Lee et al. All rights reserved. Wed, 12 Jun 2013 09:16:32 +0000 http://www.hindawi.com/journals/cmmm/2013/645043/ A linear time-invariant model based on statistical time series analysis in the Fourier domain for single subjects is further developed and applied to functional MRI (fMRI) blood-oxygen level-dependent (BOLD) multivariate data. This methodology was originally developed to analyze multiple stimulus input evoked response BOLD data. However, to analyze clinical data generated using a repeated measures experimental design, the model has been extended to handle multivariate time series data and demonstrated on control and alcoholic subjects taken from data previously analyzed in the temporal domain. Analysis of BOLD data is typically carried out in the time domain where the data has a high temporal correlation. These analyses generally employ parametric models of the hemodynamic response function (HRF) where prewhitening of the data is attempted using autoregressive (AR) models for the noise. However, this data can be analyzed in the Fourier domain. Here, assumptions made on the noise structure are less restrictive, and hypothesis tests can be constructed based on voxel-specific nonparametric estimates of the hemodynamic transfer function (HRF in the Fourier domain). This is especially important for experimental designs involving multiple states (either stimulus or drug induced) that may alter the form of the response function. Daniel E. Rio, Robert R. Rawlings, Lawrence A. Woltz, Jodi Gilman, and Daniel W. Hommer Copyright © 2013 Daniel E. Rio et al. All rights reserved. Wed, 12 Jun 2013 09:14:13 +0000 http://www.hindawi.com/journals/cmmm/2013/213901/ Texture analysis is the process of highlighting key characteristics thus providing an exhaustive and unambiguous mathematical description of any object represented in a digital image. Each characteristic is connected to a specific property of the object. In some cases the mentioned properties represent aspects visually perceptible which can be detected by developing operators based on Computer Vision techniques. In other cases these properties are not visually perceptible and their computation is obtained by developing operators based on Image Understanding approaches. Pixels composing high quality medical images can be considered the result of a stochastic process since they represent morphological or physiological processes. Empirical observations have shown that these images have visually perceptible and hidden significant aspects. For these reasons, the operators can be developed by means of a statistical approach. In this paper we present a set of customized first and second order statistics based operators to perform advanced texture analysis of Magnetic Resonance Imaging (MRI) images. In particular, we specify the main rules defining the role of an operator and its relationship with other operators. Extensive experiments carried out on a wide dataset of MRI images of different body regions demonstrating usefulness and accuracy of the proposed approach are also reported. Danilo Avola, Luigi Cinque, and Giuseppe Placidi Copyright © 2013 Danilo Avola et al. All rights reserved. Tue, 11 Jun 2013 09:11:53 +0000 http://www.hindawi.com/journals/cmmm/2013/430276/ The quantitative accuracy of SPECT is limited by photon attenuation and scatter effect when photons interact with atoms. In this study, we developed a new attenuation correction (AC) method, CT-based mean attenuation correction (CTMAC) method, and compared it with various methods that were often used currently to assess the AC phenomenon by using the small-animal SPECT/CT data that were acquired from various physical phantoms and a rat. The physical phantoms and an SD rat, which were injected with Tc, were scanned by a parallel-hole small-animal SPECT, and then they were imaged by the 80 kVp micro-CT. Scatter was estimated and corrected by the triple-energy window (TEW) method. Absolute quantification was derived from a known activity point source scan. In the physical-phantom studies, we compared the images with original, scatter correction (SC) only, and the scatter-corrected images with AC performed by using Chang’s method, CT-based attenuation correction (CTAC), CT-based iterative attenuation compensation during reconstruction (CTIACR), and the CTMAC. From the correction results, we find out that the errors of the previous six configurations are mostly quite similar. The CTMAC needs the shortest correction time while obtaining good AC results. Hsin-Hui Lee and Jyh-Cheng Chen Copyright © 2013 Hsin-Hui Lee and Jyh-Cheng Chen. All rights reserved. Mon, 10 Jun 2013 13:02:19 +0000 http://www.hindawi.com/journals/cmmm/2013/390325/ To achieve a better therapeutic effect and suppress side effects for lung cancer treatments, latency involved in current radiotherapy devices is aimed to be compensated for improving accuracy of continuous (not gating) irradiation to a respiratory moving tumor. A novel prediction method of lung tumor motion is developed for compensating the latency. An essential core of the method is to extract information valuable for the prediction, that is, the periodic nature inherent in respiratory motion. A seasonal autoregressive model useful to represent periodic motion has been extended to take into account the fluctuation of periodic nature in respiratory motion. The extended model estimates the fluctuation by using a correlation-based analysis for adaptation. The prediction performance of the proposed method was evaluated by using data sets of actual tumor motion and compared with those of the state-of-the-art methods. The proposed method demonstrated a high performance within submillimeter accuracy. That is, the average error of 1.0 s ahead predictions was  mm. The accuracy achieved by the proposed method was the best among those by the others. The results suggest that the method can compensate the latency with sufficient accuracy for clinical use and contribute to improve the irradiation accuracy to the moving tumor. Kei Ichiji, Noriyasu Homma, Masao Sakai, Yuichiro Narita, Yoshihiro Takai, Xiaoyong Zhang, Makoto Abe, Norihiro Sugita, and Makoto Yoshizawa Copyright © 2013 Kei Ichiji et al. All rights reserved. Thu, 06 Jun 2013 18:53:39 +0000 http://www.hindawi.com/journals/cmmm/2013/914124/ Quantifying the pathological features of flexor tendon pulleys is essential for grading the trigger finger since it provides clinicians with objective evidence derived from microscopic images. Although manual grading is time consuming and dependent on the observer experience, there is a lack of image processing methods for automatically extracting pulley pathological features. In this paper, we design and develop a color-based image segmentation system to extract the color and shape features from pulley microscopic images. Two parameters which are the size ratio of abnormal tissue regions and the number ratio of abnormal nuclei are estimated as the pathological progression indices. The automatic quantification results show clear discrimination among different levels of diseased pulley specimens which are prone to misjudgments for human visual inspection. The proposed system provides a reliable and automatic way to obtain pathological parameters instead of manual evaluation which is with intra- and interoperator variability. Experiments with 290 microscopic images from 29 pulley specimens show good correspondence with pathologist expectations. Hence, the proposed system has great potential for assisting clinical experts in routine histopathological examinations. Yung-Chun Liu, Hsin-Chen Chen, Hui-Hsuan Shih, Tai-Hua Yang, Hsiao-Bai Yang, Dee-Shan Yang, Fong-Chin Su, and Yung-Nien Sun Copyright © 2013 Yung-Chun Liu et al. All rights reserved. Thu, 06 Jun 2013 15:36:12 +0000 http://www.hindawi.com/journals/cmmm/2013/619658/ Differentiating lymphomas and glioblastomas is important for proper treatment planning. A number of works have been proposed but there are still some problems. For example, many works depend on thresholding a single feature value, which is susceptible to noise. In other cases, experienced observers are required to extract the feature values or to provide some interactions with the system. Even if experts are involved, interobserver variance becomes another problem. In addition, most of the works use only one or a few slice(s) because 3D tumor segmentation is time consuming. In this paper, we propose a tumor classification system that analyzes the luminance distribution of the whole tumor region. Typical cases are classified by the luminance range thresholding and the apparent diffusion coefficients (ADC) thresholding. Nontypical cases are classified by a support vector machine (SVM). Most of the processing elements are semiautomatic. Therefore, even novice users can use the system easily and get the same results as experts. The experiments were conducted using 40 MRI datasets. The classification accuracy of the proposed method was 91.1% without the ADC thresholding and 95.4% with the ADC thresholding. On the other hand, the baseline method, the conventional ADC thresholding, yielded only 67.5% accuracy. Toshihiko Yamasaki, Tsuhan Chen, Toshinori Hirai, and Ryuji Murakami Copyright © 2013 Toshihiko Yamasaki et al. All rights reserved. Wed, 05 Jun 2013 11:25:20 +0000 http://www.hindawi.com/journals/cmmm/2013/196259/ Minimum description length (MDL) based group-wise registration was a state-of-the-art method to determine the corresponding points of 3D shapes for the construction of statistical shape models (SSMs). However, it suffered from the problem that determined corresponding points did not uniformly spread on original shapes, since corresponding points were obtained by uniformly sampling the aligned shape on the parameterized space of unit sphere. We proposed a particle-system based method to obtain adaptive sampling positions on the unit sphere to resolve this problem. Here, a set of particles was placed on the unit sphere to construct a particle system whose energy was related to the distortions of parameterized meshes. By minimizing this energy, each particle was moved on the unit sphere. When the system became steady, particles were treated as vertices to build a spherical mesh, which was then relaxed to slightly adjust vertices to obtain optimal sampling-positions. We used 47 cases of (left and right) lungs and 50 cases of livers, (left and right) kidneys, and spleens for evaluations. Experiments showed that the proposed method was able to resolve the problem of the original MDL method, and the proposed method performed better in the generalization and specificity tests. Rui Xu, Xiangrong Zhou, Yasushi Hirano, Rie Tachibana, Takeshi Hara, Shoji Kido, and Hiroshi Fujita Copyright © 2013 Rui Xu et al. All rights reserved. Tue, 04 Jun 2013 09:42:11 +0000 http://www.hindawi.com/journals/cmmm/2013/830745/ Arteriovenous fistula (AVF) is an important vascular access for hemodialysis (HD) treatment but has 20–60% rate of early failure. Detecting association between patient's parameters and early AVF failure is important for reducing its prevalence and relevant costs. Also predicting incidence of this complication in new patients is a beneficial controlling procedure. Patient safety and preservation of early AVF failure is the ultimate goal. Our research society is Hasheminejad Kidney Center (HKC) of Tehran, which is one of Iran's largest renal hospitals. We analyzed data of 193 HD patients using supervised techniques of data mining approach. There were 137 male (70.98%) and 56 female (29.02%) patients introduced into this study. The average of age for all the patients was 53.87 ± 17.47 years. Twenty eight patients had smoked and the number of diabetic patients and nondiabetics was 87 and 106, respectively. A significant relationship was found between “diabetes mellitus,” “smoking,” and “hypertension” with early AVF failure in this study. We have found that these mentioned risk factors have important roles in outcome of vascular surgery, versus other parameters such as “age.” Then we predicted this complication in future AVF surgeries and evaluated our designed prediction methods with accuracy rates of 61.66%–75.13%. Mohammad Rezapour, Morteza Khavanin Zadeh, and Mohammad Mehdi Sepehri Copyright © 2013 Mohammad Rezapour et al. All rights reserved. Mon, 03 Jun 2013 15:42:49 +0000 http://www.hindawi.com/journals/cmmm/2013/983829/ Metuximab is the generic name of Licartin, a new drug for radioimmunotherapy of hepatocellular carcinoma. Although it is known to be a mouse monoclonal antibody against CD147, the complete epitope mediating the binding of metuximab to CD147 remains unknown. We panned the Ph.D.-12 phage display peptide library against metuximab and got six mimotopes. The following bioinformatics analysis based on mimotopes suggested that metuximab recognizes a conformational epitope composed of more than 20 residues. The residues of its epitope may include T28, V30, K36, L38, K57, F74, D77, S78, D79, D80, Q81, G83, S86, N98, Q100, L101, H102, G103, P104, V131, P132, and K191. The homology modeling of metuximab and the docking of CD147 to metuximab were also performed. Based on the top one docking model, the epitope was predicted to contain 28 residues: AGTVFTTV (23–30), I37, D45, E84, V88, EPMGTANIQLH (92–102), VPP (131–133), Q164, and K191. Almost half of the residues predicted on the basis of mimotope analysis also appear in the docking result, indicating that both results are reliable. As the predicted epitopes of metuximab largely overlap with interfaces of CD147-CD147 interactions, a structural mechanism of metuximab is proposed as blocking the formation of CD147 dimer. Bifang He, Canquan Mao, Beibei Ru, Hesong Han, Peng Zhou, and Jian Huang Copyright © 2013 Bifang He et al. All rights reserved. Mon, 27 May 2013 11:19:04 +0000 http://www.hindawi.com/journals/cmmm/2013/730374/ Previous studies have shown that the dorsal premotor cortex (PMd) neurons are relevant to reaching as well as grasping. In order to investigate their specific contribution to reaching and grasping, respectively, we design two experimental paradigms to separate these two factors. Two monkeys are instructed to reach in four directions but grasp the same object and grasp four different objects but reach in the same direction. Activities of the neuron ensemble in PMd of the two monkeys are collected while performing the tasks. Mutual information (MI) is carried out to quantitatively evaluate the neurons’ tuning property in both tasks. We find that there exist neurons in PMd that are tuned only to reaching, tuned only to grasping, and tuned to both tasks. When applied with a support vector machine (SVM), the movement decoding accuracy by the tuned neuron subset in either task is quite close to the performance by full ensemble. Furthermore, the decoding performance improves significantly by adding the neurons tuned to both tasks into the neurons tuned to one property only. These results quantitatively distinguish the diversity of the neurons tuned to reaching and grasping in the PMd area and verify their corresponding contributions to BMI decoding. Yan Cao, Yaoyao Hao, Yuxi Liao, Kai Xu, Yiwen Wang, Shaomin Zhang, Qiaosheng Zhang, Weidong Chen, and Xiaoxiang Zheng Copyright © 2013 Yan Cao et al. All rights reserved. Sun, 26 May 2013 14:35:06 +0000 http://www.hindawi.com/journals/cmmm/2013/832509/ Screening mammography is the most effective means for early detection of breast cancer. Although general rules for discriminating malignant and benign lesions exist, radiologists are unable to perfectly detect and classify all lesions as malignant and benign, for many reasons which include, but are not limited to, overlap of features that distinguish malignancy, difficulty in estimating disease risk, and variability in recommended management. When predictive variables are numerous and interact, ad hoc decision making strategies based on experience and memory may lead to systematic errors and variability in practice. The integration of computer models to help radiologists increase the accuracy of mammography examinations in diagnostic decision making has gained increasing attention in the last two decades. In this study, we provide an overview of one of the most commonly used models, artificial neural networks (ANNs), in mammography interpretation and diagnostic decision making and discuss important features in mammography interpretation. We conclude by discussing several common limitations of existing research on ANN-based detection and diagnostic models and provide possible future research directions. Turgay Ayer, Qiushi Chen, and Elizabeth S. Burnside Copyright © 2013 Turgay Ayer et al. All rights reserved. Sun, 26 May 2013 10:43:21 +0000 http://www.hindawi.com/journals/cmmm/2013/482941/ We analyzed a statistical model of diaphragm motion using regular principal component analysis (PCA) and generalized N-dimensional PCA (GND-PCA). First, we generate 4D MRI of respiratory motion from 2D MRI using an intersection profile method. We then extract semiautomatically the diaphragm boundary from the 4D-MRI to get subject-specific diaphragm motion. In order to build a general statistical model of diaphragm motion, we normalize the diaphragm motion in time and spatial domains and evaluate the diaphragm motion model of 10 healthy subjects by applying regular PCA and GND-PCA. We also validate the results using the leave-one-out method. The results show that the first three principal components of regular PCA contain more than 98% of the total variation of diaphragm motion. However, validation using leave-one-out method gives up to 5.0 mm mean of error for right diaphragm motion and 3.8 mm mean of error for left diaphragm motion. Model analysis using GND-PCA provides about 1 mm margin of error and is able to reconstruct the diaphragm model by fewer samples. Windra Swastika, Yoshitada Masuda, Rui Xu, Shoji Kido, Yen-Wei Chen, and Hideaki Haneishi Copyright © 2013 Windra Swastika et al. 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.