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Computer Methods and Programs in Biomedicine

Antoine Pironet, Paul D Docherty, Pierre C Dauby, J Geoffrey Chase, Thomas Desaive
BACKGROUND AND OBJECTIVE: Parameters of mathematical models of the cardiovascular system can be used to monitor cardiovascular state, such as total stressed blood volume status, vessel elastance and resistance. To do so, the model parameters have to be estimated from data collected at the patient's bedside. This work considers a seven-parameter model of the cardiovascular system and investigates whether these parameters can be uniquely determined using indices derived from measurements of arterial and venous pressures, and stroke volume...
January 17, 2017: Computer Methods and Programs in Biomedicine
Chung-Ming Lo, Usman Iqbal, Yu-Chuan Jack Li
No abstract text is available yet for this article.
April 2017: Computer Methods and Programs in Biomedicine
Félix Paulano-Godino, Juan J Jiménez-Delgado
BACKGROUND AND OBJECTIVE: The preoperative planning of bone fractures using information from CT scans increases the probability of obtaining satisfactory results, since specialists are provided with additional information before surgery. The reduction of complex bone fractures requires solving a 3D puzzle in order to place each fragment into its correct position. Computer-assisted solutions may aid in this process by identifying the number of fragments and their location, by calculating the fracture zones or even by computing the correct position of each fragment...
April 2017: Computer Methods and Programs in Biomedicine
Xin Li, João L Salinet, Tiago P Almeida, Frederique J Vanheusden, Gavin S Chu, G André Ng, Fernando S Schlindwein
BACKGROUND AND OBJECTIVE: Optimal targets for persistent atrial fibrillation (persAF) ablation are still debated. Atrial regions hosting high dominant frequency (HDF) are believed to participate in the initiation and maintenance of persAF and hence are potential targets for ablation, while rotor ablation has shown promising initial results. Currently, no commercially available system offers the capability to automatically identify both these phenomena. This paper describes an integrated 3D software platform combining the mapping of both frequency spectrum and phase from atrial electrograms (AEGs) to help guide persAF ablation in clinical cardiac electrophysiological studies...
April 2017: Computer Methods and Programs in Biomedicine
Nobutaka Ikeda, Nilanjan Dey, Aditya Sharma, Ajay Gupta, Soumyo Bose, Suvojit Acharjee, Shoaib Shafique, Elisa Cuadrado-Godia, Tadashi Araki, Luca Saba, John R Laird, Andrew Nicolaides, Jasjit S Suri
BACKGROUND AND OBJECTIVES: Standardization of the carotid IMT requires a reference marker in ultrasound scans. It has been shown previously that manual reference marker and manually created carotid segments are used for measuring IMT in these segments. Manual methods are tedious, time consuming, subjective, and prone to errors. Bulb edge can be considered as a reference marker for measurements of the cIMT. However, bulb edge can be difficult to locate in ultrasound scans due to: (a) low signal to noise ratio in the bulb region as compared to common carotid artery region; (b) uncertainty of bulb location in craniocaudal direction; and (c) variability in carotid bulb shape and size...
April 2017: Computer Methods and Programs in Biomedicine
Miroslav Zivanovic, Maciej Niegowski, Pablo Lecumberri, Marisol Gómez
BACKGROUND AND OBJECTIVES: In this paper we propose a novel single-channel harmonic and baseline noise removal approach based on the low-rank matrix factorization theory. It aims to enhance spectrogram sparsity in order to significantly reduce the dimensionality of the underlying sources in the input data. Such a low-rank non-negative representation approach admits efficient noise removal. METHODS: The sparsity is improved by a modification of the time-frequency basis through the following signal processing steps: (1) spectrograms segmentation, (2) non-negative rank estimation, and (3) source grouping...
April 2017: Computer Methods and Programs in Biomedicine
Pouya Nazari, Hossein Pourghassem
BACKGROUND AND OBJECTIVES: Retinal image is one of the most secure biometrics which is widely used in human identification application. This paper represents a rotation and translation-invariant human identification algorithm based on a new definition of geometrical shape features of the retinal image using a hierarchical matching structure. METHODS: In this algorithm, the retinal images are represented by regions which are surrounded by blood vessels that are named Surrounded Regions (SRs)...
April 2017: Computer Methods and Programs in Biomedicine
Arturo Nicola Natali, Emanuele Luigi Carniel, Alessandro Frigo, Chiara Giulia Fontanella, Alessandro Rubini, Yochai Avital, Giulia Maria De Benedictis
BACKGROUND AND OBJECTIVE: An integrated experimental and computational investigation was developed aiming to provide a methodology for characterizing the structural response of the urethral duct. The investigation provides information that are suitable for the actual comprehension of lower urinary tract mechanical functionality and the optimal design of prosthetic devices. METHODS: Experimental activity entailed the execution of inflation tests performed on segments of horse penile urethras from both proximal and distal regions...
April 2017: Computer Methods and Programs in Biomedicine
Xiayu Xu, Wenxiang Ding, Michael D Abràmoff, Ruofan Cao
(BACKGROUND AND OBJECTIVES): Retinal artery and vein classification is an important task for the automatic computer-aided diagnosis of various eye diseases and systemic diseases. This paper presents an improved supervised artery and vein classification method in retinal image. (METHODS): Intra-image regularization and inter-subject normalization is applied to reduce the differences in feature space. Novel features, including first-order and second-order texture features, are utilized to capture the discriminating characteristics of arteries and veins...
April 2017: Computer Methods and Programs in Biomedicine
Fei-Hung Hung, Hung-Wen Chiu
BACKGROUND AND OBJECTIVE: Distinguishing cancer subtypes is critical for selecting the appropriate treatment strategy. Bioinformatics approaches have gradually taken the place of clinical observations and pathological experiments. However, these approaches are typically only used in gene expression profiling. Previous studies have primarily focused on the gene level or specific diseases, and thus pathway-level factors have not been considered. Therefore, a computational method that integrates gene expression and pathway is necessary...
April 2017: Computer Methods and Programs in Biomedicine
Zeinab Arabasadi, Roohallah Alizadehsani, Mohamad Roshanzamir, Hossein Moosaei, Ali Asghar Yarifard
Cardiovascular disease is one of the most rampant causes of death around the world and was deemed as a major illness in Middle and Old ages. Coronary artery disease, in particular, is a widespread cardiovascular malady entailing high mortality rates. Angiography is, more often than not, regarded as the best method for the diagnosis of coronary artery disease; on the other hand, it is associated with high costs and major side effects. Much research has, therefore, been conducted using machine learning and data mining so as to seek alternative modalities...
April 2017: Computer Methods and Programs in Biomedicine
A Mjahad, A Rosado-Muñoz, M Bataller-Mompeán, J V Francés-Víllora, J F Guerrero-Martínez
BACKGROUND AND OBJECTIVE: To safely select the proper therapy for Ventricullar Fibrillation (VF) is essential to distinct it correctly from Ventricular Tachycardia (VT) and other rhythms. Provided that the required therapy would not be the same, an erroneous detection might lead to serious injuries to the patient or even cause Ventricular Fibrillation (VF). The main novelty of this paper is the use of time-frequency (t-f) representation images as the direct input to the classifier. We hypothesize that this method allow to improve classification results as it allows to eliminate the typical feature selection and extraction stage, and its corresponding loss of information...
April 2017: Computer Methods and Programs in Biomedicine
Guang Zhang, Taihu Wu, Zongming Wan, Zhenxing Song, Ming Yu, Dan Wang, Liangzhe Li, Feng Chen, Xinxi Xu
In recent years, numerous adaptive filtering techniques have been developed to suppress the chest compression (CC) artifact for reliable analysis of the electrocardiogram (ECG) rhythm without CC interruption. Unfortunately, the result of rhythm diagnosis during CCs is still unsatisfactory in many studies. The misclassification between corrupted asystole (ASY) and corrupted ventricular fibrillation (VF) is generally regarded as one of the major reasons for the poor performance of reported methods. In order to improve the diagnosis of VF/ASY corrupted by CCs, a novel method combining a least mean-square (LMS) filter and an amplitude spectrum area (AMSA) analysis was developed based only on the analysis of the surface of the corrupted ECG episode...
April 2017: Computer Methods and Programs in Biomedicine
J B Jeeva, Megha Singh
BACKGROUND AND OBJECTIVES: The optical characteristics of biological tissues vary in health and diseases. By analysis of photons scattering process by Monte Carlo simulation (MCS) the inhomogeneities in tissues are to be identified and their images reconstructed. METHODS: Digital phantoms with goat's heart as a control tissue embedded with inhomogeneities adipose (high scattering) and spleen (high absorption) are simulated. The phantoms considered are - (a) simulation of the developed stage of inhomogeneity by inclusion of adipose and spleen tissues in control and (b) its onset stage by increasing the optical parameters by 10% at fixed locations in control tissue...
April 2017: Computer Methods and Programs in Biomedicine
Maryam Tayefi, Mohammad Tajfard, Sara Saffar, Parichehr Hanachi, Ali Reza Amirabadizadeh, Habibollah Esmaeily, Ali Taghipour, Gordon A Ferns, Mohsen Moohebati, Majid Ghayour-Mobarhan
BACKGROUND AND AIMS: Coronary heart disease (CHD) is an important public health problem globally. Algorithms incorporating the assessment of clinical biomarkers together with several established traditional risk factors can help clinicians to predict CHD and support clinical decision making with respect to interventions. Decision tree (DT) is a data mining model for extracting hidden knowledge from large databases. We aimed to establish a predictive model for coronary heart disease using a decision tree algorithm...
April 2017: Computer Methods and Programs in Biomedicine
Siyuan Lu, Shuihua Wang, Yudong Zhang
BACKGROUND AND OBJECTIVE: A relatively new marker-based watershed method was proposed with international readership circulation. In this letter, we put forward a note on the use of max and min symbols in their study. METHODS: We deduced the mathematical equations in their study. RESULTS: We found the ``min'' operation should be changed to ``max'' in original Eqs. (1) and (5). CONCLUSIONS: In spite of the two minor problems, the paper contains many important academic points...
April 2017: Computer Methods and Programs in Biomedicine
Ming-Chin Lin, Usman Iqbal, Yu-Chuan Jack Li
No abstract text is available yet for this article.
March 2017: Computer Methods and Programs in Biomedicine
Zhong Yin, Mengyuan Zhao, Yongxiong Wang, Jingdong Yang, Jianhua Zhang
BACKGROUND AND OBJECTIVE: Using deep-learning methodologies to analyze multimodal physiological signals becomes increasingly attractive for recognizing human emotions. However, the conventional deep emotion classifiers may suffer from the drawback of the lack of the expertise for determining model structure and the oversimplification of combining multimodal feature abstractions. METHODS: In this study, a multiple-fusion-layer based ensemble classifier of stacked autoencoder (MESAE) is proposed for recognizing emotions, in which the deep structure is identified based on a physiological-data-driven approach...
March 2017: Computer Methods and Programs in Biomedicine
Reza Boostani, Foroozan Karimzadeh, Mohammad Nami
BACKGROUND AND OBJECTIVE: Proper scoring of sleep stages can give clinical information on diagnosing patients with sleep disorders. Since traditional visual scoring of the entire sleep is highly time-consuming and dependent to experts' experience, automatic schemes based on electroencephalogram (EEG) analysis are broadly developed to solve these problems. This review presents an overview on the most suitable methods in terms of preprocessing, feature extraction, feature selection and classifier adopted to precisely discriminate the sleep stages...
March 2017: Computer Methods and Programs in Biomedicine
César Domínguez, Jónathan Heras, Eloy Mata, Vico Pascual, Maria Soledad Vázquez-Garcidueñas, Gerardo Vázquez-Marrufo
BACKGROUND AND OBJECTIVE: The manual transformation of DNA fingerprints of dominant markers into the input of tools for population genetics analysis is a time-consuming and error-prone task; especially when the researcher deals with a large number of samples. In addition, when the researcher needs to use several tools for population genetics analysis, the situation worsens due to the incompatibility of data-formats across tools. The goal of this work consists in automating, from banding patterns of gel images, the input-generation for the great diversity of tools devoted to population genetics analysis...
March 2017: Computer Methods and Programs in Biomedicine
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