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Computer Methods and Programs in Biomedicine

Z T Al-Qaysi, B B Zaidan, A A Zaidan, M S Suzani
CONTEXT: Intelligent wheelchair technology has recently been utilised to address several mobility problems. Techniques based on brain-computer interface (BCI) are currently used to develop electric wheelchairs. Using human brain control in wheelchairs for people with disability has elicited widespread attention due to its flexibility. OBJECTIVE: This study aims to determine the background of recent studies on wheelchair control based on BCI for disability and map the literature survey into a coherent taxonomy...
June 18, 2018: Computer Methods and Programs in Biomedicine
Zhaohui Liang, Jun Liu, Aihua Ou, Honglai Zhang, Ziping Li, Jimmy Xiangji Huang
BACKGROUND: Computer-aided medical decision-making (CAMDM) is the method to utilize massive EMR data as both empirical and evidence support for the decision procedure of healthcare activities. Well-developed information infrastructure, such as hospital information systems and disease surveillance systems, provides abundant data for CAMDM. However, the complexity of EMR data with abstract medical knowledge makes the conventional model incompetent for the analysis. Thus a deep belief networks (DBN) based model is proposed to simulate the information analysis and decision-making procedure in medical practice...
May 4, 2018: Computer Methods and Programs in Biomedicine
F Niknejad Mazandarani, M Mohebbi
BACKGROUND AND OBJECTIVE: Automatic processing and accurate diagnosis of wide complex tachycardia (WCT) arrhythmia groups using electrocardiogram signals (ECG) remains a challenge. WCT arrhythmia consists of two main groups: ventricular tachycardia (VT) and supraventricular tachycardia with aberrancy (SVT-A). These two groups have similar morphologies in the realm of ECG signals. VT and SVT-A arrhythmias originate from the ventricle and atrium, respectively. Hence, inaccurate diagnosis of SVT-A instead of VT can be fatal...
April 20, 2018: Computer Methods and Programs in Biomedicine
Zhixing Jiang, David Zhang, Guangming Lu
BACKGROUND AND OBJECTIVES: Radial artery pulse diagnosis has been playing an important role in traditional Chinese medicine (TCM). For its non-invasion and convenience, the pulse diagnosis has great significance in diseases analysis of modern medicine. The practitioners sense the pulse waveforms in patients' wrist to make diagnoses based on their non-objective personal experience. With the researches of pulse acquisition platforms and computerized analysis methods, the objective study on pulse diagnosis can help the TCM to keep up with the development of modern medicine...
April 19, 2018: Computer Methods and Programs in Biomedicine
Pedro Henrique Bandeira Diniz, Thales Levi Azevedo Valente, João Otávio Bandeira Diniz, Aristófanes Corrêa Silva, Marcelo Gattass, Nina Ventura, Bernardo Carvalho Muniz, Emerson Leandro Gasparetto
BACKGROUND AND OBJECTIVE: White matter lesions are non-static brain lesions that have a prevalence rate up to 98% in the elderly population. Because they may be associated with several brain diseases, it is important that they are detected as soon as possible. Magnetic Resonance Imaging (MRI) provides three-dimensional data with the possibility to detect and emphasize contrast differences in soft tissues, providing rich information about the human soft tissue anatomy. However, the amount of data provided for these images is far too much for manual analysis/interpretation, representing a difficult and time-consuming task for specialists...
April 19, 2018: Computer Methods and Programs in Biomedicine
Phung-Anh Alex Nguyen, Yu-Chuan Jack Li
No abstract text is available yet for this article.
August 2018: Computer Methods and Programs in Biomedicine
Pankush Kalgotra, Ramesh Sharda
BACKGROUND AND OBJECTIVE: Because examining correlated (vs. individual) brain activity is a superior method for locating neural correlates of a stimulus, using a network approach for analyzing brain activity is gaining interest. In this study, we propose and illustrate the use of association rule mining (ARM) to analyze brain regions that are activated simultaneously. ARM is commonly used in marketing and other disciplines to help determine items that might be purchased together. We apply this technique toward identifying correlated brain regions that may respond simultaneously to specific stimuli...
August 2018: Computer Methods and Programs in Biomedicine
Takashi Teramoto, Takeshi Kamiya, Taira Sakurai, Fuminori Kanaya
BACKGROUND AND OBJECTIVE: Computational homology is an emerging mathematical tool for characterizing shapes of data. In this work, we present a methodology using computational homology for obtaining quantitative measurements of the connectivity in bone morphometry. We introduce the Betti number ratios as novel morphological descriptor for the classification of bone fine structures in three dimensions. METHODS: A total of 51 Japanese white rabbits were used to investigate the connectivity of bone trabeculae after the administration of alendronate in a tendon graft model in rabbits...
August 2018: Computer Methods and Programs in Biomedicine
Leonardo Bonato Felix, Paulo Fábio Figueiredo Rocha, Eduardo Mazoni Andrade Marçal Mendes, Antonio Mauricio Ferreira Leite Miranda de Sá
BACKGROUND AND OBJECTIVE: The local spectral F-test (SFT) corresponds to a statistical way of assessing whether the spectrum of a signal is flat in the vicinity of a specific frequency. The power of this univariate test (comparing one frequency component  against its neighbours using only one signal) depends on the signal-to-noise ratio, which is fixed in the case of electroencephalogram (EEG) analysis. However, this limitation could be overcome by considering more signals in the analysis...
August 2018: Computer Methods and Programs in Biomedicine
A Idri, H Benhar, J L Fernández-Alemán, I Kadi
BACKGROUND AND OBJECTIVE: Datamining (DM) has, over the last decade, received increased attention in the medical domain and has been widely used to analyze medical datasets in order to extract useful knowledge and previously unknown patterns. However, historical medical data can often comprise inconsistent, noisy, imbalanced, missing and high dimensional data. These challenges lead to a serious bias in predictive modeling and reduce the performance of DM techniques. Data preprocessing is, therefore, an essential step in knowledge discovery as regards improving the quality of data and making it appropriate and suitable for DM techniques...
August 2018: Computer Methods and Programs in Biomedicine
Ângela Carvalho, Tiago Esteves, Pedro Quelhas, Fernando Jorge Monteiro
BACKGROUND AND OBJECTIVE: Surface topography of biomaterials has been shown to have an effect on cells behaviour. Cell-material interactions can be visually characterized by assessing both cell shape and spreading at initial time-points and, its migration patterns, as a response to the underlying topography. Whilst many have reported the study of cell migration and shape with fluorescence labelling, the focus on evaluating cells response to surface topography is to observe, under real-time conditions, interactions between cells and surfaces...
August 2018: Computer Methods and Programs in Biomedicine
Tianyu Fu, Qin Li, Jianjun Zhu, Danni Ai, Yong Huang, Hong Song, Yurong Jiang, Yongtian Wang, Jian Yang
BACKGROUND AND OBJECTIVE: A framework of sparse deformation prediction using Markove Decision Processes is proposed for achieving a rapid and accurate registration by providing a suitable initial deformation. METHODS: In the proposed framework, the tree is built based on the training set for each patch from the template image. The template patch is considered as the root. The node is the patch group in which multiple similar patches are extracted around a key point on the training image...
August 2018: Computer Methods and Programs in Biomedicine
Ermanno Cordelli, Giuseppe Maulucci, Marco De Spirito, Alessandro Rizzi, Dario Pitocco, Paolo Soda
BACKGROUND AND OBJECTIVE: Investigation of membrane fluidity by metabolic functional imaging opens up a new and important area of translational research in type 1 diabetes mellitus, being a useful and sensitive biomarker for disease monitoring and treatment. We investigate here how data on membrane fluidity can be used for diabetes monitoring. METHODS: We present a decision support system that distinguishes between healthy subjects, type 1 diabetes mellitus patients, and type 1 diabetes mellitus patients with complications...
August 2018: Computer Methods and Programs in Biomedicine
Yung-Chuan Chen, Yuan-Kun Tu, Yi-Jung Tsai, Yi-Shan Tsai, Cheng-Yo Yen, Shih-Chieh Yang, Chih-Kun Hsiao
BACKGROUND AND OBJECTIVE: During bone drilling, the heat generated by friction depends directly on bone quality and surgical parameters. Excessive bone temperatures may cause thermal necrosis around the pilot hole, weaken the purchase of inserted screws, and in turn reduce the stability of screw fixation. A few studies have addressed the key parameters of drilling, such as the rotation speed of the drill-bit, feed force (axial force), feed rate, tool type, and tip geometry of drill-bits...
August 2018: Computer Methods and Programs in Biomedicine
Feiwei Qin, Nannan Gao, Yong Peng, Zizhao Wu, Shuying Shen, Artur Grudtsin
BACKGROUND AND OBJECTIVE: Leukocyte classification and cytometry have wide applications in medical domain, previous researches usually exploit machine learning techniques to classify leukocytes automatically. However, constrained by the past development of machine learning techniques, for example, extracting distinctive features from raw microscopic images are difficult, the widely used SVM classifier only has relative few parameters to tune, these methods cannot efficiently handle fine-grained classification cases when the white blood cells have up to 40 categories...
August 2018: Computer Methods and Programs in Biomedicine
Imma Boada, Antonio Rodriguez-Benitez, Santiago Thió-Henestrosa, Josep Olivet, Josep Soler
BACKGROUND AND OBJECTIVE: Virtual simulations recreate scenarios where student nurses can practice procedures in a safe and supervised manner and with no risk to the patient. Virtual scenarios include digital characters that reproduce human actions. Generally, these characters are modeled as males and restricted roles are assigned to females. Our objective is to evaluate how the character gender of a victim in a scenario created to practice the cardiopulmonary resuscitation protocol (CPR) affects performance of student nurses...
August 2018: Computer Methods and Programs in Biomedicine
Mohammed A Al-Masni, Mugahed A Al-Antari, Mun-Taek Choi, Seung-Moo Han, Tae-Seong Kim
BACKGROUND AND OBJECTIVE: Automatic segmentation of skin lesions in dermoscopy images is still a challenging task due to the large shape variations and indistinct boundaries of the lesions. Accurate segmentation of skin lesions is a key prerequisite step for any computer-aided diagnostic system to recognize skin melanoma. METHODS: In this paper, we propose a novel segmentation methodology via full resolution convolutional networks (FrCN). The proposed FrCN method directly learns the full resolution features of each individual pixel of the input data without the need for pre- or post-processing operations such as artifact removal, low contrast adjustment, or further enhancement of the segmented skin lesion boundaries...
August 2018: Computer Methods and Programs in Biomedicine
Andrea Calvo-Echenique, José Cegoñino, Raúl Chueca, Amaya Pérez-Del Palomar
BACKGROUND AND OBJECTIVE: Spinal degeneration and instability are commonly treated with interbody fusion cages either alone or supplemented with posterior instrumentation with the aim to immobilise the segment and restore intervertebral height. The purpose of this work is to establish a tool which may help to understand the effects of intervertebral cage design and placement on the biomechanical response of a patient-specific model to help reducing post-surgical complications such as subsidence and segment instability...
August 2018: Computer Methods and Programs in Biomedicine
Zhiqiong Wang, Junchang Xin, Peishun Sun, Zhixiang Lin, Yudong Yao, Xiaosong Gao
BACKGROUND AND OBJECTIVE: Among all malignant tumors, lung cancer ranks in the top in mortality rate. Pulmonary nodule is the early manifestation of lung cancer, and plays an important role in its discovery, diagnosis and treatment. The technology of medical imaging has encountered a rapid development in recent years, thus the amount of pulmonary nodules can be discovered are on the raise, which means even tiny or minor changes in lung can be recorded by the CT images. This paper proposes a pulmonary nodule computer aided diagnosis (CAD) based on semi-supervised extreme learning machine(SS-ELM)...
August 2018: Computer Methods and Programs in Biomedicine
Peng Cao, Xiaoli Liu, Hezi Liu, Jinzhu Yang, Dazhe Zhao, Min Huang, Osmar Zaiane
OBJECTIVE: Alzheimers disease (AD) is characterized by gradual neurodegeneration and loss of brain function, especially for memory during early stages. Regression analysis has been widely applied to AD research to relate clinical and biomarker data such as predicting cognitive outcomes from Magnetic Resonance Imaging (MRI) measures. Recently, the multi-task feature learning (MTFL) methods have been widely studied to predict cognitive outcomes and select the discriminative feature subset from MRI features by incorporating inherent correlations among multiple clinical cognitive measures...
August 2018: Computer Methods and Programs in Biomedicine
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