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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
Minjae Yoo, Jimin Shin, Hyunmin Kim, Jihye Kim, Jaewoo Kang, Aik Choon Tan
BACKGROUND AND OBJECTIVE: Traditional Chinese Medicine (TCM) has been practiced over thousands of years in China and other Asian countries for treating various symptoms and diseases. However, the underlying molecular mechanisms of TCM are poorly understood, partly due to the "multi-component, multi-target" nature of TCM. To uncover the molecular mechanisms of TCM, we perform comprehensive gene expression analysis using connectivity map. METHODS: We interrogated gene expression signatures obtained 102 TCM components using the next generation Connectivity Map (CMap) resource...
April 4, 2018: Computer Methods and Programs in Biomedicine
Charalambos Strouthopoulos, George Anifandis
No abstract text is available yet for this article.
April 4, 2018: Computer Methods and Programs in Biomedicine
Ming-Chin Lin, Yu-Chuan Jack Li
No abstract text is available yet for this article.
July 2018: Computer Methods and Programs in Biomedicine
Kirstine Rosenbeck Gøeg, Rune Kongsgaard Rasmussen, Lasse Jensen, Christian Møller Wollesen, Søren Larsen, Louise Bilenberg Pape-Haugaard
BACKGROUND AND OBJECTIVES: Most telemedicine solutions are proprietary and disease specific which cause a heterogeneous and silo-oriented system landscape with limited interoperability. Solving the interoperability problem would require a strong focus on data integration and standardization in telemedicine infrastructures. Our objective was to suggest a future-proof architecture, that consisted of small loose-coupled modules to allow flexible integration with new and existing services, and the use of international standards to allow high re-usability of modules, and interoperability in the health IT landscape...
July 2018: Computer Methods and Programs in Biomedicine
Jemal Abawajy, Andrei Kelarev, Xun Yi, Herbert F Jelinek
BACKGROUND AND OBJECTIVE: Early diagnosis of cardiac autonomic neuropathy (CAN) is critical for reversing or decreasing its progression and prevent complications. Diagnostic accuracy or precision is one of the core requirements of CAN detection. As the standard Ewing battery tests suffer from a number of shortcomings, research in automating and improving the early detection of CAN has recently received serious attention in identifying additional clinical variables and designing advanced ensembles of classifiers to improve the accuracy or precision of CAN diagnostics...
July 2018: Computer Methods and Programs in Biomedicine
Sami Dhahbi, Walid Barhoumi, Jaroslaw Kurek, Bartosz Swiderski, Michal Kruk, Ezzeddine Zagrouba
BACKGROUND AND OBJECTIVE: The aim of computer-aided-detection (CAD) systems for mammograms is to assist radiologists by marking region of interest (ROIs) depicting abnormalities. However, the confusing appearance of some normal tissues that visually look like masses results in a large proportion of marked ROIs with normal tissues. This paper copes with this problem and proposes a framework to reduce false positive masses detected by CAD. METHODS: To avoid the error induced by the segmentation step, we proposed a segmentation-free framework with particular attention to improve feature extraction and classification steps...
July 2018: Computer Methods and Programs in Biomedicine
Conor Cameron, Ibrahim Khalil, David Castle
BACKGROUND AND OBJECTIVES: Over the last decade, the application of computer vision techniques to the analysis of behavioural patterns has seen a considerable increase in research interest. One such interesting and recent application is the visual behavioural analysis of mental disorders. Despite the very recent surge in interest in this area, relatively little has been done thus far to assist individuals living with Obsessive Compulsive Disorder. The work proposed herein represents a proof of concept system designed to demonstrate the efficacy of such an approach, from the computational perspective...
July 2018: Computer Methods and Programs in Biomedicine
Kalpana Raja, Jeyakumar Natarajan
BACKGROUND: Extraction of protein phosphorylation information from biomedical literature has gained much attention because of the importance in numerous biological processes. OBJECTIVE: In this study, we propose a text mining methodology which consists of two phases, NLP parsing and SVM classification to extract phosphorylation information from literature. METHODS: First, using NLP parsing we divide the data into three base-forms depending on the biomedical entities related to phosphorylation and further classify into ten sub-forms based on their distribution with phosphorylation keyword...
July 2018: Computer Methods and Programs in Biomedicine
Meshari Almeshari, Mohamed Khalifa, Ashraf El-Metwally, Mowafa Househ, Abdullah Alanazi
BACKGROUND AND OBJECTIVE: Paper-based forms have been widely used to document patient health information for anesthesia; however, hospitals are now switching to electronic patient file documentation for anesthesia. The aim of this study is to compare the quality of paper-based and electronic pre-anesthesia assessment forms. METHODS: The research conducted in this study was quasi-experimental using a pretest-posttest design without a control group. The study was conducted at King Abdulaziz Medical City, Riyadh (KAMC-RD) during November 2015...
July 2018: Computer Methods and Programs in Biomedicine
Jiajia Guo, Hongwei Du, Jianyue Zhu, Ting Yan, Bensheng Qiu
BACKGROUND AND OBJECTIVE: Relative location prediction in computed tomography (CT) scan images is a challenging problem. Many traditional machine learning methods have been applied in attempts to alleviate this problem. However, the accuracy and speed of these methods cannot meet the requirement of medical scenario. In this paper, we propose a regression model based on one-dimensional convolutional neural networks (CNN) to determine the relative location of a CT scan image both quickly and precisely...
July 2018: Computer Methods and Programs in Biomedicine
Luís Bastião Silva, Alina Trifan, José Luís Oliveira
BACKGROUND AND OBJECTIVE: Data catalogues are a common form of capturing and presenting information about a specific kind of entity (e.g. products, services, professionals, datasets, etc.). However, the construction of a web-based catalogue for a particular scenario normally implies the development of a specific and dedicated solution. In this paper, we present MONTRA, a rapid-application development framework designed to facilitate the integration and discovery of heterogeneous objects, which may be characterized by distinct data structures...
July 2018: Computer Methods and Programs in Biomedicine
Myungsoo Bae, Sangmin Lee, Namkug Kim
BACKGROUND AND OBJECTIVE: To develop and validate a robust and cost-effective 3D respiratory monitoring system based on a Kinect device with a custom-made simple marker. METHODS: A 3D respiratory monitoring system comprising the simple marker and the Microsoft Kinect v2 device was developed. The marker was designed for simple and robust detection, and the tracking algorithm was developed using the depth, RGB, and infra-red images acquired from the Kinect sensor...
July 2018: Computer Methods and Programs in Biomedicine
GeethaRamani R, Lakshmi Balasubramanian
BACKGROUND AND OBJECTIVE: Macula segmentation and fovea localization is one of the primary tasks in retinal analysis as they are responsible for detailed vision. Existing approaches required segmentation of retinal structures viz. optic disc and blood vessels for this purpose. METHOD: This work avoids knowledge of other retinal structures and attempts data mining techniques to segment macula. Unsupervised clustering algorithm is exploited for this purpose. Selection of initial cluster centres has a great impact on performance of clustering algorithms...
July 2018: Computer Methods and Programs in Biomedicine
Vanbang Le, Dawei Yang, Yu Zhu, Bingbing Zheng, Chunxue Bai, Hongcheng Shi, Jie Hu, Changwen Zhai, Shaohua Lu
BACKGROUND AND OBJECTIVES: To improve lung nodule classification efficiency, we propose a lung nodule CT image characterization method. We propose a multi-directional feature extraction method to effectively represent nodules of different risk levels. The proposed feature combined with pattern recognition model to classify lung adenocarcinomas risk to four categories: Atypical Adenomatous Hyperplasia (AAH), Adenocarcinoma In Situ (AIS), Minimally Invasive Adenocarcinoma (MIA), and Invasive Adenocarcinoma (IA)...
July 2018: Computer Methods and Programs in Biomedicine
Mohammad Alkhatib, Adel Hafiane, Omar Tahri, Pierre Vieyres, Alain Delbos
BACKGROUND AND OBJECTIVE: In the last decade, Ultrasound-Guided Regional Anesthesia (UGRA) gained importance in surgical procedures and pain management, due to its ability to perform target delivery of local anesthetics under direct sonographic visualization. However, practicing UGRA can be challenging, since it requires high skilled and experienced operator. Among the difficult task that the operator can face, is the tracking of the nerve structure in ultrasound images. Tracking task in US images is very challenging due to the noise and other artifacts...
July 2018: Computer Methods and Programs in Biomedicine
Wei Pan, Dalel Bouslimi, Mohamed Karasad, Michel Cozic, Gouenou Coatrieux
BACKGROUND AND OBJECTIVE: Advances in information and communication technologies boost the sharing and remote access to medical images. Along with this evolution, needs in terms of data security are also increased. Watermarking can contribute to better protect images by dissimulating into their pixels some security attributes (e.g., digital signature, user identifier). But, to take full advantage of this technology in healthcare, one key problem to address is to ensure that the image distortion induced by the watermarking process does not endanger the image diagnosis value...
July 2018: Computer Methods and Programs in Biomedicine
Shumoos Al-Fahdawi, Rami Qahwaji, Alaa S Al-Waisy, Stanley Ipson, Maryam Ferdousi, Rayaz A Malik, Arun Brahma
BACKGROUND AND OBJECTIVE: Corneal endothelial cell abnormalities may be associated with a number of corneal and systemic diseases. Damage to the endothelial cells can significantly affect corneal transparency by altering hydration of the corneal stroma, which can lead to irreversible endothelial cell pathology requiring corneal transplantation. To date, quantitative analysis of endothelial cell abnormalities has been manually performed by ophthalmologists using time consuming and highly subjective semi-automatic tools, which require an operator interaction...
July 2018: Computer Methods and Programs in Biomedicine
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