{"title":"Combined spatial and frequency domain coding algorithm","authors":"Alghannai. M. Rhoma, A. Abobaker, Daw. A. Asdirah","doi":"10.1109/ICCMA.2013.6506151","DOIUrl":"https://doi.org/10.1109/ICCMA.2013.6506151","url":null,"abstract":"Usage of image has been increasing and used in many applications. Image compression plays vital role in saving storage space and saving time while sending images over network. One important point of delivering digital image is time. In this paper we concentrated on the speed of image sending with reasonable quality. The aim of this paper is to reduce image size with reasonable quality. By getting advantage from image transformation in both scope spatial domain and frequency domain. In the case of spatial domain we take the average value (AV) of each four neighbor pixels and put this average value for one of these four neighbor pixels and ignore other three pixels which give us 1:4 compression ratio. In the case of frequency domain, we apply the simplest wavelet transform, the so called Haar wavelet transform (HWT) to reduce the image size with reasonable quality. In order to obtain better performance and overcome the disadvantages of the spatial domain method, we proposed a combined spatial domain and frequency domain (AV-HWT) approach in this paper. Matlab numerical and visualization software was used to perform all of the calculations and generate and display all of the pictures in the simulation. Experimental results prove the effectiveness of proposed algorithm.","PeriodicalId":187834,"journal":{"name":"2013 International Conference on Computer Medical Applications (ICCMA)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121639286","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
E. Beveridge, M. Ma, P. Rea, Kim Bale, P. Anderson
{"title":"3D visualisation for education, diagnosis and treatment of lliotibial band syndrome","authors":"E. Beveridge, M. Ma, P. Rea, Kim Bale, P. Anderson","doi":"10.1109/ICCMA.2013.6506143","DOIUrl":"https://doi.org/10.1109/ICCMA.2013.6506143","url":null,"abstract":"The evolution of medical imaging technologies and computer graphics is leading to dramatic improvements for medical training, diagnosis and treatment, and patient understanding. This paper discusses how volumetric visualization and 3D scanning can be integrated with cadaveric dissection to deliver benefits in the key areas of clinician-patient communication and medical education. The specific area of medical application is a prevalent musculoskeletal disorder-iliotibial (IT) band syndrome. By combining knowledge from cadaveric dissection and volumetric visualization, a virtual laboratory was created using the Unity 3D game engine, as an interactive education tool for use in various settings. The system is designed to improve the experience of clinicians who had commented that their earlier training would have been enhanced by key features of the system, including accurate three-dimensional models generated from computed tomography, high resolution cryosection images of the Visible Human dataset, and surface anatomy generated from a white light scan of an athlete. The finding from the virtual laboratory concept is that knowledge gained through dissection helps enhance the value of the model by incorporating more detail of the distal attachments of the IT band. Experienced clinicians who regularly treat IT band syndrome were excited by the potential of the model and keen to make suggestions for future enhancement.","PeriodicalId":187834,"journal":{"name":"2013 International Conference on Computer Medical Applications (ICCMA)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116736911","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Risk management based early warning system for healthcare industry","authors":"A. Jadi, H. Zedan, T. Alghamdi","doi":"10.1109/ICCMA.2013.6506181","DOIUrl":"https://doi.org/10.1109/ICCMA.2013.6506181","url":null,"abstract":"The Health Delivery Practice with additional innovative technologies become a key ingredient in health care industry. However, under the complex and dynamic environment, predictability, reactivity and accuracy are considered as inherent features of risk management. During the runtime monitoring system, risks are largely observed due to changes in environmental conditions, physical damages and other technical failures. The aim of the research is to provide a risk management based early warning system using runtime monitoring for the healthcare industry for a better performance. The main objective of this research is to propose a novel technique for predicting and mitigating possible risks during runtime. That is, by using runtime monitoring along with neural networks using Java based applications. The present work explored a new technique in which early warning system is developed to identify and mitigate the best solutions for the newly identified risks in runtime using neural networks.","PeriodicalId":187834,"journal":{"name":"2013 International Conference on Computer Medical Applications (ICCMA)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121905908","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Ultrasound elastography as a motion estimation problem","authors":"Marwan H. Hussein, Y. Kadah","doi":"10.1109/ICCMA.2013.6506187","DOIUrl":"https://doi.org/10.1109/ICCMA.2013.6506187","url":null,"abstract":"We study the feasibility of processing B-mode images instead of RF data to generate ultrasound elastography displacement fields. We use the exhaustive search (ES) algorithm which is a basic block matching algorithm from the video compression domain. We also apply two modifications to ES that can enhance both speed and detectability. Quantitative measurements of accuracy and runtime are presented. Results and potential future work are discussed.","PeriodicalId":187834,"journal":{"name":"2013 International Conference on Computer Medical Applications (ICCMA)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124087864","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Bayesian network based classification of mammography structured reports","authors":"A. Farruggia, R. Magro, S. Vitabile","doi":"10.1109/ICCMA.2013.6506150","DOIUrl":"https://doi.org/10.1109/ICCMA.2013.6506150","url":null,"abstract":"In modern medical domain, documents are created directly in electronic form and stored on huge databases containing documents, text in integral form and images. Retrieving right informations from these servers is challenging and, sometimes, this is very time consuming. Current medical technology do not provide a smart methodology classification of such documents based on their content. In this work the radiological structured reports are analysed classified and assigning an appropriate label. The text classifier is used to label a mammographic structured report. The experimental data are real clinical report coming from a hospital server. Analysing the structured report content, the classifier labels the patient structured report as healthy or pathological. The present work uses Information Retrieval techniques to improve the classification process. These technique provide a light semantic analysis to remove negative terms, a removing stop-word step and, finally, a thesaurus is used to uniform used words. The structured reports are classified using a Bayes Naive Classifier. The experimental results provide interesting performance in terms of specificity and sensibility. Others two indexes are computed in order to assess system's robustness: these are the Az (Area under Curve ROC) and σ Az(Az standard error).","PeriodicalId":187834,"journal":{"name":"2013 International Conference on Computer Medical Applications (ICCMA)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125325257","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A low power low noise capacitively coupled chopper instrumentation amplifier in 130 nm CMOS for portable biopotential acquisiton systems","authors":"A. N. Mohamed, H. Ahmed, M. Elkhatib, K. Shehata","doi":"10.1109/ICCMA.2013.6506168","DOIUrl":"https://doi.org/10.1109/ICCMA.2013.6506168","url":null,"abstract":"A low-power, low-noise chopper stabilized CMOS differential difference instrumentation amplifier (CHDDA) for portable biopotential acquisition applications is presented. The proposed 130 nm CMOS chopper stabilized amplifier has 3.2μW power dissipation, thermal noise floor of 10 nV/rtHz and corner frequency in the vicinity of 10 Hz with 1 V supply voltage which performs adequately well in measuring biopotential signals.","PeriodicalId":187834,"journal":{"name":"2013 International Conference on Computer Medical Applications (ICCMA)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127965344","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Computer based analysis for heart and lung signals separation","authors":"F. Ayari, M. Ksouri, A. Alouani","doi":"10.1109/ICCMA.2013.6506152","DOIUrl":"https://doi.org/10.1109/ICCMA.2013.6506152","url":null,"abstract":"In this paper, two methodologies are proposed to enhance the automatic noise cancellation and signal separation between heart and lung sounds. In fact, transient signals such as heart and lung signals may undergo abrupt or sharp change in the first and second derivatives. A real separation between such two interfering mixed signals needs an efficient approach to avoid losing important information in both signals. Rhythmic cardiac signal contains important characteristics which can be exploited to develop adaptive based algorithms that allow efficient separation between lung and heart signals when they are mixed in a recorded signal. In the first proposed methodology we have developed an algorithm based on adaptive filtering technique and build using multiple filtering functions with coefficients correlated to the mixed source signal. In the second methodology, fast independent component analysis was developed to cancel heart sound in lung mixed sound. Both methods are well detailed in this work, and a comparative study is achieved to evaluate the efficiency of each method. A high accuracy of the new proposed algorithms is found and many applications are used to quantify the performances of these techniques.","PeriodicalId":187834,"journal":{"name":"2013 International Conference on Computer Medical Applications (ICCMA)","volume":"105 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133851488","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
F. Makhlouf, Nawrès Khlifa, H. Besbes, C. Ben Amar, B. Soulaiman
{"title":"A comparative study of multiresolution methods to reduce the noise in scintigraphic images","authors":"F. Makhlouf, Nawrès Khlifa, H. Besbes, C. Ben Amar, B. Soulaiman","doi":"10.1109/ICCMA.2013.6506173","DOIUrl":"https://doi.org/10.1109/ICCMA.2013.6506173","url":null,"abstract":"This Scintigraphy represents a tool for exploring functional property shown in several pathologies. Take the example of the ventriculair ejection fraction, the renal clearance and the thyroid activity. However, scintigraphic images are strongly affected by noise. So, our objective in this work is to improve scintigraphic images to obtain sharper images and more reliable diagnosis for better orientation and understanding of pathological phenomenon. This article focuses on the comparison of the multiresolution methods for assessing the quality of scintigraphic images to reduce noise using wavelet, contourlet, curvelet, ridgelet and bandelet.","PeriodicalId":187834,"journal":{"name":"2013 International Conference on Computer Medical Applications (ICCMA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115471866","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Polynomial modeling of the ECG signals","authors":"F. Guendouzi, M. Attari","doi":"10.1109/ICCMA.2013.6506177","DOIUrl":"https://doi.org/10.1109/ICCMA.2013.6506177","url":null,"abstract":"Our aim in this work is the modeling of the ECG data by polynomial transform. We have developed an algorithm that allows the modeling of the ECG signal with the Chebyshev polynomial. This algorithm consists of several steps. The segmentation of the signal, transposition of the signal in the domain of definition of the polynomial to compute the coefficients follows that the following uses to reconstruct the ECG signal. The modeling algorithm is evaluated using the database of MIT-BIH. The firste results obtained by the Chebyshev model exhibit the faithfully reproduction abnormalities includide in the ECG signal.","PeriodicalId":187834,"journal":{"name":"2013 International Conference on Computer Medical Applications (ICCMA)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131087672","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Knowledge management framework for achieving quality of healthcare in the developing countries","authors":"Amararachchi J L, Perera H S C, Pulasinghe K","doi":"10.1109/ICCMA.2013.6506167","DOIUrl":"https://doi.org/10.1109/ICCMA.2013.6506167","url":null,"abstract":"A severe dearth of medical experts in health institutions in the rural and remote areas in developing countries has directly affected the quality of healthcare. This problem can be alleviated by providing facilities to access up to date medical Information and knowledge for doctors who are stationed in these areas to update their knowledge. Since Knowledge Management System (KMS) consists of most related Information and knowledge, medical KMSs could be utilized to enhance the quality of clinical activities. This study was aimed to identify the factors that affect the knowledge management initiatives. Findings of the research have shown that there is a strong association between accessing and using Information/ knowledge in clinical activities and the quality of healthcare. Moreover, attitudes of Medical Practitioners (MP), Infrastructure facilities, patient Information systems, patient treatment, staff benefits etc., have contribute positively towards the success of knowledge management in Health organizations. The research has used the case study methodology for accomplishing the research objectives. Remote and rural areas in Sri Lanka have considered for the case study which is one of the developing countries in the Asian region.","PeriodicalId":187834,"journal":{"name":"2013 International Conference on Computer Medical Applications (ICCMA)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128948600","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}