Proceedings. IEEE International Symposium on Computer-Based Medical Systems最新文献

{"title":"Automated Detection of 3D Landmarks for the Elimination of Non-Biological Variation in Geometric Morphometric Analyses.","authors":"D Aneja,&nbsp;S R Vora,&nbsp;E D Camci,&nbsp;L G Shapiro,&nbsp;T C Cox","doi":"10.1109/CBMS.2015.86","DOIUrl":"https://doi.org/10.1109/CBMS.2015.86","url":null,"abstract":"<p><p>Landmark-based morphometric analyses are used by anthropologists, developmental and evolutionary biologists to understand shape and size differences (eg. in the cranioskeleton) between groups of specimens. The standard, labor intensive approach is for researchers to manually place landmarks on 3D image datasets. As landmark recognition is subject to inaccuracies of human perception, digitization of landmark coordinates is typically repeated (often by more than one person) and the mean coordinates are used. In an attempt to improve efficiency and reproducibility between researchers, we have developed an algorithm to locate landmarks on CT mouse hemi-mandible data. The method is evaluated on 3D meshes of 28-day old mice, and results compared to landmarks manually identified by experts. Quantitative shape comparison between two inbred mouse strains demonstrate that data obtained using our algorithm also has enhanced statistical power when compared to data obtained by manual landmarking.</p>","PeriodicalId":74567,"journal":{"name":"Proceedings. IEEE International Symposium on Computer-Based Medical Systems","volume":"2015 ","pages":"78-83"},"PeriodicalIF":0.0,"publicationDate":"2015-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/CBMS.2015.86","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"34078875","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Lyria PACS: A Case Study Saves Ten Million Dollars in a Brazilian Hospital","authors":"D. F. Carvalho, J. A. Guerrero, P. M. A. Marques, Alessandra Alaniz Macedo","doi":"10.1109/CBMS.2015.87","DOIUrl":"https://doi.org/10.1109/CBMS.2015.87","url":null,"abstract":"","PeriodicalId":74567,"journal":{"name":"Proceedings. IEEE International Symposium on Computer-Based Medical Systems","volume":"89 1","pages":"326-329"},"PeriodicalIF":0.0,"publicationDate":"2015-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76264439","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 Multicriteria Method for Cervical Tumor Segmentation in Positron Emission Tomography","authors":"Andre Luis Resende Monteiro, A. Machado, Marcelo Henrique Mamede Lewer","doi":"10.1109/CBMS.2014.52","DOIUrl":"https://doi.org/10.1109/CBMS.2014.52","url":null,"abstract":"Accurate delineation of tumors is a fundamental requirement for proper planning and subsequent cancer treatment. In this paper, we propose to model the process of tumor segmentation as a multicriteria decision making problem, considering the information embedded in both Positron Emission Tomography (PET) and Computed tomography (CT) images. A set of images of cervical tumors were semi-automated segmented and the results compared with a manual delineation. The results show that using a multiple criteria approach in the segmentation process can improve sensitivity, and the utilization of both PET and CT images may be a factor for improving precision.","PeriodicalId":74567,"journal":{"name":"Proceedings. IEEE International Symposium on Computer-Based Medical Systems","volume":"60 1","pages":"205-208"},"PeriodicalIF":0.0,"publicationDate":"2014-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90458369","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":"Classifying Craniosynostosis with a 3D Projection-Based Feature Extraction System.","authors":"Irma Lam, Michael Cunningham, Matthew Speltz, Linda Shapiro","doi":"10.1109/CBMS.2014.63","DOIUrl":"10.1109/CBMS.2014.63","url":null,"abstract":"<p><p>Craniosynostosis, a disorder in which one or more fibrous joints of the skull fuse prematurely, causes skull deformity and is associated with increased intracranial pressure and developmental delays. Although clinicians can easily diagnose craniosynostosis and can classify its type, being able to quantify the condition is an important problem in craniofacial research. While several papers have attempted this quantification through statistical models, the methods have not been intuitive to biomedical researchers and clinicians who want to use them. The goal of this work was to develop a general platform upon which new quantification measures could be developed and tested. The features reported in this paper were developed as basic shape measures, both single-valued and vector-valued, that are extracted from a single plane projection of the 3D skull. This technique allows us to process images that would otherwise be eliminated in previous systems due to poor resolution, noise or imperfections on their CT scans. We test our new features on classification tasks and also compare their performance to previous research. In spite of its simplicity, the classification accuracy of our new features is significantly higher than previous results on head CT scan data from the same research studies.</p>","PeriodicalId":74567,"journal":{"name":"Proceedings. IEEE International Symposium on Computer-Based Medical Systems","volume":"2014 ","pages":"215-220"},"PeriodicalIF":0.0,"publicationDate":"2014-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4205084/pdf/nihms634320.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"32770547","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Computer-Based Coding of Occupation Codes for Epidemiological Analyses.","authors":"Daniel E Russ,&nbsp;Kwan-Yuet Ho,&nbsp;Calvin A Johnson,&nbsp;Melissa C Friesen","doi":"10.1109/CBMS.2014.79","DOIUrl":"https://doi.org/10.1109/CBMS.2014.79","url":null,"abstract":"<p><p>Mapping job titles to standardized occupation classification (SOC) codes is an important step in evaluating changes in health risks over time as measured in inspection databases. However, manual SOC coding is cost prohibitive for very large studies. Computer based SOC coding systems can improve the efficiency of incorporating occupational risk factors into large-scale epidemiological studies. We present a novel method of mapping verbatim job titles to SOC codes using a large table of prior knowledge available in the public domain that included detailed description of the tasks and activities and their synonyms relevant to each SOC code. Job titles are compared to our knowledge base to find the closest matching SOC code. A soft Jaccard index is used to measure the similarity between a previously unseen job title and the knowledge base. Additional information such as standardized industrial codes can be incorporated to improve the SOC code determination by providing additional context to break ties in matches.</p>","PeriodicalId":74567,"journal":{"name":"Proceedings. IEEE International Symposium on Computer-Based Medical Systems","volume":"2014 ","pages":"347-350"},"PeriodicalIF":0.0,"publicationDate":"2014-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/CBMS.2014.79","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"32668744","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The role of medical data analytics in reducing health fraud and improving clinical and financial outcomes","authors":"R. B. Rao","doi":"10.1109/CBMS.2013.6627755","DOIUrl":"https://doi.org/10.1109/CBMS.2013.6627755","url":null,"abstract":"Consider the following healthcare trends: (1) There is a tremendous increase in the amount of patient, life sciences and process data in electronic form, fueled by advances in healthcare IT technology, and health reform legislation. (2) The amount of medical information (e.g., evidence-based knowledge) and published knowledge is said to be doubling every few years. (3) There is an explosion in the number of available therapies and diagnostic options for patient care, often enabling precise targeting of therapy to disease conditions. In this talk we will discuss these trends and some of the reasons why, despite these advances, healthcare is facing a crisis: namely, there is a steady unsustainable increase in medical costs without a corresponding improvement of patient outcomes. We believe that analysis of clinical, life sciences and medical process data can play a key role in tackling these fundamental challenges. Two technology advances, in particular, can play a key role: cloud computing and mobility will make it possible to analyze vast amounts of data and quickly deliver useful information to clinicians, consumers and researchers at the point where it can have the most impact. Some of this is already happening today, with medical records being analyzed to reduce fraud, waste and abuse, improve patient outcomes, and to improve compliance with standards of care and policy guidelines. We conclude the talk with a glimpse of a future where medical systems could be continually analyzed for optimizing healthcare costs and outcomes.","PeriodicalId":74567,"journal":{"name":"Proceedings. IEEE International Symposium on Computer-Based Medical Systems","volume":"14 6","pages":"3"},"PeriodicalIF":0.0,"publicationDate":"2013-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/CBMS.2013.6627755","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72474735","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 networks to answer challenging neuroscience questions","authors":"P. Larrañaga, C. Bielza","doi":"10.1109/CBMS.2013.6627754","DOIUrl":"https://doi.org/10.1109/CBMS.2013.6627754","url":null,"abstract":"Summary form only given. In this keynote lecture we will show how Bayesian networks can address important neuroscience problems. These problems include: (a) neuroanatomy issues, like modeling and simulation of dendritic trees and classifying neuron types based on morphological features; (b) neurodegenerative diseases, like predicting health-related quality of life in Parkinson's disease, classification of dementia stages in Parkinson's disease and searching for genetic biomarkers in Alzheimer's disease.","PeriodicalId":74567,"journal":{"name":"Proceedings. IEEE International Symposium on Computer-Based Medical Systems","volume":"42 1","pages":"2"},"PeriodicalIF":0.0,"publicationDate":"2013-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77593944","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":"Why don't engineers and clinicians talk the same language - And what to do about it?","authors":"J. Wyatt","doi":"10.1109/CBMS.2013.6627753","DOIUrl":"https://doi.org/10.1109/CBMS.2013.6627753","url":null,"abstract":"In my experience, presentations at AIME, IEEE or EFMI conferences often describe work by academic engineers using patients as a source of data to explore new modelling methods, and few demonstrate convincing solutions to real world clinical problems. One reason for this is that many doctors make themselves inaccessible, so engineers find it hard to engage them in projects. Since healthcare and medical work are very complex, it takes years of exposure to clinicians and healthcare settings for an engineer to understand real-world patient management problems in sufficient detail to help solve them. This means that sometimes, an engineer might believe they have solved the problem, while to a clinician they have only explored an irrelevant simplification of it. Another explanation is that some engineering academics have had their fingers burned by clinicians, who expect the engineer to carry out an everyday system development task with no research payload. Such engineers will become suspicious of engaging too closely with doctors. Cynics might be less fair, observing that since medical research is well funded, there is a tendency for engineers to apply any novel engineering method to a simplified health data as this is more likely to attract funding than applying their method to, say, linguistics data. However, I believe there is a deeper explanation of why so few bioengineering projects seem to bear clinically digestible fruit: there are fundamental differences in motivation, research focus and research methods between engineering and healthcare research domains, and in the kind of problems they address. For example, the engineering approaches used in the Virtual Physiological Human programme mainly involve data mining and modelling, while clinicians emphasise using psychological, social or other theories to understand and formalise a complex problem first, then use empirical testing to find out whether a theory-based solution works - the evidence based approach. It is clearly unhelpful for engineers to criticise doctors as being poor collaborators in multidisciplinary projects, just as it is for doctors to criticise engineers. So, the aim of this talk is to move beyond name calling to explore common ground constructively and to provoke useful reflection and discussion, both within and across these disciplines. This talk will therefore explore some of the similarities and differences between engineering and healthcare as research disciplines, their respective approaches to problem solving and attempt to build bridges between these two very different worlds. In conclusion, unless we describe the features of this uneasy stand-off between engineers and clinicians, confront it head on and provoke debate, it looks set to continue. This will reduce productivity on both sides and limit the enormous scientific, economic and social benefits that novel, clinically appropriate and collaboratively engineered systems can generate.","PeriodicalId":74567,"journal":{"name":"Proceedings. IEEE International Symposium on Computer-Based Medical Systems","volume":"11 1","pages":"1"},"PeriodicalIF":0.0,"publicationDate":"2013-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84886831","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":"AudioSense: Enabling Real-time Evaluation of Hearing Aid Technology In-Situ.","authors":"Syed Shabih Hasan,&nbsp;Farley Lai,&nbsp;Octav Chipara,&nbsp;Yu-Hsiang Wu","doi":"10.1109/CBMS.2013.6627783","DOIUrl":"https://doi.org/10.1109/CBMS.2013.6627783","url":null,"abstract":"<p><p>AudioSense integrates mobile phones and web technology to measure hearing aid performance in real-time and in-situ. Measuring the performance of hearing aids in the real world poses significant challenges as it depends on the patient's listening context. AudioSense uses Ecological Momentary Assessment methods to evaluate both the perceived hearing aid performance as well as to characterize the listening environment using electronic surveys. AudioSense further characterizes a patient's listening context by recording their GPS location and sound samples. By creating a time-synchronized record of listening performance and listening contexts, AudioSense will allow researchers to understand the relationship between listening context and hearing aid performance. Performance evaluation shows that AudioSense is reliable, energy-efficient, and can estimate Signal-to-Noise Ratio (SNR) levels from captured audio samples.</p>","PeriodicalId":74567,"journal":{"name":"Proceedings. IEEE International Symposium on Computer-Based Medical Systems","volume":"2013 ","pages":"167-172"},"PeriodicalIF":0.0,"publicationDate":"2013-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/CBMS.2013.6627783","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"32497113","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Inexpensive Monocular Pico-Projector-based Augmented Reality Display for Surgical Microscope.","authors":"Chen Shi,&nbsp;Brian C Becker,&nbsp;Cameron N Riviere","doi":"10.1109/CBMS.2012.6266298","DOIUrl":"https://doi.org/10.1109/CBMS.2012.6266298","url":null,"abstract":"<p><p>This paper describes an inexpensive pico-projector-based augmented reality (AR) display for a surgical microscope. The system is designed for use with Micron, an active handheld surgical tool that cancels hand tremor of surgeons to improve microsurgical accuracy. Using the AR display, virtual cues can be injected into the microscope view to track the movement of the tip of Micron, show the desired position, and indicate the position error. Cues can be used to maintain high performance by helping the surgeon to avoid drifting out of the workspace of the instrument. Also, boundary information such as the view range of the cameras that record surgical procedures can be displayed to tell surgeons the operation area. Furthermore, numerical, textual, or graphical information can be displayed, showing such things as tool tip depth in the work space and on/off status of the canceling function of Micron.</p>","PeriodicalId":74567,"journal":{"name":"Proceedings. IEEE International Symposium on Computer-Based Medical Systems","volume":"2012 ","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2012-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/CBMS.2012.6266298","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"32702814","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}