A. Asgharzadeh, R. Jordan, G. Abousleman, L. D. Canady, D. Koechner, R. Griffey
{"title":"Applications of adaptive analysis in magnetic resonance imaging","authors":"A. Asgharzadeh, R. Jordan, G. Abousleman, L. D. Canady, D. Koechner, R. Griffey","doi":"10.1109/CBMSYS.1990.109381","DOIUrl":"https://doi.org/10.1109/CBMSYS.1990.109381","url":null,"abstract":"The application of a variety of parametric modeling techniques to short complex nuclear magnetic resonance (NMR) data sequences is demonstrated. These techniques have the potential of identifying frequency clusters of signals without being compromised by truncation artifacts. These adaptive algorithms are as rapid as the fast Fourier transform (FFT), and are often a practical alternative to the FFT for generating magnetic resonance images from time-domain data sequences with only 16 complex points. There are two distinct methods of processing nonstationary NMR data, i.e. block and recursive processing. Least-mean-square and modified-least-mean-square algorithms are examples of recursive adaptive procedures, while the Yule-Walker and Burg methods are examples of block processing. Application of the adaptive algorithms yields results where the inherent information content of short time-domain data records are accurately represented. The resolution of these representations is comparable to a DFT analysis with twice the number of samples. This increase in resolution and the accuracy of the signal can be obtained without any increase in acquisition or processing time. Hence, the techniques is well suited for clinical applications on NMR instruments.<<ETX>>","PeriodicalId":365366,"journal":{"name":"[1990] Proceedings. Third Annual IEEE Symposium on Computer-Based Medical Systems","volume":"119 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1990-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123472179","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}
Huei-Ning Natasha Ma, M. Evens, D. Trace, F. Naeymi-Rad
{"title":"An intelligent progress note system for MEDAS (a Bayesian medical expert system)","authors":"Huei-Ning Natasha Ma, M. Evens, D. Trace, F. Naeymi-Rad","doi":"10.1109/CBMSYS.1990.109437","DOIUrl":"https://doi.org/10.1109/CBMSYS.1990.109437","url":null,"abstract":"The similarities and differences between four computer-based medical record systems are compared, and their progress note facilities are examined. They are: COSTAR (Computer-Stores Ambulatory Record), TMR (The Medical Record), RMRS (Regenstrief Medical Record System), and STOR (Summary Time-Oriented Record). An intelligent problem-oriented progress note system is proposed for MEDAS (the medical emergency decision assistance system).<<ETX>>","PeriodicalId":365366,"journal":{"name":"[1990] Proceedings. Third Annual IEEE Symposium on Computer-Based Medical Systems","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1990-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116829150","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}
M. Perkowski, Shiliang Wang, William Kelly Spiller, Alvin Legate, E. Pierzchala
{"title":"Ovulo-computer: application of image processing and recognition to mucus ferning patterns","authors":"M. Perkowski, Shiliang Wang, William Kelly Spiller, Alvin Legate, E. Pierzchala","doi":"10.1109/CBMSYS.1990.109378","DOIUrl":"https://doi.org/10.1109/CBMSYS.1990.109378","url":null,"abstract":"An approach to automatic prediction and detection of ovulation is described. It is based on the application of image processing techniques to the cervical mucus fern test, a popular clinical diagnostic method. The sequence of histogram equalization, filtering, edge detection, binarization, labeling, thinning, Hough transform, and automatic pattern recognition in a feature space is applied to microscopic images of the ferning patterns. This method permits decisions to be made based on quantitative data instead of the subjective evaluations that are presently used.<<ETX>>","PeriodicalId":365366,"journal":{"name":"[1990] Proceedings. Third Annual IEEE Symposium on Computer-Based Medical Systems","volume":"11 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1990-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129729385","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":"Akaike's model versus conventional spectral analysis as tools for analyzing multivariate clinical time series","authors":"T. Wada","doi":"10.1109/CBMSYS.1990.109444","DOIUrl":"https://doi.org/10.1109/CBMSYS.1990.109444","url":null,"abstract":"Akaike's method of multivariate autoregressive (AR) modeling is applied to time-series analysis of clinical data. The present approach successfully demonstrated the peculiar power spectrum in various time-series data, which failed to be detected by FFT analysis because of abundant noise. Once AR coefficients are computed from the observed time-series of the relevant variables they can be used to describe the peculiar behavior of the system under study in two different ways: impulse response (IR) curves and Akaike's relative power contribution. The original program of Akaike is modified for exclusive uses in the analysis of clinical data.<<ETX>>","PeriodicalId":365366,"journal":{"name":"[1990] Proceedings. Third Annual IEEE Symposium on Computer-Based Medical Systems","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1990-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128401986","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":"Clustering and classification of multispectral magnetic resonance images","authors":"D. Koechner, J. Rasure, R. Griffey, T. Sauer","doi":"10.1109/CBMSYS.1990.109375","DOIUrl":"https://doi.org/10.1109/CBMSYS.1990.109375","url":null,"abstract":"N-dimensional clustering and classification algorithms that offer a method for efficiently classifying, segmenting, and visualizing the information contained in multispectral magnetic resonance images are discussed. Novel imaging methods, such as chemical shift imaging, contain spectral information on tissue metabolism. A problem associated with this method of imaging is that the information contained in the spectrum is not easily interpreted, nor is it extendable to the high-resolution proton image. Each of the frequency bands in the chemical shift image can be thought of as a unique feature, or band, of a multiband image. This resulting multiband image is used as input to an algorithm which groups the data into a set of clusters. The cluster image is segmented via unsupervised and supervised classification. This classification defines regions of the image defined by the chemical characteristics of the tissue. The advantage of this approach over current image interpretation schemes is that this method allows one to compile several feature images, revealing relationships between contributing features, which can be visualized in a single image.<<ETX>>","PeriodicalId":365366,"journal":{"name":"[1990] Proceedings. Third Annual IEEE Symposium on Computer-Based Medical Systems","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1990-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128634015","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":"On the evaluation of LITREF: a PC-based information retrieval system to support stroke diagnosis","authors":"Guang-Nay Wang, M. Evens, Daniel B Hier","doi":"10.1109/CBMSYS.1990.109446","DOIUrl":"https://doi.org/10.1109/CBMSYS.1990.109446","url":null,"abstract":"LITREF was developed to run on a microcomputer to support MAIESTRO, an expert system for the diagnosis and management of stroke cases. The architecture of LITREF uses an inverted file structure with a bitmap strategy. The evaluation process uses the cosine function to measure the similarity between a query and an abstract. The Salton interpolation process is used in the computation of recall and precision values. The experiment involves applying alternative suffixing algorithms to both index terms and query keywords. When the results are evaluated by comparing precision values at each recall level, it is found that the word-stem index method is superior to the full-word index method.<<ETX>>","PeriodicalId":365366,"journal":{"name":"[1990] Proceedings. Third Annual IEEE Symposium on Computer-Based Medical Systems","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1990-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131051043","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}
D. Benachenhou, M. Cader, H. Szu, L. Medsker, C. Wittwer, D. Garling
{"title":"AIDS viral DNA amplification by polymerase chain reaction employing primers selected by AI expert system and an ART neural network","authors":"D. Benachenhou, M. Cader, H. Szu, L. Medsker, C. Wittwer, D. Garling","doi":"10.1109/CBMSYS.1990.109440","DOIUrl":"https://doi.org/10.1109/CBMSYS.1990.109440","url":null,"abstract":"To diagnose AIDS patients, doctors are starting to use the methodology of amplification induced by thermal annealing and by adding specific primers to imitate the polymerase chain reaction of the denatured DNA mutated by several types of human immunodeficiency viruses. An adaptive resonance theory (ART) neural network working in concert with an artificial intelligence (AI) rule-based system is shown to be efficient for enhancing the choice of the needed good primers. Because of the tradeoff between the simplicity of primers and the specifics of primers, doctors prefer to diagnose different viral types by administering patients with different sets of good primers. Thus, AI provides ART with both the background for self-organization and the foreground for the final goal.<<ETX>>","PeriodicalId":365366,"journal":{"name":"[1990] Proceedings. Third Annual IEEE Symposium on Computer-Based Medical Systems","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1990-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115802167","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":"Microcomputer-based tactile hearing prosthesis","authors":"S. Pourmehdi, J. Mouine, M. Sawan, F. Duval","doi":"10.1109/CBMSYS.1990.109388","DOIUrl":"https://doi.org/10.1109/CBMSYS.1990.109388","url":null,"abstract":"A fully programmable digital speech processing system for deaf patients is described. Speech coding is based on vector quantization. The system simulates in real-time the characteristics of a 10-channel tactile vocoder. The system is based on three chips: a Codec TCM29C13, a DSP digital signal processor TMS320E17, and a full custom integrated BiCmos circuit. The architecture of this portable, low-power unit allows a market improvement in synthetic vowel discrimination.<<ETX>>","PeriodicalId":365366,"journal":{"name":"[1990] Proceedings. Third Annual IEEE Symposium on Computer-Based Medical Systems","volume":"86 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1990-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122941232","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}
M. Nemat, R. Martinez, M. Osada, K. Tawara, K. Komatsu
{"title":"A high speed integrated computer network for picture archiving and communication system (PACS)","authors":"M. Nemat, R. Martinez, M. Osada, K. Tawara, K. Komatsu","doi":"10.1109/CBMSYS.1990.109373","DOIUrl":"https://doi.org/10.1109/CBMSYS.1990.109373","url":null,"abstract":"The functional and operational requirements for an integrated computer network to transmit image, text, voice, and image pointing overlays are presented, and the data traffic handling of each data type is discussed. A 200-Mbs fiber optic computer network was designed based on the presented PACS network requirements and the data traffic. The characteristics, protocols, and implementation feasibility of this network are summarized. These integrated PACS network can be used for a global PACS (GPACS). The GPACS will allow the exchange of images and patient information and will provide real-time consulting facilities among radiologists and physicians throughout the world.<<ETX>>","PeriodicalId":365366,"journal":{"name":"[1990] Proceedings. Third Annual IEEE Symposium on Computer-Based Medical Systems","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1990-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125868403","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}
C. Collet, L. Martini, M. Lovin, E. Masson, N. Fumai, M. Petroni, A. Malowany, F. Carnevale, R. Gottesman, A. Rousseau
{"title":"Real-time trend analysis for an intensive care unit patient data management system","authors":"C. Collet, L. Martini, M. Lovin, E. Masson, N. Fumai, M. Petroni, A. Malowany, F. Carnevale, R. Gottesman, A. Rousseau","doi":"10.1109/CBMSYS.1990.109417","DOIUrl":"https://doi.org/10.1109/CBMSYS.1990.109417","url":null,"abstract":"A real-time trend analysis module design which is currently being developed for the patient data management system (PDMS) at the pediatric intensive care unit of the Montreal Children's Hospital is discussed. The PDMS is based on a personal computer acquiring, in real time, patient data from a local area network of 14 bedside monitors, and displaying their trends graphically, among other tasks. The system is based on an IBM model 50 running under the OS/2 multitasking operating system and uses the 8514/A high resolution color video display. This work presents the design and implementation of the module based on two different supervised neural networks using the general delta rule learning mechanisms. The integration of such a module with a diagnosis expert system is also discussed.<<ETX>>","PeriodicalId":365366,"journal":{"name":"[1990] Proceedings. Third Annual IEEE Symposium on Computer-Based Medical Systems","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1990-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128461025","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}