Pub Date : 2000-11-08DOI: 10.1109/BIBE.2000.889627
Yingjie Tang, Lei He, Xun Wang, W. Wee
A two-step model based approach to a contour extraction problem is developed to provide a solution to more challenging contour extraction problems of biomedical images. A biomedical contour image is initially processed by a deformable contour method to obtain a first order approximation of the contour. The two-step model includes a linked contour model and a posteriori probability model. Initially, the output contour from the deformable contour method is matched against the linked contour model for both model detection and corresponding landmark contour points identification. Segments obtained from these landmarks are matched for errors. Larger error are then passed on to a regionalized a posteriori probability model for further fine tuning to obtain a final result. Experiments on both MR brain images are most encouraging.
{"title":"A model based contour searching method","authors":"Yingjie Tang, Lei He, Xun Wang, W. Wee","doi":"10.1109/BIBE.2000.889627","DOIUrl":"https://doi.org/10.1109/BIBE.2000.889627","url":null,"abstract":"A two-step model based approach to a contour extraction problem is developed to provide a solution to more challenging contour extraction problems of biomedical images. A biomedical contour image is initially processed by a deformable contour method to obtain a first order approximation of the contour. The two-step model includes a linked contour model and a posteriori probability model. Initially, the output contour from the deformable contour method is matched against the linked contour model for both model detection and corresponding landmark contour points identification. Segments obtained from these landmarks are matched for errors. Larger error are then passed on to a regionalized a posteriori probability model for further fine tuning to obtain a final result. Experiments on both MR brain images are most encouraging.","PeriodicalId":196846,"journal":{"name":"Proceedings IEEE International Symposium on Bio-Informatics and Biomedical Engineering","volume":"372 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122926341","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}
Pub Date : 2000-11-08DOI: 10.1109/BIBE.2000.889586
C. Bult, J. Richardson, J. Blake, J. Kadin, M. Ringwald, J. Eppig
Data integration is key to knowledge discovery in the age of genomics and represents a major, long-standing challenge for the genome informatics community. Integration of data across heterogeneous genome databases requires the identification of common data entities and mechanisms to ensure referential integrity and persistence of these common entities even as our understanding of their biological properties changes. The Mouse Genome Informatics (MGI) database group employs multiple strategies for achieving data integration and maintaining inter-connectedness with other databases, including: (1) the use of permanent, unique accession IDs for identifying core data entities, (2) the application of nomenclature standards for naming genes and strains of mice, and (3) the development and implementation of controlled vocabularies and ontologies to ensure semantic consistency of biological concepts within and across model organism databases.
{"title":"Mouse genome informatics in a new age of biological inquiry","authors":"C. Bult, J. Richardson, J. Blake, J. Kadin, M. Ringwald, J. Eppig","doi":"10.1109/BIBE.2000.889586","DOIUrl":"https://doi.org/10.1109/BIBE.2000.889586","url":null,"abstract":"Data integration is key to knowledge discovery in the age of genomics and represents a major, long-standing challenge for the genome informatics community. Integration of data across heterogeneous genome databases requires the identification of common data entities and mechanisms to ensure referential integrity and persistence of these common entities even as our understanding of their biological properties changes. The Mouse Genome Informatics (MGI) database group employs multiple strategies for achieving data integration and maintaining inter-connectedness with other databases, including: (1) the use of permanent, unique accession IDs for identifying core data entities, (2) the application of nomenclature standards for naming genes and strains of mice, and (3) the development and implementation of controlled vocabularies and ontologies to ensure semantic consistency of biological concepts within and across model organism databases.","PeriodicalId":196846,"journal":{"name":"Proceedings IEEE International Symposium on Bio-Informatics and Biomedical Engineering","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121808302","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}
Pub Date : 2000-11-08DOI: 10.1109/BIBE.2000.889597
K. Cheung, Dong-Guk Shin
The proliferation, diversity and complexity of genome databases pose a significant challenge to the multidatabase research community. We propose a meta-data framework based on a graph modeling technique and show how this framework can be applied to making two genome databases interoperable. Our technique maps individual database schemas expressed in heterogeneous data models into a common graph representation. This graph-based framework is designed to express both regular data and meta-data. Modeling both types of data is necessary for establishing database correspondences. We show how inter-database relationships can be expressed in terms of correspondences amongst basic graph units, including nodes, edges and the "value path". We apply these basic graph units to perform query interoperation between two databases, namely DB/12 (Database of Human Chromosome 12) and GDB (Genome Database).
{"title":"A graph-based meta-data framework for interoperation between genome databases","authors":"K. Cheung, Dong-Guk Shin","doi":"10.1109/BIBE.2000.889597","DOIUrl":"https://doi.org/10.1109/BIBE.2000.889597","url":null,"abstract":"The proliferation, diversity and complexity of genome databases pose a significant challenge to the multidatabase research community. We propose a meta-data framework based on a graph modeling technique and show how this framework can be applied to making two genome databases interoperable. Our technique maps individual database schemas expressed in heterogeneous data models into a common graph representation. This graph-based framework is designed to express both regular data and meta-data. Modeling both types of data is necessary for establishing database correspondences. We show how inter-database relationships can be expressed in terms of correspondences amongst basic graph units, including nodes, edges and the \"value path\". We apply these basic graph units to perform query interoperation between two databases, namely DB/12 (Database of Human Chromosome 12) and GDB (Genome Database).","PeriodicalId":196846,"journal":{"name":"Proceedings IEEE International Symposium on Bio-Informatics and Biomedical Engineering","volume":"81 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124780327","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}
Pub Date : 2000-11-08DOI: 10.1109/BIBE.2000.889624
L. Freire, F. Godinho
Mutual Information (MI), or relative entropy has been used as a similarity criterion in medical image registration. MI is a measure of the dispersive behavior of the joint histogram of geometrically related voxels' intensities in both images. This dispersion is assumed to be smaller when the images are aligned. Besides, no assumptions are made, before bringing images together or during MI calculation, regarding the nature of the relation between corresponding voxels. In this work the authors assess how the elaboration of joint histogram influences overall accuracy of maximization of MI registration method in unimodality and multimodality registration. For this purpose, across validation study is performed considering two other widespread registration algorithms: the SPM's registration package and multimodality AIR method. The correct elaboration of the joint histogram depends not only in the interpolation function used to resample the test image, but also in the re-scaling procedure used to fit images' values in the joint histogram and its subsequent update. The authors also evaluate if histogram's dimensions are important for overall accuracy.
{"title":"Registration by maximization of mutual information-a cross validation study","authors":"L. Freire, F. Godinho","doi":"10.1109/BIBE.2000.889624","DOIUrl":"https://doi.org/10.1109/BIBE.2000.889624","url":null,"abstract":"Mutual Information (MI), or relative entropy has been used as a similarity criterion in medical image registration. MI is a measure of the dispersive behavior of the joint histogram of geometrically related voxels' intensities in both images. This dispersion is assumed to be smaller when the images are aligned. Besides, no assumptions are made, before bringing images together or during MI calculation, regarding the nature of the relation between corresponding voxels. In this work the authors assess how the elaboration of joint histogram influences overall accuracy of maximization of MI registration method in unimodality and multimodality registration. For this purpose, across validation study is performed considering two other widespread registration algorithms: the SPM's registration package and multimodality AIR method. The correct elaboration of the joint histogram depends not only in the interpolation function used to resample the test image, but also in the re-scaling procedure used to fit images' values in the joint histogram and its subsequent update. The authors also evaluate if histogram's dimensions are important for overall accuracy.","PeriodicalId":196846,"journal":{"name":"Proceedings IEEE International Symposium on Bio-Informatics and Biomedical Engineering","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125002191","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}
Pub Date : 2000-11-08DOI: 10.1109/BIBE.2000.889594
P. Sheu, Brian J Cummings, C. Cotman, C. Chubb, Linhua Hu, Taehyung Wang, Julene Johnson, Scott Mobley, Tom Sitch, Yoshi Inagaki
As neuroscience research advances, there is an increasing need to integrate data from a single patient who has undergone multiple levels of analysis. In a biomedical application (such as an Alzheimer's clinic), a patient might have medical data, MRI data, cognitive data and autopsy data all collected at various times. This paper introduces "BioCompose", an object-relational database system that integrates clinical, neuropathological and image data sets into a uniform framework with a simple user interface. It addresses the advantages of taking an object-relational approach for a large and complex application.
{"title":"An object relational approach to biomedical database","authors":"P. Sheu, Brian J Cummings, C. Cotman, C. Chubb, Linhua Hu, Taehyung Wang, Julene Johnson, Scott Mobley, Tom Sitch, Yoshi Inagaki","doi":"10.1109/BIBE.2000.889594","DOIUrl":"https://doi.org/10.1109/BIBE.2000.889594","url":null,"abstract":"As neuroscience research advances, there is an increasing need to integrate data from a single patient who has undergone multiple levels of analysis. In a biomedical application (such as an Alzheimer's clinic), a patient might have medical data, MRI data, cognitive data and autopsy data all collected at various times. This paper introduces \"BioCompose\", an object-relational database system that integrates clinical, neuropathological and image data sets into a uniform framework with a simple user interface. It addresses the advantages of taking an object-relational approach for a large and complex application.","PeriodicalId":196846,"journal":{"name":"Proceedings IEEE International Symposium on Bio-Informatics and Biomedical Engineering","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131668442","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}
Pub Date : 2000-11-08DOI: 10.1109/BIBE.2000.889591
Z. Lacroix
Building a digital library for scientific data requires accessing and manipulating data extracted from flat files or from documents retrieved from the World Wide Web. We present an approach to querying flat files as well as Web data sources through an object database view based on a database system and a wrapper. Generally, a wrapper has two tasks: it first sends a query to the source to retrieve data and, secondly builds the expected output with respect to the virtual structure. Scientific data servers, and in particular the ones publicly available on the Web, usually provide information retrieval techniques to access data. Our wrappers are composed of a retrieval component, based on an intermediate object view mechanism called 'search views' mapping the source capabilities to attributes, and a XML engine to perform these two tasks. If the retrieval component is specific to each data source, this approach shows that the extraction component (the XML engine) can be common. We describe our system and focus on the retrieval component of the Object-Web Wrapper (OWW) for Web sources. The originality of our approach consists of (1) a common wrapper architecture for flat files and Web data sources sharing a XML engine for data extraction, (2) a generic view mechanism to access data sources with limited capabilities, and (3) the representation of hyperlinks as abstract attributes in the object view as well as their use in the search view. Our approach has been developed and demonstrated as part of a multidatabase system supporting queries via uniform Object Protocol Model (OPM) interfaces.
{"title":"Scientific data integration: wrapping textual documents with a database view mechanism and an XML engine","authors":"Z. Lacroix","doi":"10.1109/BIBE.2000.889591","DOIUrl":"https://doi.org/10.1109/BIBE.2000.889591","url":null,"abstract":"Building a digital library for scientific data requires accessing and manipulating data extracted from flat files or from documents retrieved from the World Wide Web. We present an approach to querying flat files as well as Web data sources through an object database view based on a database system and a wrapper. Generally, a wrapper has two tasks: it first sends a query to the source to retrieve data and, secondly builds the expected output with respect to the virtual structure. Scientific data servers, and in particular the ones publicly available on the Web, usually provide information retrieval techniques to access data. Our wrappers are composed of a retrieval component, based on an intermediate object view mechanism called 'search views' mapping the source capabilities to attributes, and a XML engine to perform these two tasks. If the retrieval component is specific to each data source, this approach shows that the extraction component (the XML engine) can be common. We describe our system and focus on the retrieval component of the Object-Web Wrapper (OWW) for Web sources. The originality of our approach consists of (1) a common wrapper architecture for flat files and Web data sources sharing a XML engine for data extraction, (2) a generic view mechanism to access data sources with limited capabilities, and (3) the representation of hyperlinks as abstract attributes in the object view as well as their use in the search view. Our approach has been developed and demonstrated as part of a multidatabase system supporting queries via uniform Object Protocol Model (OPM) interfaces.","PeriodicalId":196846,"journal":{"name":"Proceedings IEEE International Symposium on Bio-Informatics and Biomedical Engineering","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134438244","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}
Pub Date : 2000-11-08DOI: 10.1109/BIBE.2000.889619
B. Parvin, G. Cong, G. Fontenay, John R. Taylor, R. Henshal, M. Barcellos-Hoff
Mapping inter-cell signaling pathways requires an integrated view of experimental and informatic protocols. BioSig provides the foundation of cataloging inter-cell responses as a function of particular conditioning, treatment, staining, etc. for either in vivo or in vitro experiments. This paper outlines the system architecture, a functional data model for representing experimental protocols, algorithms for image analysis, and the required statistical analysis. The architecture provides remote shared operation of an inverted optical microscope, and couples instrument operation with images acquisition and annotation. The information is stored in an object-oriented database. The algorithms extract structural information such as morphology and organization, and map it to functional information such as inter-cellular responses. An example of usage of this system is included.
{"title":"BioSig: a bioinformatic system for studying the mechanism of inter-cell signaling","authors":"B. Parvin, G. Cong, G. Fontenay, John R. Taylor, R. Henshal, M. Barcellos-Hoff","doi":"10.1109/BIBE.2000.889619","DOIUrl":"https://doi.org/10.1109/BIBE.2000.889619","url":null,"abstract":"Mapping inter-cell signaling pathways requires an integrated view of experimental and informatic protocols. BioSig provides the foundation of cataloging inter-cell responses as a function of particular conditioning, treatment, staining, etc. for either in vivo or in vitro experiments. This paper outlines the system architecture, a functional data model for representing experimental protocols, algorithms for image analysis, and the required statistical analysis. The architecture provides remote shared operation of an inverted optical microscope, and couples instrument operation with images acquisition and annotation. The information is stored in an object-oriented database. The algorithms extract structural information such as morphology and organization, and map it to functional information such as inter-cellular responses. An example of usage of this system is included.","PeriodicalId":196846,"journal":{"name":"Proceedings IEEE International Symposium on Bio-Informatics and Biomedical Engineering","volume":"167 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132527574","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}
Pub Date : 2000-11-08DOI: 10.1109/BIBE.2000.889621
Richard W. I. Yarger, Francis K. H. Quek
Curvature-based surface features are well suited for use in multimodal medical image registration. The accuracy of such feature-based registration techniques is dependent upon the reliability of the feature computation. The computation of curvature features requires second derivative information that is best obtained from a parametric surface representation. The authors present a method of explicitly parametrizing surfaces from volumetric data. Surfaces are extracted, without a global thresholding, using active contour models. A monge basis for each surface patch is estimated and used to transform the patch into local, or parametric, coordinates. Surface patches are fit to a bicubic polynomial in local coordinates using least squares solved by singular value decomposition. The authors tested their method by reconstructing surfaces from the surface model and analytically computing gaussian and mean curvatures. The model was tested on analytical and medical data.
{"title":"Surface parameterization in volumetric images for feature classification","authors":"Richard W. I. Yarger, Francis K. H. Quek","doi":"10.1109/BIBE.2000.889621","DOIUrl":"https://doi.org/10.1109/BIBE.2000.889621","url":null,"abstract":"Curvature-based surface features are well suited for use in multimodal medical image registration. The accuracy of such feature-based registration techniques is dependent upon the reliability of the feature computation. The computation of curvature features requires second derivative information that is best obtained from a parametric surface representation. The authors present a method of explicitly parametrizing surfaces from volumetric data. Surfaces are extracted, without a global thresholding, using active contour models. A monge basis for each surface patch is estimated and used to transform the patch into local, or parametric, coordinates. Surface patches are fit to a bicubic polynomial in local coordinates using least squares solved by singular value decomposition. The authors tested their method by reconstructing surfaces from the surface model and analytically computing gaussian and mean curvatures. The model was tested on analytical and medical data.","PeriodicalId":196846,"journal":{"name":"Proceedings IEEE International Symposium on Bio-Informatics and Biomedical Engineering","volume":"28 19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128548904","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}
Pub Date : 2000-11-08DOI: 10.1109/BIBE.2000.889602
J. Falqueto, J. Barreto, Paulo Sergio da Silva Borges
Initially, different areas of research in computer science based on models inspired by nature are approached. The area entitled "evolutionary computation" is discussed in a general view. After this, emphasis is placed on the human tendency to copy and to find answers to new problems by adopting similar solutions from other equivalent issues that have already been resolved by nature. Finally, we demonstrate that, in the case of evolutionary computation, even if success is achieved in many cases, most of what nature has attained was either severely simplified or truncated in the simulation process. Also, in several cases, a more detailed and more faithful copy could have yielded better results for already-existing systems or for new ones.
{"title":"Amplification of perspectives in the use of evolutionary computation","authors":"J. Falqueto, J. Barreto, Paulo Sergio da Silva Borges","doi":"10.1109/BIBE.2000.889602","DOIUrl":"https://doi.org/10.1109/BIBE.2000.889602","url":null,"abstract":"Initially, different areas of research in computer science based on models inspired by nature are approached. The area entitled \"evolutionary computation\" is discussed in a general view. After this, emphasis is placed on the human tendency to copy and to find answers to new problems by adopting similar solutions from other equivalent issues that have already been resolved by nature. Finally, we demonstrate that, in the case of evolutionary computation, even if success is achieved in many cases, most of what nature has attained was either severely simplified or truncated in the simulation process. Also, in several cases, a more detailed and more faithful copy could have yielded better results for already-existing systems or for new ones.","PeriodicalId":196846,"journal":{"name":"Proceedings IEEE International Symposium on Bio-Informatics and Biomedical Engineering","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117000132","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}
Pub Date : 2000-11-08DOI: 10.1109/BIBE.2000.889615
Jeffrey L. Madden, Zina Ben-Miled, R. Chin, J. Schild
Membrane bound ion channels give rise to many of the electrical signal characteristics exhibited by neurons. Ion channel models of neural function such as that proposed by Hodgkin-Huxley can be represented as a set of differential equations. Solving these differential equations for a given neuron involves finding optimal values for the parameters that define the Hodgkin-Huxley equations. Most often, these parameters are evaluated using an optimization algorithm that takes as input ion channel current data recorded from a neuron using the voltage clamp technique. Real-valued optimization algorithms often fail to find a global optimum for the parameters of the Hodgkin-Huxley differential equations. Here, the authors show that interval analysis based optimization algorithm, a branch and bound algorithm, provides an accurate solution for the Hodgkin-Huxley model.
{"title":"On parameter estimation for neuron models","authors":"Jeffrey L. Madden, Zina Ben-Miled, R. Chin, J. Schild","doi":"10.1109/BIBE.2000.889615","DOIUrl":"https://doi.org/10.1109/BIBE.2000.889615","url":null,"abstract":"Membrane bound ion channels give rise to many of the electrical signal characteristics exhibited by neurons. Ion channel models of neural function such as that proposed by Hodgkin-Huxley can be represented as a set of differential equations. Solving these differential equations for a given neuron involves finding optimal values for the parameters that define the Hodgkin-Huxley equations. Most often, these parameters are evaluated using an optimization algorithm that takes as input ion channel current data recorded from a neuron using the voltage clamp technique. Real-valued optimization algorithms often fail to find a global optimum for the parameters of the Hodgkin-Huxley differential equations. Here, the authors show that interval analysis based optimization algorithm, a branch and bound algorithm, provides an accurate solution for the Hodgkin-Huxley model.","PeriodicalId":196846,"journal":{"name":"Proceedings IEEE International Symposium on Bio-Informatics and Biomedical Engineering","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121146146","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}
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