Pub Date : 1993-10-31DOI: 10.1109/NSSMIC.1993.702011
S. Wegner, H. Oswald, E. Fleck, R. Felix
For 3D scenes a 3D segmentation technique on a massively parallel computer is described and tested on CT image sequences. The approach is based on a volume growing technique driven by statistical features and a model depending on characteristic object parameters. The volumes of interest are specified interactively and used as seed volumes for the growing algorithm. An estimation technique is employed to calculate several statistical properties of these seed volumes. The required homogeneity criterion for each volume is then obtained in regard to the estimated statistics and the model of the object. These segmentation results are handled by a 3D morphological operator. Due to practical considerations the approach has been implemented on a massively parallel SIMD (single instruction multiple data) machine, the MasPar Mp1102.
{"title":"3D segmentation of Ct images on a massively parallel computer","authors":"S. Wegner, H. Oswald, E. Fleck, R. Felix","doi":"10.1109/NSSMIC.1993.702011","DOIUrl":"https://doi.org/10.1109/NSSMIC.1993.702011","url":null,"abstract":"For 3D scenes a 3D segmentation technique on a massively parallel computer is described and tested on CT image sequences. The approach is based on a volume growing technique driven by statistical features and a model depending on characteristic object parameters. The volumes of interest are specified interactively and used as seed volumes for the growing algorithm. An estimation technique is employed to calculate several statistical properties of these seed volumes. The required homogeneity criterion for each volume is then obtained in regard to the estimated statistics and the model of the object. These segmentation results are handled by a 3D morphological operator. Due to practical considerations the approach has been implemented on a massively parallel SIMD (single instruction multiple data) machine, the MasPar Mp1102.","PeriodicalId":287813,"journal":{"name":"1993 IEEE Conference Record Nuclear Science Symposium and Medical Imaging Conference","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1993-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122032003","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 : 1993-10-31DOI: 10.1109/NSSMIC.1993.701771
D. Binkley, M. Paulus, M. Casey, R. Nutt, W. Loeffler, J. Clif, J. M. Rochelle
A custom CMOS integrated circuit has been designed, prototyped, and evaluated for PET tomograph front-end applications. The integrated circuit reduces the size. cost, and power consumption of existing PET frontend circuits by Over a factor of two. The integrated circuit, fabricated in a standard digital, 2 p, double-metal, double-poly, n-well CMOS process, has a die size of 6.6mmx6.4mm and power consumption of under 600 mW. The PET front-end CMOS integrated circuit processes energy, position, and timing information from a BGO block detector containing four photomultiplier tubes. Photomultiplier preamplifiers and variable gain amplifiers are co~ected to summing circuits and gated integrators to provide energy and position (x and y) signals. A constantfraction discriminator, requiring no external delay line, provides a timing output derived from the sum of the four photomultiplier signals. Eight 7- and 8-bit digital-to-analog converters. connected to a readwrite serial data interface, provide gain-control and threshold levels. The measured position, energy, and timing performance (3.05ns FWHM) of the integrated circuit is comparable to existing discrete PET frontend circuits.
{"title":"A Custom CMOS Integrated Circuit For PET Tomograph Front-end Applications","authors":"D. Binkley, M. Paulus, M. Casey, R. Nutt, W. Loeffler, J. Clif, J. M. Rochelle","doi":"10.1109/NSSMIC.1993.701771","DOIUrl":"https://doi.org/10.1109/NSSMIC.1993.701771","url":null,"abstract":"A custom CMOS integrated circuit has been designed, prototyped, and evaluated for PET tomograph front-end applications. The integrated circuit reduces the size. cost, and power consumption of existing PET frontend circuits by Over a factor of two. The integrated circuit, fabricated in a standard digital, 2 p, double-metal, double-poly, n-well CMOS process, has a die size of 6.6mmx6.4mm and power consumption of under 600 mW. The PET front-end CMOS integrated circuit processes energy, position, and timing information from a BGO block detector containing four photomultiplier tubes. Photomultiplier preamplifiers and variable gain amplifiers are co~ected to summing circuits and gated integrators to provide energy and position (x and y) signals. A constantfraction discriminator, requiring no external delay line, provides a timing output derived from the sum of the four photomultiplier signals. Eight 7- and 8-bit digital-to-analog converters. connected to a readwrite serial data interface, provide gain-control and threshold levels. The measured position, energy, and timing performance (3.05ns FWHM) of the integrated circuit is comparable to existing discrete PET frontend circuits.","PeriodicalId":287813,"journal":{"name":"1993 IEEE Conference Record Nuclear Science Symposium and Medical Imaging Conference","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1993-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123664240","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 : 1993-10-31DOI: 10.1109/NSSMIC.1993.701848
M. S. Atkins, B. Johnston, T. Zuk, T. Arden
Developers of new algorithms typically require an interactive environment in which the image data can be passed through various operators, some of which may involve feedback, synchronization, merging and conditional control strategies. This paper describes how the dataflow methodology of a pictorial object-oriented software development tool called WIT has greatly simplified the prototyping and testing of our new image registration and segmentation methods. WIT allows the user to draw a dataflow graph by linking operators in a CAD-like manner. We describe the main features of WIT, and show dataflow graphs for two medical image analysis algorithms; the 3D registration of PET scans into a common coordinate space, and tissue segmentation in MRI images where we are looking at quantitation of tumour volumes.
{"title":"An Object-oriented Dataflow Software Development Tool For Medical Image Analysis","authors":"M. S. Atkins, B. Johnston, T. Zuk, T. Arden","doi":"10.1109/NSSMIC.1993.701848","DOIUrl":"https://doi.org/10.1109/NSSMIC.1993.701848","url":null,"abstract":"Developers of new algorithms typically require an interactive environment in which the image data can be passed through various operators, some of which may involve feedback, synchronization, merging and conditional control strategies. This paper describes how the dataflow methodology of a pictorial object-oriented software development tool called WIT has greatly simplified the prototyping and testing of our new image registration and segmentation methods. WIT allows the user to draw a dataflow graph by linking operators in a CAD-like manner. We describe the main features of WIT, and show dataflow graphs for two medical image analysis algorithms; the 3D registration of PET scans into a common coordinate space, and tissue segmentation in MRI images where we are looking at quantitation of tumour volumes.","PeriodicalId":287813,"journal":{"name":"1993 IEEE Conference Record Nuclear Science Symposium and Medical Imaging Conference","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1993-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124454200","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 : 1993-10-31DOI: 10.1109/NSSMIC.1993.373523
T. Beyer, D. Townsend, M. Defrise
Two methods for attenuation correction in 3D positron emission tomography have been compared. The first method, which is referred to here as the direct method, estimates the attenuation correction factors from the ratio of the blank and transmission scan. The second method, referred to here as the reconstruction-reprojection method is based on the reconstruction and forward projection of a transmission image. Using computer simulation, it is shown that the reconstruction-reprojection method significantly increases the signal-to-noise ratio in the corrected 3D emission scan, but leads to only a limited improvement in the image. A similar image signal-to-noise ratio can be obtained using the direct method, if the transmission scan is first convolved with a 3-point smoothing window. The consequence of the loss of resolution caused by this smoothing is analysed using a simulated chest phantom.<>
{"title":"Attenuation correction in 3D PET-comparison of the direct and the reconstruction-reprojection method","authors":"T. Beyer, D. Townsend, M. Defrise","doi":"10.1109/NSSMIC.1993.373523","DOIUrl":"https://doi.org/10.1109/NSSMIC.1993.373523","url":null,"abstract":"Two methods for attenuation correction in 3D positron emission tomography have been compared. The first method, which is referred to here as the direct method, estimates the attenuation correction factors from the ratio of the blank and transmission scan. The second method, referred to here as the reconstruction-reprojection method is based on the reconstruction and forward projection of a transmission image. Using computer simulation, it is shown that the reconstruction-reprojection method significantly increases the signal-to-noise ratio in the corrected 3D emission scan, but leads to only a limited improvement in the image. A similar image signal-to-noise ratio can be obtained using the direct method, if the transmission scan is first convolved with a 3-point smoothing window. The consequence of the loss of resolution caused by this smoothing is analysed using a simulated chest phantom.<<ETX>>","PeriodicalId":287813,"journal":{"name":"1993 IEEE Conference Record Nuclear Science Symposium and Medical Imaging Conference","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1993-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114579541","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 : 1993-10-31DOI: 10.1109/NSSMIC.1993.373606
L. Thurfjell, C. Bohm
The interpretation of functional neuroimaging data can in many cases be facilitated by comparisons with simulated data corresponding to the measuring situation. A computerized brain atlas is used to provide information regarding the spatial extent of the object being imaged. This knowledge combined with information about the resolution of the imaging device expressed as point spread functions is used to calculate a simulated image of the object. This image can be regarded as a generalized region of interest (ROI) containing information of the object as viewed by the specific instrument. Generalized ROIs are used to automatically determine boundaries of ordinary ROIs and to provide recovery coefficients to compensate for partial volume effects. Simulations can also be used to generate three-dimensional data sets where different uptake levels have been assigned to different anatomical structures.<>
{"title":"Atlas generated generalized ROIs for use in functional neuroimaging","authors":"L. Thurfjell, C. Bohm","doi":"10.1109/NSSMIC.1993.373606","DOIUrl":"https://doi.org/10.1109/NSSMIC.1993.373606","url":null,"abstract":"The interpretation of functional neuroimaging data can in many cases be facilitated by comparisons with simulated data corresponding to the measuring situation. A computerized brain atlas is used to provide information regarding the spatial extent of the object being imaged. This knowledge combined with information about the resolution of the imaging device expressed as point spread functions is used to calculate a simulated image of the object. This image can be regarded as a generalized region of interest (ROI) containing information of the object as viewed by the specific instrument. Generalized ROIs are used to automatically determine boundaries of ordinary ROIs and to provide recovery coefficients to compensate for partial volume effects. Simulations can also be used to generate three-dimensional data sets where different uptake levels have been assigned to different anatomical structures.<<ETX>>","PeriodicalId":287813,"journal":{"name":"1993 IEEE Conference Record Nuclear Science Symposium and Medical Imaging Conference","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1993-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117211019","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 : 1993-10-31DOI: 10.1109/NSSMIC.1993.373629
G. L. Zeng, Y. Hsieh, G. Gullberg
The authors propose and implement a rotating-and-squashing projector-backprojector pair for fan-beam and cone-beam iterative algorithms. The motivation of their investigation is to significantly reduce both computation time and reconstruction artifacts when implementing attenuation, geometric and scatter correction models. At each projection angle, the authors' projector/backprojector first rotates the image volume so that the front face of the volume is parallel to the detector, then squashes the image volume so that the fan-beam and cone-beam rays are converted into parallel rays. In the authors' implementation, these two steps are combined and they only interpolate the voxel values once. The projection operation is achieved by a simple summation, and the backprojection operation is achieved by copying the projection array to the image volume. Another advantage of this projector/backprojector is that the system point response function can be deconvolved via the fast Fourier transform using the shift-invariant property of the point response function when the voxel-to-detector distance is constant. At each projection angle, the authors rotate and squash the image volume using interpolations. This causes smoothing of the image. However, this smoothing can be modeled as a point spread function and be deconvolved. The fan-beam and cone-beam rotating-and-squashing projector/backprojector have been implemented on a SPECT system for the EM-ML algorithm.<>
{"title":"A rotating and squashing projector-backprojector pair for fan-beam and cone-beam iterative algorithms","authors":"G. L. Zeng, Y. Hsieh, G. Gullberg","doi":"10.1109/NSSMIC.1993.373629","DOIUrl":"https://doi.org/10.1109/NSSMIC.1993.373629","url":null,"abstract":"The authors propose and implement a rotating-and-squashing projector-backprojector pair for fan-beam and cone-beam iterative algorithms. The motivation of their investigation is to significantly reduce both computation time and reconstruction artifacts when implementing attenuation, geometric and scatter correction models. At each projection angle, the authors' projector/backprojector first rotates the image volume so that the front face of the volume is parallel to the detector, then squashes the image volume so that the fan-beam and cone-beam rays are converted into parallel rays. In the authors' implementation, these two steps are combined and they only interpolate the voxel values once. The projection operation is achieved by a simple summation, and the backprojection operation is achieved by copying the projection array to the image volume. Another advantage of this projector/backprojector is that the system point response function can be deconvolved via the fast Fourier transform using the shift-invariant property of the point response function when the voxel-to-detector distance is constant. At each projection angle, the authors rotate and squash the image volume using interpolations. This causes smoothing of the image. However, this smoothing can be modeled as a point spread function and be deconvolved. The fan-beam and cone-beam rotating-and-squashing projector/backprojector have been implemented on a SPECT system for the EM-ML algorithm.<<ETX>>","PeriodicalId":287813,"journal":{"name":"1993 IEEE Conference Record Nuclear Science Symposium and Medical Imaging Conference","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1993-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130653500","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 : 1993-10-31DOI: 10.1109/NSSMIC.1993.373518
M. Usman, A. Hero, J. Fessler, W. Rogers
The authors quantify fundamental bias-variance tradeoffs for the image reconstruction problem in radio-pharmaceutical tomography using Cramer-Rao (CR) bound analysis. The image reconstruction problem is very often biased and the classical or the unbiased CR bound on the mean square error performance of the estimator can not be used. The authors use a recently developed "uniform" CR bound which applies to biased estimators whose bias gradient satisfies a user specified length constraint. The authors demonstrate the use of the "uniform" CR bound for a simple SPECT system using several different examples.<>
{"title":"Bias-variance tradeoffs analysis using uniform CR bound for a SPECT system","authors":"M. Usman, A. Hero, J. Fessler, W. Rogers","doi":"10.1109/NSSMIC.1993.373518","DOIUrl":"https://doi.org/10.1109/NSSMIC.1993.373518","url":null,"abstract":"The authors quantify fundamental bias-variance tradeoffs for the image reconstruction problem in radio-pharmaceutical tomography using Cramer-Rao (CR) bound analysis. The image reconstruction problem is very often biased and the classical or the unbiased CR bound on the mean square error performance of the estimator can not be used. The authors use a recently developed \"uniform\" CR bound which applies to biased estimators whose bias gradient satisfies a user specified length constraint. The authors demonstrate the use of the \"uniform\" CR bound for a simple SPECT system using several different examples.<<ETX>>","PeriodicalId":287813,"journal":{"name":"1993 IEEE Conference Record Nuclear Science Symposium and Medical Imaging Conference","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1993-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130747736","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 : 1993-10-31DOI: 10.1109/NSSMIC.1993.373634
L. Eriksson
A simple model to describe data losses in PET cameras is presented. The model is not intended to be used primarily for dead time corrections in existing scanners, even if this may be possible. Instead the model is intended to be used for data simulations in order to determine the figures of merits of future camera systems based on data handling state-of-art solutions. The model assumes the data loss to be factorized into two components, one describing the detector or block-detector performance and the other the remaining data handling such as coincidence determinations, data transfer and data storage. Two modern positron camera systems have been investigated in terms of this model. These are the new Siemens-CTI systems, Ecat Exact and Ecat Exact HR, both with an axial field-of-view (FOV) covering around 15 cm. They both have retractable septa and can acquire data from the whole volume within the FOV and can reconstruct volume image data. An example is given how to use the model for live time calculations in a futuristic large axial FOV cylindrical system.<>
{"title":"A simple data loss model for positron camera systems","authors":"L. Eriksson","doi":"10.1109/NSSMIC.1993.373634","DOIUrl":"https://doi.org/10.1109/NSSMIC.1993.373634","url":null,"abstract":"A simple model to describe data losses in PET cameras is presented. The model is not intended to be used primarily for dead time corrections in existing scanners, even if this may be possible. Instead the model is intended to be used for data simulations in order to determine the figures of merits of future camera systems based on data handling state-of-art solutions. The model assumes the data loss to be factorized into two components, one describing the detector or block-detector performance and the other the remaining data handling such as coincidence determinations, data transfer and data storage. Two modern positron camera systems have been investigated in terms of this model. These are the new Siemens-CTI systems, Ecat Exact and Ecat Exact HR, both with an axial field-of-view (FOV) covering around 15 cm. They both have retractable septa and can acquire data from the whole volume within the FOV and can reconstruct volume image data. An example is given how to use the model for live time calculations in a futuristic large axial FOV cylindrical system.<<ETX>>","PeriodicalId":287813,"journal":{"name":"1993 IEEE Conference Record Nuclear Science Symposium and Medical Imaging Conference","volume":"104 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1993-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127992748","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 : 1993-10-31DOI: 10.1109/NSSMIC.1993.373607
C. Davatzikos, Jerry L Prince, R. Bryan
The authors address the problem of brain image registration, and they present a new, nonlinear registration technique. In the first step of the authors' technique they obtain a point-to-point mapping between the outer cortical contours of the brain images using an elastic string algorithm. In the second step the authors register the two images based on the point-to-point correspondence established in the first step. They propose a new, nonlinear registration transformation, which is based on a spatially variable scaling and relation that can describe highly nonlinear deformations. Finally, the authors test their algorithm on two different registration problems: they first consider the registration of a postmortem photograph of a baboon brain cross-section and then an MR image of approximately the same cross-section.<>
{"title":"Brain image registration based on cortical contour mapping","authors":"C. Davatzikos, Jerry L Prince, R. Bryan","doi":"10.1109/NSSMIC.1993.373607","DOIUrl":"https://doi.org/10.1109/NSSMIC.1993.373607","url":null,"abstract":"The authors address the problem of brain image registration, and they present a new, nonlinear registration technique. In the first step of the authors' technique they obtain a point-to-point mapping between the outer cortical contours of the brain images using an elastic string algorithm. In the second step the authors register the two images based on the point-to-point correspondence established in the first step. They propose a new, nonlinear registration transformation, which is based on a spatially variable scaling and relation that can describe highly nonlinear deformations. Finally, the authors test their algorithm on two different registration problems: they first consider the registration of a postmortem photograph of a baboon brain cross-section and then an MR image of approximately the same cross-section.<<ETX>>","PeriodicalId":287813,"journal":{"name":"1993 IEEE Conference Record Nuclear Science Symposium and Medical Imaging Conference","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1993-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122833833","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 : 1993-10-31DOI: 10.1109/NSSMIC.1993.701795
J. Jehlen, K. Nichols, D. Wilkinson, E. Brown
fNTRODlJCTION EPRI has undertaken the Instrumentation and Control (I&C) Initiative to reduce operations and maintenance (O&M) costs through long term life cycle management planning and to promote the cost effective use of modern technology in nuclear power plant I&C upgrades. A key element in the Initiative is the Demonstration Plant Program. The Demonstration Plant Program was started in 1991 with the goal of establishing comprehensive, integrata I&C maintenance and upgrade planning programs in operating nuclear power plants. The intent of these programs is to develop cost effective solutions to I&C obsolescence problems, and to demonstrate the technology developed under EPRI research and development programs. Currently, EPRI has established demonstration programs at eight plants including:
{"title":"Instrumentation And Control Upgrade Planning At Arkansas Nuclear One","authors":"J. Jehlen, K. Nichols, D. Wilkinson, E. Brown","doi":"10.1109/NSSMIC.1993.701795","DOIUrl":"https://doi.org/10.1109/NSSMIC.1993.701795","url":null,"abstract":"fNTRODlJCTION EPRI has undertaken the Instrumentation and Control (I&C) Initiative to reduce operations and maintenance (O&M) costs through long term life cycle management planning and to promote the cost effective use of modern technology in nuclear power plant I&C upgrades. A key element in the Initiative is the Demonstration Plant Program. The Demonstration Plant Program was started in 1991 with the goal of establishing comprehensive, integrata I&C maintenance and upgrade planning programs in operating nuclear power plants. The intent of these programs is to develop cost effective solutions to I&C obsolescence problems, and to demonstrate the technology developed under EPRI research and development programs. Currently, EPRI has established demonstration programs at eight plants including:","PeriodicalId":287813,"journal":{"name":"1993 IEEE Conference Record Nuclear Science Symposium and Medical Imaging Conference","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1993-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126263276","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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