Biological modeling utilizing image data
First Claim
1. A method for quantitative or semi-quantitative modeling of a biological or physiological system, said method comprising the steps of:
- a. acquiring time-series image data relating to said biological or physiological system;
b. generating a prediction of the dynamic evolution of the state of said biological or physiological system using a simulation model that takes into account underlying physiological, chemical or biological variables;
c. converting said biological- or physiological-state prediction into a series of predicted images corresponding temporally to the acquired images; and
d. modifying the simulation model in such a manner as to reduce the magnitude of an error measure that is based upon the differences between the acquired time-series image data and the predicted images.
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Abstract
The present invention relates to a method and system for quantitative and semi-quantitative modeling of biological and physiological systems using image data. More specifically, the system utilizes time-series image data to improve the accuracy of the predictions made by a simulation model capable of forecasting the spatiotemporal evolution of a given biological or physiological system. Furthermore, in accordance with another aspect of the invention, the quality of experimentally acquired images can be improved by using a simulation model to eliminate noise and measurement errors from the acquired image data. Finally, in accordance with another aspect of the invention, certain undamped random disturbances in a biological or physiological system can be detected and tracked by applying a fading-memory filter to acquired time-series data and predictions of the time series using a simulation model that takes into account underlying physiological, chemical or biological variables.
73 Citations
97 Claims
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1. A method for quantitative or semi-quantitative modeling of a biological or physiological system, said method comprising the steps of:
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a. acquiring time-series image data relating to said biological or physiological system;
b. generating a prediction of the dynamic evolution of the state of said biological or physiological system using a simulation model that takes into account underlying physiological, chemical or biological variables;
c. converting said biological- or physiological-state prediction into a series of predicted images corresponding temporally to the acquired images; and
d. modifying the simulation model in such a manner as to reduce the magnitude of an error measure that is based upon the differences between the acquired time-series image data and the predicted images. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43)
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44. A method for quantitative or semi-quantitative modeling of a biological or physiological system, said method comprising the steps of:
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a. acquiring time-series image data relating to said biological or physiological system;
b. generating a prediction of the dynamic evolution of the state of said biological or physiological system using a simulation model that takes into account underlying physiological, chemical or biological variables;
c. converting said image data into state-space data; and
d. adjusting one or more parameters of the simulation model in order to reduce the magnitude of an error measure that is based upon the differences between the acquired state-space data and the corresponding predicted state(s) of the system. - View Dependent Claims (45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86)
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87. A system for quantitative or semi-quantitative modeling of a biological or physiological system, said system comprising:
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a. a means for acquiring time-series image data relating to said biological or physiological system;
b. a means for generating a prediction of the dynamic evolution of the state of said biological or physiological system using a simulation model that takes into account underlying physiological, chemical or biological variables;
c. a means for converting said biological- or physiological-state prediction into a series of predicted images corresponding temporally to the acquired images; and
d. a means for adjusting one or more parameters of the simulation model in order to reduce the magnitude of an error measure based upon the differences between the acquired time-series image data and the predicted images.
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88. A system for quantitative or semi-quantitative modeling of a biological or physiological system, said system comprising:
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a. a means for acquiring time-series image data relating to said biological or physiological system;
b. a means for generating a prediction of the dynamic evolution of the state of said biological or physiological system using a simulation model that takes into account underlying physiological, chemical or biological variables;
c. a means for converting said image data into state-space data; and
d. a means for adjusting one or more parameters of the simulation model in order to reduce the magnitude of an error measure that is based upon the differences between the acquired state-space data and the corresponding predicted state(s) of the system.
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89. A method for improving the quality of spatiotemporal data relating to a biological or physiological system, said method comprising the steps of:
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a. acquiring time-series image data relating to said biological or physiological system;
b. generating a prediction of the dynamic evolution of the state of said biological or physiological system using a simulation model that takes into account underlying physiological, chemical or biological variables; and
c. correcting the acquired images to eliminate noise and measurement errors based upon the predictions of said simulation model.
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90. A system for improving the quality of spatiotemporal data relating to a biological or physiological system, said system comprising:
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a. a means for acquiring time-series image data relating to said biological or physiological system;
b. a means for generating a prediction of the dynamic evolution of the state of said biological or physiological system using a simulation model that takes into account underlying physiological, chemical or biological variables; and
c. a means for correcting the acquired images to eliminate noise and measurement errors based upon the predictions of said simulation model.
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91. A method for quantitative or semi-quantitative modeling of a biological or physiological system, said method comprising the steps of:
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a. acquiring time-series fluorescence image data relating to said biological or physiological system;
b. generating a prediction of the dynamic evolution of the state of said biological or physiological system using a simulation model that takes into account underlying physiological, chemical or biological variables;
c. converting said biological- or physiological-state prediction into a series of predicted images corresponding temporally to the acquired images; and
d. applying a batch estimator or recursive filter to the predicted images and the acquired image data.
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92. A method for quantitative or semi-quantitative modeling of a biological or physiological system, said method comprising the steps of:
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a. acquiring fluorescence image data relating to said biological or physiological system;
b. generating a prediction of the state of said biological or physiological system using a simulation model that takes into account underlying physiological, chemical or biological variables and the acquired fluorescence image data; and
c. converting said biological- or physiological-state prediction into a set of predicted images corresponding to the acquired images. - View Dependent Claims (93)
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94. A method for detecting undamped random disturbances in, and tracking the altered state trajectory of, a biological or physiological system, said method comprising the steps of:
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a. acquiring time-series data relating to said biological or physiological system;
b. generating a prediction of the dynamic evolution of the state of said biological or physiological system using a simulation model that takes into account underlying physiological, chemical or biological variables; and
c. applying a recursive memory-fading filter to determine the onset of a symmetry-breaking event. - View Dependent Claims (95, 97)
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96. A method for detecting undamped random disturbances in, and tracking the altered state trajectory of, a biological or physiological system, said system comprising:
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a. a means for acquiring time-series data relating to said biological or physiological system;
b. a means for generating a prediction of the dynamic evolution of the state of said biological or physiological system using a simulation model that takes into account underlying physiological, chemical or biological variables; and
c. a recursive fading-memory filter applied to predicted state and acquired data to determine the onset of a symmetry-breaking event.
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Specification