Abstract: A method of determining structured behavior from network adjacency matrices is described. A method of detecting physiological signals from a subject is described.

Abstract: A method of determining structured behavior from network adjacency matrices is described. A method of detecting physiological signals from a subject is described.

Abstract: A non-invasive method of detecting anomalous tissue, such as cancerous or injured tissue, in a patient. At least two hemoglobin signal components of hemoglobin levels in at least one segment of tissue of the patient are non-invasively measured over time. Time varying changes of at least a first of the hemoglobin signal components are measured with respect to at least time varying changes of a second of the hemoglobin signal components. A co-varying coordinate system of the time varying changes is generated. Any anomalous tissue in the measured segment of tissue is detected from a signature of the measured segment of tissue in the co-varying coordinate system which differs from a signature of non-anomalous tissue in the co-varying coordinate system. Preferably, five hemoglobin signal components are measured: oxyHb, deoxyHb, total Hb (totalHb=oxyHb+deoxy Hb), Hb oxygen saturation (HbO2Sat=(oxyHb/totalHb)*100), and tissue-hemoglobin oxygen exchange HbO2Exc (deoxyHb?oxyHb).

Abstract: A non-invasive method of detecting anomalous tissue, such as cancerous or injured tissue, in a patient. At least two hemoglobin signal components of hemoglobin levels in at least one segment of tissue of the patient are non-invasively measured over time. Time varying changes of at least a first of the hemoglobin signal components are measured with respect to at least time varying changes of a second of the hemoglobin signal components. A co-varying coordinate system of the time varying changes is generated. Any anomalous tissue in the measured segment of tissue is detected from a signature of the measured segment of tissue in the co-varying coordinate system which differs from a signature of non-anomalous tissue in the co-varying coordinate system. Preferably, five hemoglobin signal components are measured: oxyHb, deoxyHb, total Hb (totalHb=oxyHb+deoxy Hb), Hb oxygen saturation (HbO2Sat=(oxyHb/totalHb)*100), and tissue-hemoglobin oxygen exchange HbO2Exc (deoxyHb?oxyHb).

Abstract: A non-invasive method of detecting anomalous tissue, such as cancerous or injured tissue, in a patient. At least two hemoglobin signal components of hemoglobin levels in at least one segment of tissue of the patient are non-invasively measured over time. Time varying changes of at least a first of the hemoglobin signal components are measured with respect to at least time varying changes of a second of the hemoglobin signal components. A co-varying coordinate system of the time varying changes is generated. Any anomalous tissue in the measured segment of tissue is detected from a signature of the measured segment of tissue in the co-varying coordinate system which differs from a signature of non-anomalous tissue in the co-varying coordinate system. Preferably, five hemoglobin signal components are measured: oxyHb, deoxyHb, total Hb (totalHb=oxyHb+deoxy Hb), Hb oxygen saturation (HbO2Sat=(oxyHb/totalHb)*100), and tissue-hemoglobin oxygen exchange HbO2Exc (deoxyHb?oxyHb).

Abstract: A non-invasive method of detecting anomalous tissue, such as cancerous or injured tissue, in a patient. At least two hemoglobin signal components of hemoglobin levels in at least one segment of tissue of the patient are non-invasively measured over time. Time varying changes of at least a first of the hemoglobin signal components are measured with respect to at least time varying changes of a second of the hemoglobin signal components. A co-varying coordinate system of the time varying changes is generated. Any anomalous tissue in the measured segment of tissue is detected from a signature of the measured segment of tissue in the co-varying coordinate system which differs from a signature of non-anomalous tissue in the co-varying coordinate system. Preferably, five hemoglobin signal components are measured: oxyHb, deoxyHb, total Hb (totalHb=oxyHb+deoxy Hb), Hb oxygen saturation (HbO2Sat=(oxyHb/totalHb)*100), and tissue-hemoglobin oxygen exchange HbO2Exc (deoxyHb?oxyHb).

Abstract: Data from a target system (616) that exhibits a non-linear relationship between system properties and measurement data, is processed by applying a linear filter (F) to improve resolution and accuracy. The filter reduces inaccuracies that are introduced by an algorithm used to reconstruct the data. The filter is defined by assigning time varying functions, such as sinusoids (200), to elements (210) in a model (Y) of the system to perturbate the elements. The resulting data output from the model is reconstructed using the same algorithm used to subsequently reconstruct the data from the target system. The filter is defined as a matrix (F) that transforms the reconstructed data of the model (X) back toward the known properties of the model (Y). A library of filters can be pre-calculated for different applications. In an example implementation, the system is tissue that is imaged using optical tomography.

Abstract: A method of significantly improving the quality of solutions to a system of linear equations. The solution to a system of linear equations is enhanced by: (1) modeling a target medium into a plurality of elements and imposing at least one localized fluctuation into the target medium; (2) measuring an output resulting from at least one localized fluctuation; and (3) processing the measured output to reconstruct a result, determining a correction filter, and applying the correction filter to the result.

Abstract: A method and system for minimizing inter-coefficient crosstalk in imaging the internal properties of a scattering medium. The method and system minimizing inter-coefficient. crosstalk in image reconstruction by solving a system of linear perturbation equations with the use of relative detector values, weight matrix scaling, and constraints based on either the know or unknown direction of the perturbations in the medium's properties. The constraint being either (1) positive or negative corresponding to the direction of a known perturbations, or (2) solving the system of equations with both positive and negative constraints and summing the results where the direction of the perturbations are unknown. The advantages of the inventive method and system result in effective isolation of absorption and scattering coefficient variations, even for complex combinations of perturbations in these coefficients.

Abstract: A method and system for minimizing inter-coefficient crosstalk in imaging the internal properties of a scattering medium. The method and system minimizing inter-coefficient crosstalk in image reconstruction by solving a system of linear perturbation equations with the use of relative detector values, weight matrix scaling, and constraints based on either the know or unknown direction of the perturbations in the medium's properties. The constraint being either (1) positive or negative corresponding to the direction of a known perturbations, or (2) solving the system of equations with both positive and negative constraints and summing the results where the direction of the perturbations are unknown. The advantages of the inventive method and system result in effective isolation of absorption and scattering coefficient variations, even for complex combinations of perturbations in these coefficients.

Abstract: A system and method for determining the relative losses and/or efficiencies of the individual channels of a multi-channel measurement system, such as a multi-channel optical tomography system. The system and method provide several independent estimates of the losses associated with each of the plurality of source and detector components, whereby statistical analysis of the independent estimates can be used to reveal system errors or misalignments.

Abstract: A system and method for determining the relative losses and/or efficiencies of the individual channels of a multi-channel measurement system, such as a multi-channel optical tomography system. The system and method provide several independent estimates of the losses associated with each of the plurality of source and detector components, whereby statistical analysis of the independent estimates can be used to reveal system errors or misalignments.