Abstract: The present invention relates generally to a species (analyte) separation and analysis system, for instance a spectrometry system, comprising a processor for receiving and processing signals from said its detector to remove undesirable variation or noise before further processing into a spectrum, whereby the processor is programmed by a novel program for a normalization preprocessing of the signals of said separation and analysis system.

Abstract: Imaging mass spectrometry (IMS) has become a prime tool for studying the distribution of biomolecules in tissue. Although IMS data sets can become very large, computational methods have made it practically feasible to search these experiments for relevant findings. However, these methods lack access to an important source of information that many human interpretations rely upon: anatomical insight. In this work, this need is addressed by (1) integrating a curated anatomical data source with an empirically acquired IMS data source, establishing an algorithm-accessible link between them; and (2) demonstrating the potential of such an IMS-anatomical atlas link by applying it toward automated anatomical interpretation of ion distributions in tissue.

Abstract: The present invention relates generally to a species (analyte) separation and analysis system, for instance a spectrometry system, comprising a processor for receiving and processing signals from said its detector to remove undesirable variation or noise before further processing into a spectrum, whereby the processor is programmed by a novel program for a normalization preprocessing of the signals of said separation and analysis system.

Abstract: The present invention relates generally to a species (analyte) separation and analysis system, for instance a spectrometry system, comprising a processor for receiving and processing signals from said its detector to remove undesirable variation or noise before further processing into a spectrum, whereby the processor is programmed by a novel program for a normalization preprocessing of the signals of said separation and analysis system.

Abstract: Imaging mass spectrometry (IMS) has become a prime tool for studying the distribution of biomolecules in tissue. Although IMS data sets can become very large, computational methods have made it practically feasible to search these experiments for relevant findings. However, these methods lack access to an important source of information that many human interpretations rely upon: anatomical insight. In this work, this need is addressed by (1) integrating a curated anatomical data source with an empirically acquired IMS data source, establishing an algorithm-accessible link between them; and (2) demonstrating the potential of such an IMS-anatomical atlas link by applying it toward automated anatomical interpretation of ion distributions in tissue.

Abstract: Systems and methods are provided for generating a model relating parameters generated via a first molecular imaging modality to parameters generated via a second molecular imaging modality. First and second feature extractors extract, from images of a region of interest obtained via respective first and second molecular imaging modalities, respective sets of parameters for respective first and second sets of locations. A mapping component associates respective locations of the first and second sets of locations according to their spatial relationship within the region of interest to produce a training set. Each example in the training set comprises a set of parameters associated with a location in the first set of locations and a set of parameters associated with a location in the second set. A modeling component generates a predictive model relating the parameters associated with the first modality with at least one parameter associated with the second modality.

Abstract: Systems and methods are provided for generating a model relating parameters generated via a first molecular imaging modality to parameters generated via a second molecular imaging modality. First and second feature extractors extract, from images of a region of interest obtained via respective first and second molecular imaging modalities, respective sets of parameters for respective first and second sets of locations. A mapping component associates respective locations of the first and second sets of locations according to their spatial relationship within the region of interest to produce a training set. Each example in the training set comprises a set of parameters associated with a location in the first set of locations and a set of parameters associated with a location in the second set. A modeling component generates a predictive model relating the parameters associated with the first modality with at least one parameter associated with the second modality.

Abstract: The present invention relates generally to a species (analyte) separation and analysis system, for instance a spectrometry system, comprising a processor for receiving and processing signals from said its detector to remove undesirable variation or noise before further processing into a spectrum, whereby the processor is programmed by a novel program, for a normalization preprocessing of the signals of said separation and analysis system.