Abstract: Methods and systems for identifying biologic subtypes in a biological specimen may include receiving a data set associated with a cohort of biological specimens, determining a potential number of clusters associated with the data set, associating a cluster with one or more data points in the data set, associating a cluster label with the one or more data points in the data set, treating a related cluster as a biologic subtype and associating a biologic subtype with one or more data points with regions of interest in the data set, establishing duster features and metrics in the data set, determining if a new biologic subtype is identified by comparing the biologic subtype associated with the regions of interest with known biologic subtypes, and discovering a new diagnostic, prognostic, predictive, and/or therapeutic biologic subtype by correlating a new biologic subtype with patient, prognostic, predictive, therapeutic and/or clinical trial data.

Abstract: A method for analyzing biological specimens by spectral imaging to provide a medical diagnosis includes obtaining spectral and visual images of biological specimens and registering the images to detect cell abnormalities, pre-cancerous cells, and cancerous cells. This method eliminates the bias and unreliability of diagnoses that is inherent in standard histopathological and other spectral methods. In addition, a method for correcting confounding spectral contributions that are frequently observed in microscopically acquired infrared spectra of cells and tissue includes performing a phase correction on the spectral data. This phase correction method may be used to correct various types of absorption spectra that are contaminated by reflective components.

Abstract: Methods, systems, and devices for classifying a biological sample that include receiving an image of a biological sample and applying one or more algorithms from a data repository to the image, generating a classification of the biological sample based on the outcome of the one or more algorithms applied to the image, and transmitting the classification for presentation on a display or via another medium. The methods, systems, and devices may also include features for developing a data master reference and/or other correlation/translation features to enable comparison of data sets from one platform to another or from one machine to another or from the same machine at different points in time.

Abstract: A method for analyzing biological specimens by spectral imaging to provide a medical diagnosis includes obtaining spectral and visual images of biological specimens and registering the images to detect cell abnormalities, pre-cancerous cells, and cancerous cells. This method eliminates the bias and unreliability of diagnoses that is inherent in standard histopathological and other spectral methods. In addition, a method for correcting confounding spectral contributions that are frequently observed in microscopically acquired infrared spectra of cells and tissue includes performing a phase correction on the spectral data. This phase correction method may be used to correct various types of absorption spectra that are contaminated by reflective components.

Abstract: Disclosed herein is a process and system to correct reflective distortions of an optical spectrum. In addition, a spectroscopy system that compensates for reflective distortions is disclosed.

Abstract: The methods, devices, and systems may allow a practitioner to obtain information regarding a biological sample, including analytical data, a medical diagnosis, and/or a prognosis or predictive analysis. The method, devices, and systems may provide a grade or level of development for identified diseases. In addition, the methods, devices and systems may generate a confidence value for the predictive classifications generated, which may, for example be generated in a format to show such confidence value or other feature in a graphical representation (e.g., a color code). Further, the methods, devices and system may aid in the identification and discovery of new classes and tissue sub-types.

Abstract: The methods, devices, and systems may allow a practitioner to obtain information regarding a biological sample, including analytical data, a medical diagnosis, and/or a prognosis or predictive analysis. The method, devices, and systems may provide a grade or level of development for identified diseases. In addition, the methods, devices and systems may generate a confidence value for the predictive classifications generated, which may, for example be generated in a format to show such confidence value or other feature in a graphical representation (e.g., a color code). Further, the methods, devices and system may aid in the identification and discovery of new classes and tissue sub-types.

Abstract: The methods, systems, and devices may include performing one or more quality tests to determine and/or certify the quality of slides used in infrared imaging. The methods, systems, and devices may certify a quality of a slide when the average quality assessment of the slide is within the established quality value range.

Abstract: Embodiments of the present disclosure provides improved methods for determining the presence of abnormalities in exfoliated cells. In one embodiment, the present disclosure provides methods for reconstructing cellular spectrum of a cell sample by creating a spectral map of the cellular sample, generating a binary mask of the spectral map, removing edge artifacts from each cell, and co-adding spectral data of each pixel corresponding to the cell to reconstruct the spectrum of each cell.

Abstract: The methods, systems, and devices may include performing one or more quality tests to determine and/or certify the quality of slides used in infrared imaging.

Abstract: Methods, systems, and devices for classifying a biological sample that include receiving an image of a biological sample and applying one or more algorithms from a data repository to the image, generating a classification of the biological sample based on the outcome of the one or more algorithms applied to the image, and transmitting the classification for presentation on a display or via another medium. The methods, systems, and devices may also include features for developing a data master reference and/or other correlation/translation features to enable comparison of data sets from one platform to another or from one machine to another or from the same machine at different points in time.

Abstract: Embodiments of the present disclosure provides improved methods for determining the presence of abnormalities in exfoliated cells. In one embodiment, the present disclosure provides methods for reconstructing cellular spectrum of a cell sample by creating a spectral map of the cellular sample, generating a binary mask of the spectral map, removing edge artifacts from each cell, and co-adding spectral data of each pixel corresponding to the cell to reconstruct the spectrum of each cell.

Abstract: Embodiments of the present disclosure provides improved methods for determining the presence of abnormalities in exfoliated cells. In one embodiment, the present disclosure provides methods for reconstructing cellular spectrum of a cell sample by creating a spectral map of the cellular sample, generating a binary mask of the spectral map, removing edge artifacts from each cell, and co-adding spectral data of each pixel corresponding to the cell to reconstruct the spectrum of each cell.

Abstract: A method for analyzing biological specimens by spectral imaging to provide a medical diagnosis includes obtaining spectral and visual images of biological specimens and registering the images to detect cell abnormalities, pre-cancerous cells, and cancerous cells. This method eliminates the bias and unreliability of diagnoses that is inherent in standard histopathological and other spectral methods. In addition, a method for correcting confounding spectral contributions that are frequently observed in microscopically acquired infrared spectra of cells and tissue includes performing a phase correction on the spectral data. This phase correction method may be used to correct various types of absorption spectra that are contaminated by reflective components.

Abstract: A method for analyzing biological specimens by spectral imaging to provide a medical diagnosis includes obtaining spectral and visual images of biological specimens and registering the images to detect cell abnormalities, pre-cancerous cells, and cancerous cells. This method eliminates the bias and unreliability of diagnoses that is inherent in standard histopathological and other spectral methods. In addition, a method for correcting confounding spectral contributions that are frequently observed in microscopically acquired infrared spectra of cells and tissue includes performing a phase correction on the spectral data. This phase correction method may be used to correct various types of absorption spectra that are contaminated by reflective components.

Abstract: Methods, devices, and systems for imaging tissue and other samples or samples using infrared (IR) transmissions from coherent transmission sources, such as a wide range, tunable, quantum cascade laser (QCL) designed for the rapid collection of infrared microscopic data for medical diagnostics across a wide range of discrete spectral increments. The infrared transmissions are transmitted through, reflected from, and/or transreflected through a sample, and then magnified and/or focused prior to being detected by a detector. After detection, the sample related image data is used to assess the sample. Such methods, devices, and systems may be used to detect abnormalities in tissue, for example, before such abnormalities can be diagnosed using art cytopathological methods. The methods, devices and systems may also optionally include a visible light detection subsystem and/or a motion control subsystem to assist in control and processing of imaging.

Abstract: Disclosed herein is a process and system to correct reflective distortions of an optical spectrum. In addition, a spectroscopy system that compensates for reflective distortions is disclosed.

Abstract: The methods, devices, and systems may allow a practitioner to obtain information regarding a biological sample, including analytical data, a medical diagnosis, and/or a prognosis or predictive analysis. The method, devices, and systems may provide a grade or level of development for identified diseases. In addition, the methods, devices and systems may generate a confidence value for the predictive classifications generated, which may, for example be generated in a format to show such confidence value or other feature in a graphical representation (e.g., a color code). Further, the methods, devices and system may aid in the identification and discovery of new classes and tissue sub-types.

Abstract: Methods, devices, and systems for imaging tissue and other samples or samples using infrared (IR) transmissions from coherent transmission sources, such as a wide range, tunable, quantum cascade laser (QCL) designed for the rapid collection of infrared microscopic data for medical diagnostics across a wide range of discrete spectral increments. The infrared transmissions are transmitted through, reflected from, and/or transreflected through a sample, and then magnified and/or focused prior to being detected by a detector. After detection, the sample related image data is used to assess the sample. Such methods, devices, and systems may be used to detect abnormalities in tissue, for example, before such abnormalities can be diagnosed using art cytopathological methods. The methods, devices and systems may also optionally include a visible light detection subsystem and/or a motion control subsystem to assist in control and processing of imaging.

Abstract: Embodiments of the present disclosure provides improved methods for determining the presence of abnormalities in exfoliated cells. In one embodiment, the present disclosure provides methods for reconstructing cellular spectrum of a cell sample by creating a spectral map of the cellular sample, generating a binary mask of the spectral map, removing edge artifacts from each cell, and co-adding spectral data of each pixel corresponding to the cell to reconstruct the spectrum of each cell.