Abstract: Disclosed techniques include skin diagnostics using optical signatures. A plurality of optical excitation light wavelength bands is scanned on a material sample, wherein the material sample exhibits optical spectral characteristics along the light wavelength spectrum. Excitation response wavelengths emitted by the material sample are captured in response to the plurality of optical excitation light wavelength bands, wherein the capturing is accomplished using an imaging sensor. Output values of a plurality of pixels of an image from the imaging sensor are measured, wherein the image represents excitation response wavelengths captured by the imaging sensor, wherein the measuring detects optical spectral characteristics of the material sample, and wherein the optical spectral characteristics are in response to the plurality of optical excitation light wavelength bands.

Abstract: Disclosed techniques include image analysis using skin wound factors. One or more skin wound images are obtained for an individual. The skin wound images provide light spectrum information that includes fluorescence and reflectance characteristics. The light spectrum information includes infrared thermal characteristics. Processors are used to analyze the skin wound images to determine metrics for skin wound factors, based on the light spectrum information. The skin wound factors comprise infection, inflammation, granulation, topology, and epithelialization. An epithelialization metric is included in determining skin wound topology. The skin wound topology comprises wound area, wound volume, wound depth, wound shape, wound edge definition, or wound topography. An output indicative of biophysical skin wound status is generated. The output is based on the analyzing of the skin wound factors. The output is augmented, based on analysis of the infrared thermal characteristics.

Abstract: Embodiments related to methods of use of an image analysis system for identifying residual cancer cells after surgery are disclosed. In some embodiments, the image analysis system collects a surgical site image and indicates on a display one or more locations of the identified cancer cells. In some embodiments, the method for identifying residual cancer cells comprises determining and selecting a portion of the surgical site image responsive to an intensity parameter; modifying the selected portion of the surgical site image to determine one or more groups of residual cancer cells based on size; and identifying at least one of the one or more groups of residual cancer cells from the modified portion of the surgical site image using a local-based threshold.

Abstract: Disclosed techniques include wound care image analysis using light signatures. A light wavelength is excited on a material sample. The exciting enables capture of fluorescence characteristics of the material sample. The material sample exhibits fluorescence characteristics along the Red-Green-Blue light wavelength spectrum. The material sample is illuminated with at least three additional light wavelengths. The illuminating enables capture of reflectance characteristics of the material sample. The material sample exhibits reflectance characteristics along the Red-Green-Blue light wavelength spectrum. An output indicative of biophysical status of the material sample is generated. The output is based on analysis of the fluorescence characteristics and the reflectance characteristics. The analysis includes identifying a wound topology within the material sample. The wound topology is identified based on measurements in the wound sample. A thermal image of the material sample is captured.

Abstract: Embodiments related to methods of use of an image analysis system for identifying residual cancer cells after surgery are disclosed. In some embodiments, a patient-specific threshold used to detect abnormal cells in a surgical site can be determined. A medical imaging device can be configured to produce a set of images of an anatomy of a patient. An image analysis system, comprising one or more processors, can be configured to receive the set of images, and analyze the set of images to determine a patient-specific threshold to use to detect abnormal tissue of the patient.

Abstract: Embodiments related to methods of use of an image analysis system for identifying residual cancer cells after surgery are disclosed. In some embodiments, a patient-specific threshold used to detect abnormal cells in a surgical site can be determined. A medical imaging device can be configured to produce a set of images of an anatomy of a patient. An image analysis system, comprising one or more processors, can be configured to receive the set of images, and analyze the set of images to determine a patient-specific threshold to use to detect abnormal tissue of the patient.

Abstract: Embodiments related to methods of use of an image analysis system for identifying residual cancer cells after surgery are disclosed. In some embodiments, the image analysis system collects a surgical site image and indicates on a display one or more locations of the identified cancer cells. In some embodiments, the method for identifying residual cancer cells comprises determining and selecting a portion of the surgical site image responsive to an intensity parameter; modifying the selected portion of the surgical site image to determine one or more groups of residual cancer cells based on size; and identifying at least one of the one or more groups of residual cancer cells from the modified portion of the surgical site image using a local-based threshold.

Abstract: Embodiments related to medical imaging devices including rigid imaging tips and their methods of use for identifying abnormal tissue within a surgical bed are disclosed.

Abstract: Embodiments related to methods of use of an image analysis system for identifying residual cancer cells after surgery are disclosed. In some embodiments, the image analysis system collects a surgical site image and indicates on a display one or more locations of the identified cancer cells. In some embodiments, the method for identifying residual cancer cells comprises determining and selecting a portion of the surgical site image responsive to an intensity parameter; modifying the selected portion of the surgical site image to determine one or more groups of residual cancer cells based on size; and identifying at least one of the one or more groups of residual cancer cells from the modified portion of the surgical site image using a local-based threshold.

Abstract: Disclosed techniques include multispectral sample analysis using absorption signatures. At least two excitation light wavelengths are provided to a material sample. The sample exhibits absorption characteristics along the Red-Green-Blue (RGB) light wavelength spectrum. Output values of an RGB sensor are measured. The measuring detects the absorption characteristics of the sample. The absorption characteristics are in response to the at least two excitation light wavelengths. A third excitation light wavelength is provided and an additional output value of the RGB sensor is measured. The providing at least two excitation light wavelengths and a third excitation light wavelength enable water identification and biochrome identification. An indication of composition of the material sample is generated. The indication is based on interpreting the output values that were measured. An additional RGB sensor enables stereoscopic sensor imaging.

Abstract: Disclosed techniques include multispectral sample analysis using fluorescence signatures. At least one fluorescence excitation light wavelength is provided to a material sample. The material sample exhibits fluorescence characteristics along the Red-Green-Blue (RGB) light wavelength spectrum. The at least one fluorescence excitation light wavelength includes a wavelength less than a wavelength of the RGB light wavelength spectrum. Output values of an RGB sensor are measured. The measuring detects the fluorescence characteristics of the material sample. The fluorescence characteristics are in response to the at least one fluorescence excitation light wavelength. The output of the RGB sensor is compensated based on an analysis of a wavelength response of the RGB sensor. An indication of composition of the material sample is generated. The indication is based on interpreting the output values that were measured. The indication can include skin assessment or wound assessment, taken over time.

Abstract: Disclosed techniques include skin diagnostics using optical signatures. A plurality of optical excitation light wavelength bands is scanned on a material sample, wherein the material sample exhibits optical spectral characteristics along the light wavelength spectrum. Excitation response wavelengths emitted by the material sample are captured in response to the plurality of optical excitation light wavelength bands, wherein the capturing is accomplished using an imaging sensor. Output values of a plurality of pixels of an image from the imaging sensor are measured, wherein the image represents excitation response wavelengths captured by the imaging sensor, wherein the measuring detects optical spectral characteristics of the material sample, and wherein the optical spectral characteristics are in response to the plurality of optical excitation light wavelength bands.

Abstract: Disclosed techniques include exudate analysis using optical signatures. Access to a tissue exudate sample is obtained, wherein the tissue exudate sample contains one or more analytes representing a state of the tissue. The one or more analytes are isolated from the exudate sample on a substrate. The exudate is transferred from the substrate to an immunoassay. The immunoassay is illuminated with photons, wherein the illuminating comprises a controlled photon exposure. The controlled photon exposure comprises ambient lighting and/or one or more fluorescence excitation light wavelength bands. Light emanating from the immunoassay is imaged, wherein the imaging captures intensities of light wavelengths across the light wavelength spectrum. The imaging captures reflected light and fluorescent emanating light. A signature for the one or more analytes is generated, based on analysis of the intensities that were imaged. The signature expresses a magnitude for each of the one or more analytes.

Abstract: Embodiments related to medical imaging devices including rigid imaging tips and their methods of use for identifying abnormal tissue within a surgical bed are disclosed.

Abstract: Embodiments related to medical imaging devices including rigid imaging tips and their methods of use for identifying abnormal tissue within a surgical bed are disclosed.

Abstract: Embodiments related to methods of use of an image analysis system for identifying residual cancer cells after surgery are disclosed. In some embodiments, a patient-specific threshold used to detect abnormal cells in a surgical site can be determined. A medical imaging device can be configured to produce a set of images of an anatomy of a patient. An image analysis system, comprising one or more processors, can be configured to receive the set of images, and analyze the set of images to determine a patient-specific threshold to use to detect abnormal tissue of the patient.

Abstract: Embodiments related to medical imaging devices including rigid imaging tips and their methods of use for identifying abnormal tissue within a surgical bed are disclosed.

Abstract: Embodiments related to medical imaging devices including rigid imaging tips and their methods of use for identifying abnormal tissue within a surgical bed are disclosed.

Abstract: Embodiments related to medical imaging devices including rigid imaging tips and their methods of use for identifying abnormal tissue within a surgical bed are disclosed.