Abstract: A method and system of analyzing a resected tissue specimen is provided. The method includes: a) using an imaging system to image a tissue sample with excitation light configured to produce fluorescent emissions from the tissue sample, the imaging producing signals representative of the fluorescent emissions from the sample; b) determining a presence or an absence of at least one suspect tissue region on the tissue sample; c) determining a spatial location of said at least one suspect tissue region determined to be present on the tissue sample; d) using the imaging system to image the suspect tissue region at the determined spatial location with excitation light configured to produce Raman scattering from the sample, the imaging producing signals representative of the Raman scattering from sample; and e) analyzing the determined suspect tissue region using the signals representative of the Raman scattering from the sample.

Abstract: A system and method for analyzing bladder tissue sample is provided that includes an excitation light source, a photodetector, an optical filter, and a system controller. The excitation light source produces excitation lights centered on a distinct wavelengths. At least one of the wavelengths produces autofluorescence emissions from one or more biomolecules, and at least one of the wavelengths produces diffuse reflectance signals. The photodetector detects at least one of the autofluorescence emissions or diffuse reflectance signals and produces signals representative thereof. The optical filter filters at least one of autofluorescence emissions or the diffuse reflectance signals. The system controller communicates with the system components and a memory storing instructions. The instructions cause the system controller to control the excitation light unit, receive and process the photodetector signals, produce a signal image, and analyze the tissue sample to determine the presence of detrusor muscle tissue.

Abstract: A method and system for classifying a tissue specimen is provided. The method includes: a) interrogating a tissue specimen with a first interrogation light; b) detecting first light from the tissue specimen resulting from the interrogation, wherein the first light includes a first scattered light component and a first fluorescence light component, and producing first signals; c) interrogating the tissue specimen with a second interrogation light at a second excitation wavelength, wherein the first and second excitation wavelengths are within about 2 nm of each other; d) detecting second light from the tissue specimen resulting from the interrogation, wherein the second light includes a second scattered light component and a second fluorescence light component, and producing second signals; e) determining a difference between the first and second lights; f) determining a fluorescence spectrum produced by the interrogation of the tissue specimen; and g) classifying the tissue specimen.

Abstract: A method and system for analyzing a tissue sample is provided.

Abstract: A method and system for determining the presence of a mass of cancerous cells in vivo within a tissue body is provided. The method includes: a) performing an examination of the tissue body using a diagnostic method operable to determine the presence of a suspect tissue mass, and determining a location of the same; b) administering a solution containing “RR-CTEs”, the RR-CTEs configured to target and bind with cancerous cells; c) interrogating the tissue body with a beam of light, wherein the RR-CTEs are configured to produce Raman scattered light upon impingement; d) collecting the Raman scattered light; e) processing the collected Raman scattered light to determine a presence or an absence of the a Raman signature; and f) comparing the determined location of the suspect tissue mass with the determined location of the mass of cancerous cells to determine the presence of the mass of cancerous cells.

Abstract: A method of and a system for analyzing a tissue sample is provided. The method includes a) imaging a tissue specimen to produce multispectral images of the tissue specimen, the multispectral images including autofluorescence (AF) images and reflectance images acquired at different excitation and emission wavelengths; b) using the multispectral images to produce a plurality of biomolecular barcodes (BBCs) attributable to the tissue specimen; and c) analyzing the tissue specimen to identify a type of the tissue specimen, the analyzing using the plurality of BBCs attributable to the tissue specimen and a plurality of predetermined BBCs based on known tissue types.

Abstract: A system and method for analyzing a sample using Raman spectral light includes a light source, a light detector, a narrow band pass filter and an analyzer. Within the system, excitation light is directed to interrogate the sample. The narrow band pass filter is positioned to receive Raman scattered light produced as a result of the interrogation. The light detector is positioned to receive the Raman scattered light that has passed through the at least one narrow band pass filter. The analyzer contains stored instructions that when executed cause the processor to a) control the light source; and b) process signals produced by the light detector to analyze the sample material, the signals representative of the intensity of the Raman scattered light received by the at least one light detector corresponding to one or more wavenumbers in a high wavenumber region of a Raman signal.

Abstract: A system for processing Raman scattering light from a sample is provided. The system includes a source, a digital mirror device (DMD), a detector, and an analyzer. The DMD is configured to reflect Raman scattering light and includes micromirrors selectively controllable between ON and OFF states. The detector is configured to detect Raman scattering light and to produce signals representative of the Raman scattering light. The analyzer is in communication with the light source, the DMD, the detector, and a memory storing instructions, which instructions when executed cause the processor to: a) control the light source to produce a beam of light for interrogating the sample; b) control the DMD to place in an ON or OFF state based on one or more known spectral shapes stored in the memory; and c) process the Raman scattering light reflected by the micromirrors in the ON state.

Abstract: A system and method for assaying high and low abundant biomolecules within a biological fluid sample is provided. The method includes: a) placing a biological fluid sample in contact with a first nanostructure surface; b) interrogating the sample with a light source, the sample in contact with the first nanostructure surface, the interrogation using a SERS technique; c) detecting an enhanced Raman scattering from at least one high abundant biomolecule type and producing first signals representative thereof; d) placing the sample in contact with a second nanostructure surface having a targeting agent that targets a low abundant biomolecule; e) interrogating the sample with the light source using the SERS technique; f) detecting the enhanced Raman scattering from the low abundant biomolecules and producing second signals representative thereof; and g) assaying the biological fluid sample using the first signals and the second signals.

Abstract: A system and method for mapping a tissue sample is provided. The system includes a light source, a scanner, a digital mirror device (DMD), a light detector, and an analyzer. The DMD has an array of micromirrors. The analyzer controls the light source, controls the scanner, controls the DMD to have on-state micromirrors aligned with a light beam, and other micromirrors in an off-state. The on-state micromirrors direct the light beam to a tissue sample. The analyzer assigns one or more location codes to the on-state micromirrors, controls the light detector to receive Raman light emitted from the tissue sample, correlates the location codes of the on-state micromirrors with light detector signals representative of the Raman emitted light, and produces a spatial map of the Raman emitted light.

Abstract: A method and system for identifying a Raman spectrum component of an observed spectrum is provided. The observed spectrum is produced by interrogating a material such as a tissue sample with light at the one or more predetermined wavelengths, and the observed spectrum includes a background fluorescence component representative of fluorescent emissions resulting from the light interrogation and a Raman spectrum component representative of a Raman scattering resulting from the light interrogation. The method includes a) creating a reconstructed fluorescence spectrum representative of the background fluorescence component of the observed spectrum using one or more empirically determined fluorescent spectral profiles; and b) identifying the Raman spectrum of the observed spectrum using the reconstructed fluorescence spectrum.

Abstract: A method and system for classifying a tissue specimen is provided. The method includes: a) interrogating a tissue specimen with a first interrogation light; b) detecting first light from the tissue specimen resulting from the interrogation, wherein the first light includes a first scattered light component and a first fluorescence light component, and producing first signals; c) interrogating the tissue specimen with a second interrogation light at a second excitation wavelength, wherein the first and second excitation wavelengths are within about 2 nm of each other; d) detecting second light from the tissue specimen resulting from the interrogation, wherein the second light includes a second scattered light component and a second fluorescence light component, and producing second signals; e) determining a difference between the first and second lights; f) determining a fluorescence spectrum produced by the interrogation of the tissue specimen; and g) classifying the tissue specimen.

Abstract: A method and system for identifying tissue types is provided that utilizes Raman scattered light in the high wavenumber region (HWN) of Raman spectrum. The method includes: a) interrogating a tissue specimen with at least one wavelength of light, the wavelength of light operable to produce Raman scattered light in a HWN region of Raman spectrum from the tissue specimen; b) producing signal data representative of the Raman scattering, the signal data relating signal intensity as a function of wavenumber within the HWN region; c) fitting a curve to a portion of the signal data attributable to a HWN peak within the signal data, for a plurality of different HWN peaks; d) determining a plurality of characteristics of each fitted curve; and e) determining a tissue type using the determined characteristics and stored collective data representative of fitted peaks in the HWN region of a plurality of different tissue types.

Abstract: An apparatus and method for analyzing a tissue sample to provide depth-selective information includes at least one light source, collection light optics, and a light detector. The light source is configured to produce a light beam having one or more wavelengths of light that cause a tissue sample to produce Raman light signals upon interrogation of the tissue sample. The light beam is oriented to impinge on an exposed surface of the tissue sample at a point of incidence (POI), and oriented so that the light beam enters the tissue sample at an oblique angle relative to the exposed surface of the tissue sample. The collection light optics are configured to collect the Raman light signals emanating from the tissue sample at one or more predetermined lateral distances from the point of incidence. The light detector is configured to receive the Raman light signals from the collection light optics.

Abstract: The subject invention pertains to methods and systems for classifying leukocytes using artificial intelligence called AIRFIHA (artificial-intelligence enabled reagent-free imaging hematology analyzer) that can accurately classify subpopulations of leukocytes in a label-free manner. AIRFIHA can not only subtype lymphocytes into B and T cell but is capable of sorting different types of T cells subtypes. AIRFIHA is realized through training a two-step neural network using label-free images of separated leukocytes acquired from a custom-built quantitative phase microscope. Owing to its easy operation, low cost, and strong discerning capability of complex leukocyte subpopulations, AIRFIHA is clinically translatable and can also be deployed in resource-limited settings.

Abstract: A system and method for assaying high and low abundant biomolecules within a biological fluid sample is provided. The method includes: a) placing a biological fluid sample in contact with a first nanostructure surface; b) interrogating the sample with a light source, the sample in contact with the first nanostructure surface, the interrogation using a SERS technique; c) detecting an enhanced Raman scattering from at least one high abundant biomolecule type and producing first signals representative thereof; d) placing the sample in contact with a second nanostructure surface having a targeting agent that targets a low abundant biomolecule; e) interrogating the sample with the light source using the SERS technique; f) detecting the enhanced Raman scattering from the low abundant biomolecules and producing second signals representative thereof; and g) assaying the biological fluid sample using the first signals and the second signals.

Abstract: A method and system for determining the presence or absence of cancerous cells within subject tissue. The method includes: providing a material that includes a peptide component configurable in a non-binding form when disposed in a neutral pH environment, and in a binding form when disposed in an acidic pH environment, wherein the peptide component is configured to produce a first Raman spectrum when subjected to one or more predetermined wavelengths of light; administering the material to a subject tissue; interrogating the subject tissue with light; sensing the subject tissue for light emitted from the subject tissue, and producing signals representative of the sensed emitted light; analyzing the signals to determine a presence or absence of the first Raman spectrum; and determining the presence or absence of cancerous cells based on the presence or absence of the first Raman spectrum within the sensed light emitted from the subject tissue.

Abstract: A system and method for determining the presence of cancerous tissue within a tissue cavity is provided. The system includes one or more excitation light sources, a photodetector, a probe, and a system controller. The probe includes an optically transparent probe body configured to fit within the tissue cavity. The system controller is in communication with the excitation light sources, the photodetector, and a memory storing instructions. The instructions when executed cause the system controller to a) control the excitation light sources to produce excitation light beams within the probe body, the excitation light beams operable to produce a response of the tissue to the interrogation and control the photodetector to detect the response and produce signals representative thereof; and b) produce information indicative of a presence of the cancerous tissue using the signals representative of the response.

Abstract: A system for and method of examining a tissue sample using stimulated Raman spectroscopy is provided. The method includes: a) producing a first beam of light at a first wavelength; b) producing a second beam of light at at least a second wavelength, the second wavelength different from the first wavelength; c) combining the first and second beams of light to provide a combined output; d) interrogating a tissue sample with the combined output to produce Raman scattering light, the tissue sample prepared with at least one target molecule having a targeting agent conjugated with a Raman silent dye, the targeting agent configured to bind with at least one biomarker; e) detecting at least a portion of the produced Raman scattering light using a photodetector; and f) producing immunohistological data relating to the tissue sample using photodetector signals representative of the detected Raman scattering light.

Abstract: A system for processing Raman scattering light from a sample is provided. The system includes a source, a digital mirror device (DMD), a detector, and an analyzer. The DMD is configured to reflect Raman scattering light and includes micromirrors selectively controllable between ON and OFF states. The detector is configured to detect Raman scattering light and to produce signals representative of the Raman scattering light. The analyzer is in communication with the light source, the DMD, the detector, and a memory storing instructions, which instructions when executed cause the processor to: a) control the light source to produce a beam of light for interrogating the sample; b) control the DMD to place in an ON or OFF state based on one or more known spectral shapes stored in the memory; and c) process the Raman scattering light reflected by the micromirrors in the ON state.