Abstract: An imaging and capture micro-dissection microscope (12) for spectrally analyzing a sample (10) and isolating a region of interest (210) in the sample (10) includes (i) a stage (26A) that retains the sample (10); (ii) an analysis laser assembly (14) that generates a coherent interrogation beam (16A) that is directed at the sample (10), the interrogation beam (16A) having a center wavelength that is in the infrared region; (iii) an image sensor (24A) that receives light from the sample (10), the image sensor (24A) capturing image information that is used to identify the region of interest (210) in the sample (10); (iv) a separation assembly (18) that separates the region of interest (210) from the sample (10) while the sample (10) is retained by the stage (26A); and (v) a capturing assembly (20) that captures the region of interest (210).

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: Spectrally analyzing an unknown sample (10A) for the existence of a characteristic includes (i) analyzing a first known sample (10C) having the characteristic and a second known sample (10D) not having the characteristic to identify less than fifty diagnostic spectral features, each diagnostic spectral feature being present at a different diagnostic wavelength in a mid-infrared spectral region; (ii) directing a plurality of interrogation beams (16) at the unknown sample (10A), each of the interrogation beams (16) having a different interrogation wavelength, and each interrogation wavelength corresponding to a different one of the diagnostic wavelengths; (iii) acquiring a plurality of separate output images (245) of the unknown sample (10A), wherein each of the output images (245) is acquired while the unknown sample is illuminated by a different one of the interrogation beams (16); and (iv) analyzing less than fifty output images (245) with a control system (28) to determine whether the characteristic is pres

Abstract: Spectrally analyzing an unknown sample (10A) includes (i) providing a spatially homogeneous region (10B) of the unknown sample (10A); (ii) directing a plurality of interrogation beams (16) at the spatially homogeneous region (10B) with a laser source (14), (iii) acquiring a separate output image (245) while the unknown sample (10A) is illuminated by each of the interrogation beams (16) with an image sensor (26A); and (iv) analyzing less than fifty output images (245) to analyze whether a characteristic is present in the unknown sample (10A) with a control system (28) that includes a processor. Each of the interrogation beams (16) is nominally monochromatic and has a different interrogation wavelength that is in the mid-infrared spectral range.

Abstract: Spectrally analyzing an unknown sample (10A) includes (i) providing a spatially homogeneous region (10B) of the unknown sample (10A); (ii) directing a plurality of interrogation beams (16) at the spatially homogeneous region (10B) with a laser source (14), (iii) acquiring a separate output image (245) while the unknown sample (10A) is illuminated by each of the interrogation beams (16) with an image sensor (26A); and (iv) analyzing less than fifty output images (245) to analyze whether a characteristic is present in the unknown sample (10A) with a control system (28) that includes a processor. Each of the interrogation beams (16) is nominally monochromatic and has a different interrogation wavelength that is in the mid-infrared spectral 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: Spectrally analyzing an unknown sample (10A) includes (i) providing a spatially homogeneous region (10B) of the unknown sample (10A); (ii) directing a plurality of interrogation beams (16) at the spatially homogeneous region (10B) with a laser source (14), (iii) acquiring a separate output image (245) while the unknown sample (10A) is illuminated by each of the interrogation beams (16) with an image sensor (26A); and (iv) analyzing less than fifty output images (245) to analyze whether a characteristic is present in the unknown sample (10A) with a control system (28) that includes a processor. Each of the interrogation beams (16) is nominally monochromatic and has a different interrogation wavelength that is in the mid-infrared spectral 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: 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: 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: 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: 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.