Method for analyzing biological specimens by spectral imaging

Abstract

A method for registering a visual image and a spectral image of a biological sample includes aligning a first set of coordinate positions of a plurality of reticles on a slide holder and a second set of coordinate positions of the plurality of reticles on the slide holder. The method further includes generating a registered image of a visual image of a biological sample and a spectral image of the biological sample based upon the alignment of the first and second set of coordinate positions.

1 - 17 . (canceled) 
     
     
         18 . A method for analyzing biological specimens by spectral imaging, comprising:
 acquiring spectral data from a spectral image of a biological specimen;   pre-processing the spectral data by selecting a spectral range, computing a second derivative, performing reverse Fourier transformation, performing zero-filling and reverse Fourier transformation, and performing a phase correction to generate a pre-processed spectral image;   performing multivariate analysis on the pre-processed spectral image data to detect spectral differences in the pre-processed spectral data;   creating at least one group of data with similar spectral data based on the multivariate analysis; and   generating at least one or more of a grayscale or pseudo-color spectral image, supervised spectral images, and unsupervised pseudo-color cluster images based on the at least one group of data.   
     
     
         19 . The method of  claim 18 , further comprising:
 using one or more of the pre-processed spectral data, the pre-processed spectral image, the grayscale or pseudo-color spectral image, the supervised spectral images, and the unsupervised pseudo-color cluster images for one or more of diagnostic analysis, prognostic analysis, and predictive analysis.   
     
     
         20 . The method of  claim 18 , further comprising:
 performing unsupervised analysis on one or more of the pre-processed spectral data, the pre-processed spectral image, the grayscale or pseudo-color spectral image, the supervised spectral images, and the unsupervised pseudo-color cluster images to identify disease conditions.   
     
     
         21 . The method of  claim 18 , further comprising:
 acquiring a visual image of the biological specimen; and   registering the grayscale or pseudo-color spectral image with the visual image by spatially matching the grayscale or pseudo-color spectral image to align with the visual image into a common coordinate system to generate a registered image.   
     
     
         22 . The method of  claim 21 , wherein in the registered image, the pixels in the grayscale or pseudo-color spectral image and the visual image coincide to same points in the common coordinate system. 
     
     
         23 . The method of  claim 22 , wherein when a pixel region in the grayscale or pseudo-color spectral image is selected, the corresponding pixel region in the visual image is accessed, and
 wherein when a pixel region in the visual image is selected, the corresponding pixel region in the grayscale or pseudo-color spectral image is accessed.   
     
     
         24 . The method of  claim 21 , wherein the registered image is used for one or more of diagnostic analysis, prognostic analysis, and predictive analysis. 
     
     
         25 . The method of  claim 21 , further comprising:
 identifying a region of a visual image containing a disease or condition;   using the registered image to correlate the region of the visual image to spectral data in the grayscale or pseudo-color image corresponding to the region of the visual image; and   developing a training set of data for a supervised algorithm for use with one or more of diagnostic analysis, prognostic analysis, and predictive analysis based on the correlation.   
     
     
         26 . The method of  claim 18 , wherein the phase correction is performed on one or more of second derivative data and non-derivative data. 
     
     
         27 . A system for analyzing biological specimens by spectral imaging, comprising:
 a memory in communication with a processor, wherein the memory and the processor are cooperatively configured to:
 acquire spectral data from a spectral image of a biological specimen; 
 pre-process the spectral data by selecting a spectral range, computing a second derivative, performing reverse Fourier transformation, performing zero-filling and reverse Fourier transformation, and performing a phase correction to generate a pre-processed spectral image; 
 perform multivariate analysis on the pre-processed spectral image data to detect spectral differences in the pre-processed spectral data; 
 create at least one group of data with similar spectral data based on the multivariate analysis; and 
 generate at least one or more of a pre-processed spectral image, a grayscale or pseudo-color spectral image, supervised spectral images, and unsupervised pseudo-color cluster images based on the at least one group of data. 
   
     
     
         28 . The system of  claim 27 , wherein the memory and the processor are further operable to use one or more of the pre-processed spectral data, the pre-processed spectral image, the grayscale or pseudo-color spectral image, the supervised spectral images, and the unsupervised pseudo-color cluster images for one or more of diagnostic analysis, prognostic analysis, and predictive analysis. 
     
     
         29 . The system of  claim 27 , wherein the memory and the processor are further operable to perform unsupervised analysis on one or more of the pre-processed spectral data, the pre-processed spectral image, the grayscale or pseudo-color spectral image, the supervised spectral images, and the unsupervised pseudo-color cluster images to identify disease conditions. 
     
     
         30 . The system of  claim 27 , wherein the memory and the processor are further operable to:
 acquire a visual image of the biological specimen; and   register the grayscale or pseudo-color spectral image with the visual image by spatially matching the grayscale or pseudo-color spectral image to align with the visual image into a common coordinate system to generate a registered image.   
     
     
         31 . The system of  claim 30 , wherein in the registered image, the pixels in the grayscale or pseudo-color spectral image and the visual image coincide to same points in the common coordinate system. 
     
     
         32 . The system of  claim 31 , wherein when a pixel region in the grayscale or pseudo-color spectral image is selected, the corresponding pixel region in the visual image is accessed, and
 wherein when a pixel region in the visual image is selected, the corresponding pixel region in the grayscale or pseudo-color spectral image is accessed.   
     
     
         33 . The system of  claim 30 , wherein the registered image is used for one or more of diagnostic analysis, prognostic analysis, and predictive analysis. 
     
     
         34 . The system of  claim 30 , wherein the memory and the processor are further operable to:
 identify a region of a visual image containing a disease or condition;   use the registered image to correlate the region of the visual image to spectral data in the grayscale or pseudo-color image corresponding to the region of the visual image; and   develop a training set of data for a supervised algorithm for use with one or more of diagnostic analysis, prognostic analysis, and predictive analysis based on the correlation.   
     
     
         35 . The system of  claim 27 , wherein the phase correction is performed on one or more of second derivative data and non-derivative data. 
     
     
         36 . A computer-readable medium storing instructions executable by a computer device, comprising:
 at least one instruction for causing the computer device to acquire spectral data from a spectral image of a biological specimen;   at least one instruction for causing the computer device to pre-process the spectral image data by selecting a spectral range, computing a second derivative, performing reverse Fourier transformation, performing zero-filling and reverse Fourier transformation, and performing a phase correction to generate a pre-processed spectral image;   at least one instruction for causing the computer device to perform multivariate analysis on the pre-processed spectral data to detect spectral differences in the pre-processed spectral data;   at least one instruction for causing the computer device to create at least one group of data with similar spectral data based on the multivariate analysis; and   at least one instruction for causing the computer device to generate at least one or more of a pre-processed spectral image, a grayscale or pseudo-color spectral image, supervised spectral images, and unsupervised pseudo-color cluster images based on the at least one group of data.