Multi-Spectral Three Dimensional Imaging System and Method

Abstract

A processor receives a first image of a first section of a specimen contacted with at least one first fluorophore having an emission spectrum in the range of approximately 200 nm to 1000 nm, the first image created using a first wavelength of invisible light. The processor receives a second image of a second section of the specimen, the second section adjacent to the first section and the second image created using the first wavelength of invisible light. The processor co-registers the first image and the second image. The processor creates a single-plane image of the first section using a next-image process; wherein the creating of the image includes a debluring process. The processor receives an image of a third section of the specimen created using the first wavelength of invisible light. The processor creates a 3D image of the specimen using at least three images of adjacent specimen sections.

1 . A computer-implemented method of creating an image of a specimen wherein the specimen is contacted with at least one first fluorophore having an emission spectrum in the range of approximately 200 nm to 1000 nm, the method comprising the steps of:
 i. receiving, by a processor, a first image N x  of a first section S x  of a specimen, the first image created using a first wavelength of invisible light;   ii. receiving, by the processor, a second image N x+1  of a second section S x+1  of the specimen, the second section S x+1  being adjacent to the first section S x  and the second image created using the first wavelength of invisible light;   iii. co-registering, by the processor, the first image and the second image;   iv. creating, by the processor, a single-plane image of the first section using a next-image process; wherein the creating of the image includes a debluring process;   v. receiving, by the processor, an image N x+3  of a third section S x+3  of the specimen created using the first wavelength of invisible light; and,   vi. creating, by the processor, a 3D image of the specimen using at least three images of adjacent specimen sections.   
     
     
         2 . The method of  claim 1 , wherein the step of receiving, by a processor, includes receiving a visible light image V x  of the first section S x  of the specimen created using white light. 
     
     
         3 . The method of  claim 1 , wherein the method includes reiterating the processes of steps i. through vii for receiving images N x  for a next section S x  of a specimen, where x=2 and increments by 1 for each iteration. 
     
     
         4 . The method of  claim 2 , wherein the method includes reiterating the processes of steps i. through vii for receiving images N x  and V x  for a next section S x  of a specimen, where x=2 and increments by 1 for each iteration; and co-registering, by the processor, the visible light images of the section of the specimen 
     
     
         5 . The method of  claim 1 , wherein the de-blurring process includes one of subsurface fluorescence removal, resolving an aberration in camera optics or physical correction. 
     
     
         6 . The method of  claim 1 , wherein the specimen is contacted with the first fluorophore, and a second, different fluorophore, said second fluorophore having an emission spectrum in the range of, but not limited to, approximately 200 nm to 1000 nm. 
     
     
         7 . The method of  claim 4 , further comprising:
 determining a tissue type from an image and wherein the de-blurring is performed based on the tissue type.   
     
     
         8 . The method of  claim 7  wherein determining the tissue type is from a visible light image, an invisible light image, or an invisible light image in combination with a visible light image. 
     
     
         9 . The method of  claim 7  wherein the tissue type is determined by a processor using a classification algorithm based on a stored history or library. 
     
     
         10 . The method of  claim 5 , wherein the de-blurring includes one of an analytical solution, a Monte Carlo simulation, a point spread function method, and a deconvolution method. 
     
     
         11 . The method of  claim 10 , wherein the deconvolution method includes one of: a measured point spread function kernel, a simulated point spread function kernel, a Richardson-Lucy method, a Weiner filter deconvolution, a Van Cittert deconvolution, a blind deconvolution, and a regularized deconvolution method. 
     
     
         12 . The method of  claim 1 , further comprising:
 receiving, by the processor, an image of the first section of the specimen created using visible light.   
     
     
         13 . A system for creating an image of a specimen comprising:
 a light source;   an image capture device;   a whitelight light source;   a processor configured to:
 receive a first image of a first section of a specimen, the first image created using a first wavelength of invisible light; 
 receive a second image of a second section of the specimen, the second section being adjacent to the first section and the second image created using the first wavelength of invisible light; 
 co-register the first image and the second image; and 
 create a single-plane image of the first section using a next-image process; 
 receive a first whitelight light image of the first section of the specimen created using white light; and 
 co-register the images of the first section of the specimen. 
   
     
     
         14 . The system of  claim 13 , wherein the processor is further configured to:
 receive an Nth image of an Nth section of the specimen created using the first wavelength of invisible light; and   create a 3D image of the specimen using at least three images of adjacent specimen sections.   
     
     
         15 . The system of  claim 14 , wherein the creating of the 3D image is performed via a next-image process. 
     
     
         16 . The system of  claim 13 , wherein the specimen is contacted with at least one first fluorophore having an emission spectrum in the range of approximately 200 nm to 1000 nm. 
     
     
         17 . The system of  claim 13 , wherein the specimen is contacted with a first fluorophore and a second, different fluorophore, said second fluorophore having an emission spectrum in the range of approximately 200 nm to 1000 nm. 
     
     
         18 . The system of  claim 13 , wherein the processor is further configured to:
 receive a third image of the first section of the specimen, the third image created using a second wavelength of invisible light;   receive a fourth image of a second section of the specimen, the fourth image created using the second wavelength of invisible light;   co-register the third image and the fourth image; and   create a single-plane image of the first section using a next-image process.   
     
     
         19 . The system of  claim 18 , wherein the processor is further configured to de-blur the first image. 
     
     
         20 . The system of  claim 18 , further comprising:
 determining a tissue type from a visible light image, wherein the de-blurring is performed based on tissue type.   
     
     
         21 . The system of  claim 19 , wherein the de-blurring includes one of an analytical solution to optical transport, a Monte Carlo simulation, a point spread function method, and a deconvolution method. 
     
     
         21 . The system of  claim 19 , wherein the deconvolution method includes one of a measured point spread function kernel, a simulated point spread function kernel, a Richardson-Lucy method, a Weiner filter deconvolution, a Van Cittert deconvolution, a blind deconvolution, and a regularized deconvolution method. 
     
     
         22 . The system of  claim 12 , further comprising:
 a display in communication with the processor.