Abstract:
A compact and low cost microscope illuminator capable of generating 3-D optical images includes a first light source and a second light source. The two light sources lead two optical paths: one to illuminate a sample and another to project a pattern onto the focal plane of a microscope objective lens. The two light sources are controlled by a processor and can be turned on and off rapidly. A 3-D optical microscope equipped with said microscope illuminator and a method of creating a 3-D image on said 3-D optical microscope are also described.

Description:
RELATED APPLICATIONS 
     This application is a continuation-in-part of U.S. patent application Ser. No. 11/754,282 filed on May 26, 2007now U.S Pat No. 7,729,049, which is incorporated by reference herein in its entirety. 
    
    
     FIELD OF THE INVENTION 
     This invention relates generally to an optical microscope and, more particularly, to a microscope illuminator for a three-dimensional (3-D) imaging optical microscope. 
     BACKGROUND OF THE INVENTION 
     A conventional microscope enables an operator to view magnified images of minute features on a sample otherwise invisible to the human eye. Because of this, conventional microscopes have been widely used in universities, in research institutes, and in many industries. A conventional microscope, however, has important limitations. For example, it only provides a two-dimensional (2-D) image of a sample while in the real world a majority of samples are 3-D in nature. 
     Various improvements have been made over the years to achieve 3-D viewing and 3-D imaging with optical microscopes. Costales in U.S. Pat. No. 6,275,335 discloses a stereomicroscope using various polarizing optical components to achieve a stereoscopic effect in the image. Although Costales&#39; microscope produces a perception of depth, it cannot provide quantitative measurement of the depth dimension. 
     Kino in U.S. Pat. No. 5,022,743 proposes a confocal microscope utilizing a spinning Nipkow disc. Sheppard in U.S. Pat. No. 4,198,571 discloses a confocal microscope based on laser scanning. Although a confocal microscope is able to generate a 3-D image and provide quantitative depth measurement, it is expensive to build and relatively complex to maintain and operate. In addition, if one already bought a conventional microscope, it is not easy and in many cases impossible to turn his microscope into a confocal microscope. 
     Sieckmann in U.S. Appl. No. 2004/0257360A1 proposes a method of creating 3-D images of a sample by analyzing a stack of images of the sample taken at various focus positions. Although it is cost effective to implement such a method, it only works on samples with contrasting features. In short, Sieckmann&#39;s method fails to generate a reliable and accurate 3-D image of a sample with little or no contrast. 
     Morgan in U.S. Pat. No. 5,381,236 proposes an optical range sensor that is capable of sensing the depth profile of a plain surface by actively projecting a pattern of light onto the target object. Although Morgan&#39;s sensor measures the 3-D profile of a sample, it does not combine the 3-D profile with the intensity or color information of the sample. As a result, his sensor does not yield a 3-D image. In addition, the pattern of light in Morgan&#39;s sensor is always superimposed on the sample surface, and thus interferes with the true features of the sample surface being captured by a camera. 
     Accordingly, there is a need for a 3-D optical microscope that is relatively low cost to build and easy to operate; a method that can be easily deployed to turn a conventional microscope into a 3-D optical microscope; and a 3-D imaging method that works on all samples regardless of their feature contrast. 
     SUMMARY OF THE INVENTION 
     The need is met with the present invention which achieves three objectives: first, to create a simple and relatively low cost microscope that is capable of generating a 3-D image on samples with or without contrast; second, to propose simple hardware modifications that one can make to turn a conventional optical microscope into a 3-D optical microscope; and third, to disclose a method that enables reliable and accurate 3-D imaging on almost any sample regardless of its image contrast. 
     In one aspect of the present invention, a compact and low cost microscope illuminator capable of generating 3-D optical images includes a first light source and a second light source. The two light sources lead two optical paths: one to illuminate a sample and another to project a pattern onto the focal plane of a microscope objective lens. The two light sources are controlled by a processor and can be turned on and off rapidly. 
     Other aspects and advantages of the present invention will become apparent from the following detailed description, taken in conjunction with the accompanying drawings, illustrating by way of example the principles of the invention. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1A  is a top view block diagram illustrating a microscope illuminator of the present invention. 
         FIG. 1B  is a block diagram illustrating a reflective 3-D optical microscope of the present invention. 
         FIG. 2  is a flowchart illustrating a process of extracting a 2-D contrast array from a 2-D image using maximum gradient method. 
         FIG. 3  is a flowchart illustrating a process of performing a Z scan and image capture. 
         FIG. 4  is a flowchart illustrating a process of generating a 3-D image based on image contrast. 
         FIG. 5  is a flowchart illustrating Z scan and image acquisition process of the present invention. 
         FIG. 6  is a flowchart illustrating a data analysis process to generate a 3-D image. 
         FIG. 7  is a block diagram illustrating a transmitted 3-D optical microscope of the present invention. 
         FIG. 8  is a diagram illustrating major components of a conventional optical microscope with a reflective illuminator. 
         FIG. 9  is a diagram illustrating modifications made to the conventional optical microscope of  FIG. 8  to turn it into a 3-D optical microscope in accordance with the present invention. 
         FIG. 10  is a diagram illustrating major components of a conventional optical microscope with a transmitted illuminator. 
         FIG. 11  is a diagram illustrating modifications made to the conventional optical microscope of  FIG. 10  to turn it into a 3-D optical microscope in accordance with the present invention. 
         FIG. 12  is a diagram illustrating modifications made to the conventional optical microscope of  FIG. 10  to turn it into a 3-D optical microscope in accordance with the present invention. 
     
    
    
     DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS 
       FIG. 1A  is a top view block diagram illustrating a microscope illuminator of the present invention. The microscope illuminator  100  contains two light sources  101  and  102  forming two light paths as illustrated by the dot-dashed lines. Light source  101  launches a first light path. The first part of the first light path consists of light source  101 . The second part of the first light path consists of a first beam-splitter  103 , a lens group formed by an achromat doublet lens  105  and a double-convex lens  106 , and a second beam-splitter  107 . Light source  102  launches a second light path. The first part of the second light path consists of light source  102  and a patterned article  104 . The second part of the second light path consists of a first beam-splitter  103 , a lens group formed by an achromat doublet lens  105  and a double-convex lens  106 , and a second beam-splitter  107 . Although the first parts of their paths are different, the first and second light paths share the same second part of their paths. Beam-splitter  107  is mounted on a linear slider linked to a pull lever  109 . If necessary, pull lever  109  can slide beam-splitter  107  sideways so that it is outside the shared optical path of illuminator  100 . The optical components of illuminator  100  are mounted inside a dark enclosure with two openings (not shown): a top opening and a bottom opening. The top opening is directly above beam-splitter  107  while the bottom opening directly below beam-splitter  107 . These two openings allow light from both light paths to interact with the outside world. A multi-pin connector  108  is linked to light sources  101  and  102  via electrical wires. 
     In the preferred embodiment, light sources  101  and  102  are light emitting diodes or LEDs. Other light sources such as halogen lamps, fiber coupled lights, lasers, and etc can also be used and are within the scope of this invention. Lens  105  is an achromat doublet lens. Lens  106  is a double-convex lens. It is understood by those skilled in the art that other types of lenses can also be used and are within the scope of this invention. The patterned article is a piece of glass with a two dimensional array of evenly spaced opaque dots formed on one of its surfaces. Different types of patterns such as a grid and etc. can also be used. In fact, any pattern will work as long as it satisfy the following conditions: (1) it has high contrast; (2) it is either regular or random but evenly distributed; (3) it is semi-transparent; (4) its minimum feature size matches sampling resolution of an imaging optical sensor used. In addition, different substrate materials such as a photographic film and etc. can also be used to carry the pattern. These various designs of a patterned article are also within the scope of this invention. The patterned surface of the patterned article is located at the effective focal plane of said lens group consists of lenses  105  and  106 . 
       FIG. 1B  is a diagram illustrating a reflective 3-D optical microscope equipped with illuminator  100  in accordance with the present invention. Illuminator  100  is shown in side view. To avoid confusion, the optical components inside illuminator  100  are not shown in  FIG. 1B . Whenever these components are mentioned in the next several paragraphs, the reader is advised to reference  FIG. 1A . A microscope operating in reflective illumination mode is often used for studying opaque samples such as a semiconductor wafer. When operating in reflective mode, a microscope objective lens  110  is mounted directly below the bottom opening of illuminator  100 . When light source  101  or  102  is turned on, the lens group formed by lenses  105  and  106  projects an image of the light source (e.g. light sources  190 A and  190 B) onto the entrance pupil (EP) of microscope objective lens  110  (via the solid line ray tracing), thereby ensuring uniform illumination (e.g.  195 A (with  190 A) or  195 B (with  190 B)) on sample  120  (having a dot pattern for illustration purposes). When light source  102  is turned on, the lens group formed by lenses  105  and  106  in conjunction with objective lens  110  projects an image of the pattern on patterned article  104  onto the focal plane (FP) of objective lens  110  (via the dotted line ray tracing). Positioning means  130  is provided to change the relative position between sample  120  and objective lens  110 . As a result, different features on the sample can be brought into focus of objective lens  110 . As an option, a XY stage (not shown) can be incorporated into the microscope of  FIG. 1B  to move sample  120  around in a horizontal plane. In the preferred embodiment, positioning means  130  is a motorized Z stage. There are, of course, other ways to vary the relative position between sample  120  and objective lens  110 . For example, objective lens  110  could be mounted on a piezoelectric actuator. In such an arrangement, sample  120  remains stationary while objective lens  110  moves up and down. It is understood by those skilled in the art that these variations are within the scope of this invention. Coupler  140  in conjunction with objective lens  110  yields an image of sample  120  on optical sensor  150 . In the preferred embodiment, optical sensor  150  is either a CCD or a CMOS camera. 
     Processor  160  is connected to the 3-D optical microscope of  FIG. 1B . Said processor is used to control positioning means  130 , light sources  101  and  102  of  FIG. 1A , and optical sensor  150 . In addition, said processor analyzes data and creates a 3-D image of the sample. In the preferred embodiment, said process is a personal computer. 
     Creating a 3-D image on the 3-D optical microscope of  FIG. 1B  involves just a single pass according to the present invention. During the process, positioning means  130  moves sample  120  from a pre-determined start position away from objective lens  110  through a set of pre-determined steps. At each step, processor  160  turns light source  102  on and light source  101  off. As a result, an image of the pattern on patterned article  104  is projected onto the focal plane of objective lens  110 , optical sensor  150  captures and saves a first image of the sample; then processor  160  turns light source  101  on and light source  102  off, optical sensor  150  captures and saves a second image of the sample. This process repeats itself until all the steps have been taken. When done, processor  160  analyzes the first and second image set to create a 3-D image. The details of the single pass 3-D image creation process of the present invention will be discussed when we describe  FIGS. 5 and 6  later. In the next several paragraphs, we will discuss software controls and algorithms related to acquiring 2-D image stacks of a sample, extracting image contrast, constructing 3-D depth profiles, and creating a 3-D rendering of the sample. 
     A microscope objective lens is usually characterized by several important parameters such as focal length, magnification, working distance (W.D.), and numerical aperture (N.A.). To a large extent, the N.A. of an objective lens determines its depth-of-field. When a sample is placed at the focal plane of an objective lens, the sample is said to be in-focus, and the image produced by the objective lens has the sharpest contrast. If the same sample is placed slightly away from the focal plane but is still within the range defined by the depth-of-field, the image contrast is still relatively sharp. As the sample is moved out of the depth-of-field range, it becomes out-of-focus, and the image becomes blurrier. 
     Mathematically, image contrast is related to the high frequency or gradient content of the image intensity: the sharper the image, the higher the intensity gradient, and the stronger its high frequency content. Consider a microscope operator who is trying to find the best focus. He will move the sample up and down around the focal plane of the objective lens to find the point where the image contrast is the highest. Similarly, a system can be devised so that the relative position between the sample and the objective lens is changed at controlled steps. After each step move, a camera takes an image; the image is converted into digital form so a computer can extract its high frequency content. This high frequency content is recorded and compared with that of the previous steps. As the sample is stepping one-way towards and eventually passing through the best focus, its image&#39;s high frequency content level would rise, reach a peak, and then fall. The best focus position corresponds to where the image&#39;s high frequency content reaches a maximum. 
     Generally, an object is not flat but rather has a depth profile. By calculating the high frequency contents at each pixel for every image taken at a specific distance between the sample and the objective lens, the computer can compare and find the distance where maximum high frequency content of each pixel occurs. By applying this calculation to all pixels, the process can, in theory, yield a depth profile of the sample. The intensity or color values of those pixels that are located on the contour of the depth profile can also be extracted from the relevant images. Graphic rendering of both depth and color information should yield a 3-D image of the sample. This type of image contrast based 3-D creation method forms the bases of Sieckmann in U.S. Appl. No. 2004/0257360A1. 
     There are many well-known methods in calculating the high frequency content of a pixel. Most of these methods are based on finding the intensity differences among neighboring pixels, and are called high pass filters, or gradient filters. Most commonly, the operation of these filters is a convolution of a filter mask with the pixel and its immediate 8 neighboring pixels: 
     
       
         
               
               
               
             
               
               
               
               
               
               
             
           
               
                   
               
               
                 Filter mask, Laplacian 
                 Neighboring pixels 
               
               
                   
               
             
             
               
                   
               
             
          
           
               
                 −1 
                 −1 
                 −1 
                 P(−1, −1) 
                 P(0, −1) 
                 P(1, −1) 
               
               
                 −1 
                 8 
                 −1 
                 P(−1, 0) 
                 P(0, 0) 
                 P(1, 0) 
               
               
                 −1 
                 −1 
                 −1 
                 P(−1, 1) 
                 P(0, 1) 
                 P(1, 1) 
               
               
                   
               
             
          
         
       
     
     Where P(i,j) is the intensity of a pixel located (i,j) pixels away from the reference pixel or pixel of interest, and i being the relative pixel number in the horizontal (X) direction, and j being that in the vertical (Y) direction. For example, if P(0, 0) is the intensity of the pixel of interest, then P(−1,−1) refers to that of its top left neighboring pixel, P(0,−1) that of its top neighbor, and P(1,−1) that of its top right neighbor. Using the Laplacian high pass filter to find the high frequency content of P(0, 0) involves convolving the Laplacian filter mask with the neighboring pixels:
 
High frequency content of  P (0,0)=absolute(8 *P (0,0)−
 
1*P(−1,−1)−1*P(0,−1)−1*P(1,−1)−
 
1*P(−1,0)−1*P(1,0)−
 
1*P(−1,1)−1*P(0,1)−1*P(1,1))  Equation 1
 
     A high pass filter, like the Laplacian, is non-directional in that it does not care whether or not an image has directional features. There are directional high pass or edge filters that have filter masks optimized to the direction of interest. For example, if an image is known to have horizontal edges or lines, and if only the vertical component of the high frequency content is wanted, then the North-South edge filter mask can be used to produce a much stronger result than one can get by using a non-directional filter mask. 
     
       
         
               
             
               
               
               
             
           
               
                   
               
               
                 North-South directional filter mask: 
               
               
                   
               
             
             
               
                   
               
             
          
           
               
                 −1 
                 −1 
                 −1 
               
               
                 −0 
                 0 
                 0 
               
               
                 1 
                 1 
                 1 
               
               
                   
               
             
          
         
       
     
     Since most images do not have a fixed feature orientation, a single directional filter operation will in general not yield desirable results. Instead, multiply applications of directional filters such as the ones shown below, each with a different direction, are performed to find the gradients along these directions. Among them, the one filter that yields maximum value determines the maximum high frequency content of a pixel. Such an approach is called maximum gradient method. 
     
       
         
               
               
               
               
             
               
               
               
               
               
               
               
               
               
               
               
               
             
           
               
                   
               
               
                 North-South 
                 East-West 
                 135 deg 
                 45 deg 
               
               
                 mask: 
                 mask: 
                 mask: 
                 mask: 
               
               
                   
               
             
             
               
                   
               
             
          
           
               
                 −1 
                 −1 
                 −1 
                 1 
                 0 
                 −1 
                 −1 
                 −1 
                 0 
                 0 
                 −1 
                 −1 
               
               
                 0 
                 0 
                 0 
                 1 
                 0 
                 −1 
                 −1 
                 0 
                 1 
                 1 
                 0 
                 −1 
               
               
                 1 
                 1 
                 1 
                 1 
                 0 
                 −1 
                 0 
                 1 
                 1 
                 1 
                 1 
                 0 
               
               
                   
               
             
          
         
       
     
     A three-by-three filter mask is commonly used because of its small size, thus computational efficient, and because it captures only the highest frequency content. Other directional 3×3 edge filter masks are also possible. For example, the Sobel edge filter mask, shown below, will yield similar results. 
     
       
         
               
             
               
               
               
             
           
               
                   
               
               
                 Sobel North-South mask: 
               
               
                   
               
             
             
               
                   
               
             
          
           
               
                 1 
                 2 
                 1 
               
               
                 0 
                 0 
                 0 
               
               
                 −1 
                 −2 
                 −1 
               
               
                   
               
             
          
         
       
     
     A larger filter mask, 5×5 or 7×7 for example, also works. In particular, a larger filter mask can be tailored to work better for images with lower contrast, or with more lower frequency contents, at the expense of computation efficiency. It is understood that other filter masks that can be used to extract contrast information is within the scope of the present invention. 
     A process of extracting a 2-D contrast array from a 2-D image based on maximum gradient method is illustrated in  FIG. 2 . In step  201 , a default 2-D ContrastArray(x, y) is created, where all pixel are either left un-initialized or set to a default value. In steps  202  and  203 , the initial pixel location is set to (x=1, y=1). In step  204 , a test array is created by copying the intensity values of a 3-by-3 section of the image pixels centering around pixel (1, 1). Convolving this test array with a North-South mask in a manner similar to Equation 1 yields a value C 1  in step  205 . Subsequently, convolving the same test array with an East-West, 135-deg, and 45-deg masks yield values C 2 , C 3 , and C 4  respectively in steps  206 - 208 . In step  209 , a comparison is made among C 1 , C 2 , C 3 , and C 4  to find the maximum absolute value. In step  210 , the maximum contrast for pixel (1, 1), ContrastArray(1, 1), is set to equal to the maximum value found in step  209 . Next, we move one pixel over in the horizontal direction, that is, our next pixel is (2, 1). Since x=2, x is less than (image width−1), test  211  returns YES and the process flow is looped back to  204 . This loop will run its course until x≧(image width−1). At that point, the flow proceeds to step  212  where we start to increment y pixel number from 1 to 2, and the process is moved back to step  203 , and x is set to 1. Again the loop will run its course until y≧(image height−1) and test  212  returns NO. At that moment we have filled in the entire ContrastArray(x, y) except for the border pixels. We simply fill ContrastArray corresponding to the border pixels with the values of their adjacent pixels in step  213 . We now have finished generating a 2-D contrast array from a 2-D image. 
     To create a 3-D depth profile of a sample based on contrast analysis method, a stack of images must be taken at different focus positions or relative sample-objective lens z distances. The detailed image capturing process is illustrated in  FIG. 3 . The process starts with step  301 , the creation of a default IntensityArray(x, y, z) where all pixels are either left un-initialized or set to a default value. At this point, a user must determine the range of z distances in order to cover the tallest peak and the deepest valley on the sample. This is done in steps  302  and  303 . In step  304 , the user also needs to specify the number of steps, so the computer can calculate the Z step size needed to cover the entire z distance range. Alternatively, he can specify step size, and the computer determines the number of steps to cover the z range. The user must also choose the right amount of illumination and select appropriate gain and exposure time for the camera so that an image captured by the camera is neither too bright nor too dark. Of course, once all of these settings are fine tuned, they can be stored in a recipe to be used later by the computer on similar samples. After choosing all the settings, the sample is moved to the starting Z scan position in step  305 . In step  306 , the camera captures an image in digital form. The intensity values of every pixel of the image and the corresponding z distance value is stored into IntensityArray(x, y, z). At that point, the flow proceeds to check point  307  to see if the last Z scan step is reached. If not, the sample is moved down one step, at  308 , and the process is directed back to step  306 . This loop will run its course until the last Z scan step is reached. The process of  FIG. 3  is called Z scan and image capture. 
     Since the working distance of a high magnification objective lens is usually very small, some precaution is needed to prevent the objective lens from coming into contact with the sample during the Z scan. Generally speaking, it is safer to start the Z scan from a position where the sample is closest to the objective lens within the Z scan range, and gradually move the sample away from the objective lens. In the case of  FIG. 3 , this means to start the scan from the bottom of the sample, and move the sample down to cover the full Z scan range. As mentioned earlier, there are alternative ways to carry out the Z scan other than moving the sample. For example, it is possible to move the objective lens up and down to achieve the same result as stepping the sample. If the approach is moving the objective lens, it is safer to start the Z scan from the bottom of the sample, and then gradually step the objective lens upward to cover the full Z scan range. 
     Once a stack of images is captured through the Z scan process of  FIG. 3 , a 3-D image of the sample can be constructed using a process outlined in  FIG. 4 . The process starts with step  401 , the creation of a high contrast array ContrastArray(x, y, z). For every z step, the corresponding values of ContrastArray(x, y, z) is calculated based on the maximum gradient method of  FIG. 2  using the image data stored in IntensityArray(x, y, z) of  FIG. 3 . The next step,  402 , is to create a default array 3DZ(x, y) to store depth value and a default array 3DI(x, y) to store intensity value. In steps  403  and  404 , the pixel location (x, y) is initially set at x=0 and y=0. For this initial pixel (0, 0), a search is carried out to find the maximum value among array elements ContrastArray(0, 0, z). The z value corresponding to this maximum is defined as Z max  and is then stored as array element 3DZ(0, 0) in step  405 . The intensity value corresponding to IntensityArray(0, 0, Z max ) is stored as array element 3DI(0, 0) in step  406 . It is now time to move to the next pixel x=1 and y=0, or pixel (1, 0) in step  407 . Test  408  is carried out to see if x is less than the image width. A positive answer will direct the flow back to steps  405  through  408 . This loop will run its course until test  408  yields a negative answer. At that point  409 , the y pixel number is incremented by 1. Test  410  is carried out to see if y is less than the image height. A positive answer will direct the flow back to steps  404  through  410 . This loop will run its course until test  410  yields a negative answer. At that moment, array 3DZ(x, y) and array 3DI(x, y) are filled. The final step  411  involves taking the z value of 3DZ(x, y) and image intensity value 3DI(x, y) at every pixel location (x, y) and rendering them as a 3-D image. 
     While contrast based 3-D image creation method, as described during the discussion of  FIGS. 2 through 4 , works for samples with a surface texture that produces high image contrast when in focus, it has difficulties with smooth samples with little contrast. Such an important limitation is unfortunately associated with Sieckmann in U.S. Appl. No. 2004/0257360A1. An improved 3-D image generation method of the present invention that overcomes this difficulty will now be described. Our method involves a one-pass image acquisition process and subsequent data analysis.  FIG. 5  outlines the one-pass image acquisition process of the present invention.  FIG. 6  illustrates a data analysis process to construct a 3-D image in according with the present invention. 
     In a one-pass image acquisition process of the present invention, the process begins at step  520  of  FIG. 5  with the creation of two default arrays IntensityArray(x, y, z) and IntensityArray2(x, y, z). In step  521 , preparation for the Z scan is carried out by following the steps of  302  through  305  in  FIG. 3 , and the sample is moved to the starting position of the Z scan. If the sample has little or no contrast, such as a polished clean bare silicon wafer, it is normally a challenge to know when the surface is in focus. In such a case, light source  102  of  FIG. 1A  can be turned on so that an image of the pattern on patterned article  104  is projected onto the focal plane of the objective lens to help the search for the top and bottom of the Z scan range. Whenever the pattern of patterned article  104  is in focus, we know that the flat sample is also in focus, and vice versa. For a sample with topography or depth profile, whenever a certain part of it, say region A, is in focus, the corresponding part of the pattern of patterned article  104  which overlaps with region A in the image field-of-view will also be in focus. In step  522 , processor  160  turns light source  102  on and light source  101  off. As a result, an image of the pattern on patterned article  104  is projected onto the focal plane of the objective lens. In step  523 , a first image of the sample at the current z position is captured and saved in IntensityArray(x,y,z). This image contains information from both the sample and the projected pattern. In step  524 , processor  160  turns light source  101  on and light source  102  off, effectively erases the pattern. As a result, the focal plane of the objective lens now only contains information of the sample. In the mean time, processor  160  also adjusts the intensity of light source  101  automatically so that the average image intensity with or without the projected pattern&#39;s presence is the same. In step  525 , a second image of the sample is captured and saved in IntensityArray2(x, y, z). In step  526 , a test is carried out to see if the last Z scan step is reached. If not, the sample is moved down one step, in  527 , and the process is directed back to step  522 . This loop will run its course until the last Z scan step is reached. At that point, IntensityArray(x, y, z) is filled with image data from the first image set, and IntensityArray2(x, y, z) is filled with image data from the second image set. 
       FIG. 6  outlines a data analysis process involved in constructing a 3-D image according to the present invention. The process starts with  630 , the creation of a high contrast array ContrastArray(x, y, z) from IntensityArray(x, y, z). Note that IntensityArray(x, y, z) and IntensityArray2(x, y, z) are fundamentally different; while the former is based on images containing information from both the sample and the patterned article, the latter is based on images containing information from the sample only. The next step,  631 , is to generate a 3DZ(x, y) from ContrastArray(x, y, z) according the procedure of  FIG. 4 . In steps  632  and  633 , the pixel location (x, y) is initially set at y=0 and x=0. For this initial pixel (0, 0), the value of 2-D array element 3DI(0, 0) is set equal to IntensityArray2(0, 0, z) in step  634 , where z is the value of element 3DZ(0, 0). It is now time to move to the next pixel x=1 and y=0, or pixel (1, 0), in step  635 . Test  636  is carried out to see if x is less than the image width. A positive answer will direct the flow back to steps  634  through  636 . This loop will run its course until test  636  yields a negative answer. At that point  637 , the y pixel number is incremented by 1. Test  638  is carried out to see if y is less than the image height. A positive answer will direct the flow back to steps  633  through  638 . This loop will run its course until test  638  yields a negative answer. At that moment, array 3DI(x, y) are filled with image information from IntensityArray2(x, y, z). The final step  639  involves taking the z values of 3DZ(x, y) and image intensity or color values 3DI(x, y) at every pixel location (x, y) and rendering them as a 3-D image. 
     Those skilled in the art of computer programming and image processing will be familiar with techniques for improving the computational efficiency of the algorithm disclosed above. In particular, the use of parallel programming to speed up the process of image capturing, processing, and storage is within the scope of this invention. 
     It is worth pointing out that the z values of 3DZ(x, y) are based entirely on IntensityArray(x, y, z) while the image intensity or color values of 3DI(x, y) is generated with data only from IntensityArray2(x, y, z). In essence, for the one-pass image acquisition process of this invention, we are using the first image set to find a 3-D skeleton of the sample, and then filled the skeleton with image intensity or color data from the second image set. The most important difference between the 3-D creation method of the present invention and that of Sieckmann in U.S. Appl. No. 2004/0257360A1 lies in the fact that in generating a 3-D skeleton of a sample, we rely on the image contrast of a patterned article while Sieckmann relies on the image contrast of the sample itself. Therefore, the method of the present invention will work on samples with little or no image contrast while that of Sieckmann&#39;s won&#39;t. 
       FIG. 7  is a diagram illustrating a transmitted 3-D optical microscope equipped with illuminator  100  in accordance with the present invention. In  FIG. 7 , illuminator  100  is shown in side view. To avoid confusion, the optical components inside illuminator  100  are not shown in  FIG. 7 . Whenever these components are mentioned, the reader is advised to reference  FIG. 1A . A microscope operating in transmitted illumination mode is often used for studying transparent objects such as biology related samples. When operating in transmitted illumination mode, illuminator  100  is turned upside down so that its normal bottom opening is now pointing upwards. A condenser lens  711  is mounted directly above the normal bottom opening of illuminator  100 . When light source  101  or light source  102  is on, lens group formed by lenses  105  and  106  projects an image of the light source onto the front aperture of condenser lens  711  ensuring uniform illumination on sample  720 . When light source  102  is on, condenser  711  together with lens group formed by lenses  105  and  106  projects an image of the pattern on patterned article  104  onto the focal plane of objective lens  710 . 
     Positioning means  730  is provided to change the relative position between sample  720  and objective lens  710 . As a result, different features on the sample can be brought into focus of objective lens  710 . As an option, a XY stage (not shown) can be incorporated into the microscope of  FIG. 7  to move sample  720  around in a horizontal plane. Condenser lens  711  and sample  720  moves in tandem under the command of positioning means  730 . In the preferred embodiment, positioning means  730  is a motorized Z stage. There are, of course, other ways to vary the relative position between sample  720  and objective lens  710 . For example, objective lens  710  could be mounted on a piezoelectric actuator. In such an arrangement, the sample remains stationary while the objective lens moves up and down. It is understood by those skilled in the art that these variations are within the scope of this invention. Coupler  740  in conjunction with objective lens  710  yields an image of the sample on optical sensor  750 . In the preferred embodiment, optical sensor  750  is either a CCD or a CMOS camera. Processor  160  is connected to the 3-D optical microscope of  FIG. 7 . Said processor is used to control positioning means  730 , light sources  101  and  102 , and optical sensor  750 . In addition, said processor analyzes data and creates a 3-D image of a sample. In the preferred embodiment, said process is a personal computer. 
     Creating a 3-D image on the 3-D optical microscope of  FIG. 7  involves just a single pass according to the present invention. During the process, positioning means  730  moves sample  720  from a pre-determined start position away from objective lens  710  through a set of pre-determined steps. At each step, processor  160  turns light source  102  on and light source  101  off. As a result, an image of the pattern on patterned article  104  is projected onto the focal plane of objective lens  710 , optical sensor  750  captures and saves a first image of the sample; then processor  160  turns light source  101  on and light source  102  off, optical sensor  750  captures and saves a second image of the sample. This process repeats itself until all the steps have been taken. When done, processor  160  analyzes the first and second image set to create a 3-D image. The details of the single pass 3-D image creation process of the present invention has been discussed when we describe  FIGS. 5 and 6  earlier. 
       FIG. 8  is a diagram illustrating a conventional optical microscope with a reflective illuminator. Light source  801  is attached onto illuminator  800 . Objective turret  803 , often with 4 to 6 mounting holes, is attached to microscope body  804 . Objective lens  805  is threaded into one of the mounting holes of objective turret  803 . Sample stage  806  can move in X and Y direction with turning knob  807  and move in vertical (Z) direction with focusing knobs  808  or  809 . Focusing knob  808  can initiate large step moves in the Z direction and therefore is often called coarse focus knob. Focusing knob  809  performs small step moves in the Z direction and therefore is often called fine focus knob. Sample  810  is seated on sample stage  806 . Trinocular tube  811  is attached to illuminator  800 . Two identical eyepieces  812  slide into two of the three openings on the trinocular tube. An operator can view the sample through the eyepieces. The third opening on the trinocular tube is reserved for adding a camera which is optional for a conventional microscope. 
       FIG. 9  illustrates modifications made to a conventional microscope of  FIG. 8  in order to turn it into a 3-D optical microscope in accordance with the present invention. Illuminator  100  is mounted on top the regular microscope illuminator  800  of  FIG. 8 . Means for focusing adjustment  913  is implemented either on fine focus knob  809  or on objective turret  803  of  FIG. 8 . Some examples of means for focusing adjustment are electrical motor, piezoelectric actuator, and etc. In the preferred embodiment, means for focusing adjustment  913  is a motor coupled to fine focus knob  809  of  FIG. 8 . It is understood that other means of focusing adjustment is also within the scope of the present invention. Coupler  914  is mounted on trinocular tube  811  of  FIG. 8  and camera  915  is attached to coupler  914 . Pull level  109  is used to pull beam-splitter  107  out of the optical path of illuminator  100  when the microscope is operating in dark-field mode. Finally, processor  160  is connected to the modified microscope of  FIG. 9 . The processor is used to control means for focusing adjustment  913 , camera  915 , and light sources  101  and  102  of  FIG. 1A . In addition, said processor analyzes data and creates a 3-D image of the sample. In the preferred embodiment, processor  160  is a personal computer. 
       FIG. 10  is a diagram illustrating a conventional optical microscope with a transmitted illuminator. A substantial portion of the illuminator is hidden inside microscope body  1000 . Some visible components of the illuminator typically include lens  1003  and condenser lens  1004 . Light source  1001  is mounted to the entrance of the illuminator. Objective turret  1005 , often with 4 to 6 mounting holes, is attached to microscope body  1000 . Objective lens  1006  is threaded into one of the mounting holes of objective turret  1005 . Sample stage  1007  can move in X and Y direction with turning knob  1008  and move in vertical (Z) direction with focusing knobs  1009  or  1010 . Focusing knob  1009  can initiate large step moves in the Z direction and therefore is often called coarse focus knob. Focusing knob  1010  performs small step moves in the Z direction and therefore is often called fine focus knob. Sample  1011  is mounted on sample stage  1007 . Condenser lens  1004  and sample stage  1007  travel in the Z direction together under the command of focusing knobs  1009  and  1010 . Trinocular tube  1012  is attached to microscope body  1000 . Two identical eyepieces  1013  slide into two of the three openings on the trinocular tube. An operator can view the sample through the eyepieces. The third opening on the trinocular tube is reserved for adding a camera which is optional for a conventional microscope. 
       FIG. 11  illustrates modifications made to a conventional microscope of  FIG. 10  in order to turn it into a 3-D optical microscope in accordance with the present invention. Illuminator  100  is mounted upside down on top of lens  1003  of  FIG. 10 . Means for focusing adjustment  1114  is implemented either on fine focus knob  1010  or on objective turret  1005  of  FIG. 10 . Some examples of means for focusing adjustment are electrical motor, piezoelectric actuator, and etc. In the preferred embodiment, means for focusing adjustment  1114  is a motor coupled to fine focus knob  1010  of  FIG. 10 . It is understood that other means of focusing adjustment is within the scope of the present invention. Coupler  1115  is mounted on trinocular tube  1012  of  FIG. 10  and camera  1116  is attached to coupler  1115 . Pull level  109  (not shown) is used to pull beam-splitter  107  out of the optical path of illuminator  100  when the microscope is operating in dark-field mode. Finally, processor  160  is connected to the modified microscope of  FIG. 11 . The processor is used to control means for focusing adjustment  1114 , camera  1116 , and light sources  101  and  102  of  FIG. 1A . In addition, said processor analyzes data and creates a 3-D image of the sample. In the preferred embodiment, processor  160  is a personal computer. 
       FIG. 12  illustrates modifications made to a conventional microscope of  FIG. 10  in order to turn it into a 3-D optical microscope in accordance with the present invention. Illuminator  100  is added on the top frame of the conventional microscope of  FIG. 10 . Pull lever  109  is used to pull beam-splitter  107  of  FIG. 1A  out of the optical path of illuminator  100  when the microscope is operating in dark-field mode. Means for focusing adjustment  1214  is implemented either on fine focus knob  1010  or on objective turret  1005  of  FIG. 10 . Some examples of means for focusing adjustment are electrical motor, piezoelectric actuator, and etc. In the preferred embodiment, means for focusing adjustment is a motor coupled to fine focus knob  1010  of  FIG. 10 . It is understood that other means of focusing adjustment is within the scope of the present invention. Coupler  1215  is mounted on trinocular tube  1012  of  FIG. 10  and camera  1216  is attached to coupler  1215 . Finally, processor  160  is connected to the modified microscope of  FIG. 10 . The processor is used to control means for focusing adjustment  1214 , camera  1216 , and light sources  101  and  102  of  FIG. 1A . In addition, said processor analyzes data and creates a 3-D image of the sample. In the preferred embodiment, processor  160  is a personal computer. 
     Operation principles of the 3-D microscopes shown in  FIGS. 9 and 12  are similar to that of  FIG. 1B  while operation principles of the 3-D microscope shown in  FIG. 11  are similar to that of  FIG. 7 . Since we have described the operation principles of the microscopes shown in  FIG. 1B  and  FIG. 7 , we will not repeat the same description here. The key point to remember is that in order to create a 3-D image using the microscopes of  FIG. 1B ,  FIG. 7 ,  FIG. 9 ,  FIG. 11 , and  FIG. 12  in accordance with the present invention involves the aforementioned one-pass image acquisition process of  FIG. 5  and subsequent data analysis process of  FIG. 6 . 
     The modifications of the microscopes of  FIGS. 9 ,  11 , and  12  in accordance with the present invention can be implemented easily and economically on almost all conventional optical microscopes as long as they have a fine focus knob. This is a big advantage over prior art related to confocal microscopy. A confocal microscope is relatively expensive to build. It is not easy and in many cases impossible to turn an existing optical microscope into a confocal microscope. With the present invention, however, an existing optical microscope can be easily turned into a 3-D optical microscope with just a few simple modifications.