Microscope picture processing

Abstract

A microscope image processing method includes applying a computing operation to at least one part of a microscope image, having the following steps: (a) providing the image in the mass storage device, (b) breaking down the microscope image into at least two image segments that can be loaded into the working memory and that have a dimension m, where m≦n, (c) for one image segment, determining all pixels that are located in the image segment and in at least one of the partial images, so that a filled image segment results, (d) providing the filled image segment in the working memory, (e) applying the computing operation to the pixels located in the filled image segment so that an image segment result is created, (f) repeating steps (c), (d), and (e) for all image segments, and (g) combining all image segment results to create an overall result.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

The method is explained in the following using the attached drawings.

FIG. 1 is a schematic depiction of a computer;

FIG. 2 is a schematic depiction of a two-dimensional microscope image;

FIG. 3 a is a schematic depiction of a two-dimensional microscope image that has four partial images and is broken down into nine image segments;

FIG. 3 b is a filled image segment that results from the first image segment of the microscope image in accordance with FIG. 3a;

FIG. 3 c is the filled image segment that results from the second image segment of the microscope image in accordance with FIG. 3a; and,

FIG. 4 is another schematic depiction of a microscope image that comprises four partial images and that is broken down into five image segments that include entire lines of the microscope image; and,

FIGS. 5 and 6 are flowcharts for the inventive method.

DETAILED DESCRIPTION

FIG. 1 schematically depicts a computer 10 that, in addition to a screen 12, has a processor 14 that is connected to a working memory 16 and a mass storage device 18. The working memory 16 has a maximum storage capacity. When the computer 10 is operating, a portion of the maximum storage capacity is required, for instance, for processes of an operating system of the computer 10 so that when the computer 10 is operating the working memory 16 has an available storage capacity that is less than its maximum storage capacity. The available storage capacity of the working memory 16 is available for executing an inventive method.

The mass storage device 18 has a clearly greater storage capacity, for instance greater by a factor of five, than the working memory. The computer 10 can be connected via a network cable (not shown) to a network in order to be able to access mass storage devices of other computers. The computer 10 can be connected to a camera 17 of a microscope 19 via a data link 15. The microscope and the computer 10 then form a microscopy system.

For recording a microscope image, the computer 10 transmits a control impulse via a data cable 21 to a step motor 22, which then moves a positioning unit 23. Affixed to the positioning unit 23 is a specimen 24 that therefore moves relative to the camera 17. When a prespecified position is attained, the computer 10 transmits a control impulse to the camera 17, which then records a partial image of the sample 24. Then another prespecified position is assumed and another partial image is recorded. This procedure is performed until a prespecified number of partial images with prespecified coordinates relative to one another or relative to the specimen 24 have been assumed and partial images have been recorded for each. The recorded partial images are transmitted via the data cable 21 to the computer and are stored there on the mass storage device 18.

FIG. 2 schematically depicts pixels P_i,j of a microscope image 20. The pixels are arranged in a lines, which run horizontally, and b lines, which run vertically and are therefore also called columns. Each pixel P_i,j can be uniquely determined using a first index i (line number) and a second index j (column number). The microscope image 20 therefore has the dimension n=2.

FIG. 3 a schematically depicts a microscope image 20 that comprises four partial images TB₁, where 1=1, 2, 3, 4, that is, four partial images TB₁, TB₂, TB₃, TB₄, that are identified with the solid edges. In FIG. 3a, as well, each pixel P_i,j can be uniquely identified using line and column, that is first index i and second index j. The microscope image 20 has a size that exceeds the available storage capacity of the working memory 16.

For performing the inventive method, the microscope image 20 is first provided in the mass storage device 18. In the present instance this occurs in that the partial images of the microscope image 20 are recorded using the camera 17 of the microscope 19 and are loaded via the data link 15 onto a fixed disk drive as the mass storage device 18.

Then the microscope image is broken down into nine image segments BA₁, BA₂, BA₃, . . . BA₉, the boundaries of which are indicated with broken lines in FIG. 3a. The image segments BA_k are selected in such a way that the desired computing operation can be executed. For instance, if a line-based computing operation is to be executed on the microscope image, the image segments are selected in such a way that they include entire lines, e.g. one line.

The image segments BA_k indicated in FIG. 3a are disjointed and the unification of all image segments BA_k includes all pixels in the microscope image 20 so that the image segments BA_k involve partitioning of the microscope image 20.

Now, first all pixels are determined that are located in one of the image segments, for instance in the first image segment BA₁, and in at least one of the partial images TB₁ through TB₄. In the example depicted in FIG. 3a, there are pixels from the first partial image TB₁ and from the second partial image TB₂ that are located in the image segment BA₁. On the other hand, no pixels from the partial images TB₃ and TB₄ are located in the image segment BA₁. The pixels that are located in the image segment BA₁ and in one of the partial images are depicted schematically in FIG. 3b. These pixels form a first filled image segment and are loaded into the working memory 16. The hash-marked pixels in FIG. 3a are located both in the first partial image TB₁ and in the second partial image TB₂. One of the pixels is selected, in the present case it is the pixel in the first partial image TB₁. The filled image segment therefore does not include all of the pixels in the second partial image TB₂, although the second partial image TB₂ is enclosed by the first image segment BA₁.

The computing operation is applied to the pixels located in the first filled image segment BA₁ so that a first image segment result is created. Then the step of determining all pixels that are located in one of the image segments and in at least one of the partial images is repeated for a next image segment, for instance for the second image segment BA₂. The pixels that are located in the image segment BA₂ and in at least one of the partial images are depicted in FIG. 3c and form a second filled image segment. This second filled image segment is also provided in the working memory 16. Then the computing operation is applied to the pixels located in the second filled image segment so that a second image segment result is created.

These steps are repeated for all of the remaining image segments BA₃ through BA₉ and all of the image segment results are then combined to create an overall result for the entire microscope image 20.

It should be noted that there is no pixel P_i,j that is located in the image segment BA₇ and in one of the partial images. There is therefore no filled image segment for the image segment BA₇ and when the computing operation is applied to this blank pixel quantity there is no result. The overall result is thus not affected.

FIG. 4 depicts the microscope image 20 in which the image segments BA₁ through BA₅ are selected in such a way that they include entire lines of the microscope image. For the image segments selected in this manner the method is also performed as described in the foregoing. The breakdown depicted in FIG. 4 is used when a line-based computing operation is to be applied to the microscope image 20.

FIG. 5 depicts a flowchart for an inventive method as it was described in connection with FIGS. 3a through 3c. First the microscope image that comprises N_TB partial images is provided in the mass storage device. Then the microscope image is broken down or partitioned into N_BA image segments. In an internal loop, the segment quantities are formed with the partial image TB₁ for a solid image segment BA_k. All 1=1, 2, . . . N_TB are run through, that is, the segment quantities of the image segment BA_k are computed with all partial images TB₁.

If all of the partial images TB₁ are run through, the unification quantity of all of these segment quantities is formed. This unification quantity contains all pixels that are contained both in the image segment BA_k and also in one of the partial images TB₁. If a pixel is present in a plurality of partial images, only the pixel of one partial image is used. Alternatively, a mean is calculated from the pixel that is present several times. Then the computing operation is applied to this unification quantity so that an image segment result E_K is created.

In an external loop all image segments BA_k are run through. The index k runs from 1 through N_BA. If all of the image segments BA_k have been run through, the individual image segment results E_k are combined to create an overall result for the image.

A flowchart of another inventive method is depicted in FIG. 6. In a first step (a) the microscope image 20, which comprises N_TB partial images, is provided in the mass storage device. In a further step (a2), at least one area G_p is acquired. This occurs, for instance, in that a user of the computer inputs an area via a graphical user interface, for instance by means of a mouse. A total of N_G areas are acquired.

In a subsequent step (b) the microscope image 20 is broken down or partitioned into N_BA image segments BA_k. In a first internal loop, for a fixed image segment BA_k, for instance the first image segment BA₁, the segment quantity of the 1st partial image TB₁ is formed with this image segment BA_K. After this internal loop has been run through, in a step that is not shown pixels that are available in duplicate are removed, as is described at the top of FIG. 5. Thus the segment quantity of the k^th image segment BA_k is obtained with all partial images, that is, the entirety of all pixels that are located both in the k^th image segment and also in at least one of the partial images. This segment quantity is the filled image segment. The filled image segment for the first image segment BA₁ is schematically depicted in FIG. 3b.

In a subsequent internal loop the segment quantities with the areas G_p are formed for the filled k^th image segment BA_k, in this case then for BA₁, and the computing operation is applied to the segment quantities. FIG. 3b schematically depicts two areas G₁ and G₂. The pixels in the two segment quantities of G₁ and G₂ with the filled image segment of the image segment BA₁ are shown with hash marks.

The computing operation is applied to these pixels with the hash marks. A segment quantity result E_k,p is created. The index p for the area functions as an identification parameter. In a subsequent step, the segment results E_k,p are combined to create an image segment result E_k. The image segment results E_k are then combined to create an overall result for the image. Alternatively, the segment quantity results E_k,p are combined to create area results E_p.

Claims

1. Microscope image processing method for execution on a computer the computer including a working memory having a pre-specified available memory capacity anda mass storage device that has a longer access time than said working memory,for processing a digital microscope image that comprises pixels (Pi,j),is n-dimensional, where n>1,comprises at least two partial images (TB1), and has a size that exceeds the available memory capacity of said working memory,by applying a computing operation to at least one part of said microscope image, comprising:(a) storing said microscope image in said mass storage device,(b) breaking down said microscope image into at least two image segments (BAk) that can be loaded into said working memory and that have a dimension m, where m≦n,(c) for one image segment (BAk), determining all pixels that are located in said image segment (BAk) and in at least one of said partial images (TB1), so that a filled image segment results,(d) storing said filled image segment in said working memory,(e) applying said computing operation to said pixels (Pi,j) located in said filled image segment so that an image segment result is created,(f) repeating steps (c), (d), and (e) for all image segments (BAk), and(g) combining all image segment results to create an overall result.

2. The microscope image processing method in accordance with claim 1, further comprising capturing said microscope image by moving a positioning unit for a microscope in a prespecified grid for recording said microscope images,recording a partial image (TB1) of a specimen affixed to said positioning unit at each grid position with a camera of said microscope, andstoring said partial images (TB1) in said mass storage device of said computer.

3. The microscope image processing method in accordance with claim 1, wherein each image segment (BAk) has an edge with a width of at least one pixel.

4. The microscope image processing method in accordance with claim 1, wherein breaking down said microscope image into at least two image segments (BAk) comprises partitioning said microscope image.

5. The microscope image processing method in accordance with claim 1, wherein n=3.

6. The microscope image processing method in accordance claim 1, wherein m=3.

7. The microscope image processing method in accordance with claim 1, wherein n=2.

8. The microscope image processing method in accordance with claim 1, wherein m=2.

9. The microscope image processing method in accordance with claim 1, wherein said image segments are rectangular.

10. The microscope image processing method in accordance with claim 8, wherein said image segments (BAk) include entire lines of said microscope image.

11. The microscope image processing method in accordance with claim 1, said computing operation further comprising a point operation, a proximity operation, an image transformation, a Fourier transformation or a combination of the foregoing.

12. The microscope image processing method in accordance claim 1, wherein said computing operation includes a calculation based on a measured value.

13. The microscope image processing method in accordance with claim 1, further comprising: assigning an identification parameter (p) for each area (Gp) to each result (Ek,p) of the application of said computing operation to the segment quantity of said image segment with said area (Gp).

14. A microscope that includes a digital mass storage device and a digital working memory, wherein said computer is set up for executing a microscope image processing method in accordance with claim 1.

15. A computer program that can be loaded into a digital working memory of a computer and codes a microscope image processing method in accordance with claim 1.

16. A data carrier on which a computer program in accordance with claim 14 is stored.

17. Microscope image processing method for execution on a computer the computer including a working memory having a pre-specified available memory capacity anda mass storage device that has a longer access time than said working memory,for processing a digital microscope image that comprises pixels (Pi,j),is n-dimensional, where n>1,comprises at least two partial images (TB1), and has a size that exceeds the available memory capacity of said working memory,by applying a computing operation to at least one part of said microscope image, comprising:(a) storing said microscope image in said mass storage device, acquiring at least one area (Gp),(b) breaking down said microscope image into at least two image segments (BAk) that can be loaded into said working memory and that have a dimension m, where m≦n,(c) for one image segment (BAk), determining all pixels that are located in said image segment (BAk) and in at least one of said partial images (TB1), so that a filled image segment results,(c2) for said filled image segment images from a segment quantity comprising pixels and having the at least one area (Gp),(d) storing said filled image segment in said working memory,(e) applying said computing operation to said pixels of said segment quantity so that an image segment result is created, an(f) repeating steps (c), (c2), (d), and (e) for all image segments, and(g) combining all image segment results to create an overall result.

18. The microscope image processing method in accordance with claim 17, further comprising capturing said microscope image bymoving a positioning unit for a microscope in a prespecified grid for recording said microscope images,

19. The microscope image processing method in accordance with claim 17, wherein each image segment (BAk) has an edge with a width of at least one pixel.

20. The microscope image processing method in accordance with claim 17, wherein breaking down said microscope image into at least two image segments (BAk) comprises partitioning said microscope image.

21. The microscope image processing method in accordance with claim 17, wherein n=3.

22. The microscope image processing method in accordance claim 17, wherein m=3.

23. The microscope image processing method in accordance with claim 17, wherein n=2.

24. The microscope image processing method in accordance with claim 17, wherein m=2.

25. The microscope image processing method in accordance with claim 17, wherein said image segments are rectangular.

26. The microscope image processing method in accordance with claim 24, wherein said image segments (BAk) include entire lines of said microscope image.

27. The microscope image processing method in accordance with claim 17, said computing operation further comprising a point operation, a proximity operation, an image transformation, a Fourier transformation or a combination of the foregoing.

28. The microscope image processing method in accordance claim 17, wherein said computing operation includes a calculation based on a measured value.

29. The microscope image processing method in accordance with claim 17, further comprising: assigning an identification parameter (p) for each area (Gp) to each result (Ek,p) of the application of said computing operation to the segment quantity of said image segment with said area (Gp).

30. A microscope that includes a digital mass storage device and a digital working memory, wherein said computer is set up for executing a microscope image processing method in accordance with claim 17.

31. A computer program that can be loaded into a digital working memory of a computer and codes a microscope image processing method in accordance with claim 17.

32. A data carrier on which a computer program in accordance with claim 17 is stored.

33. Microscope image processing method for execution on a computer the computer including a working memory having a pre-specified available memory capacity anda mass storage device that has a longer access time than said working memory,for processing a digital microscope image that comprises pixels (Pi,j),is n-dimensional, where n>1,comprises at least two partial images (TB1), and has a size that exceeds the available memory capacity of said working memory,by applying a computing operation to at least one part of said microscope image, comprising:(a) storing said microscope image in said mass storage device,(a2) acquiring at least one area (Gp),(b) breaking down at least one area (Gp) into at least two image segments that can be loaded into said working memory (16) and have a dimension m, where m≦n,(c) for one image segment (BAk), determining all pixels that are located in said image segment (BAk) and in at least one of said partial images (TB1), so that a filled image segment results,(d) storing said filled image segment in said working memory,(e) applying said computing operation to said pixels (Pi,j) located in said filled image segment so that an image segment result is created,(f) repeating steps (c), (d), and (e) for all image segments (BAk), and(g) combining all image segment results to create an overall result for said area (Gp).

34. The microscope image processing method in accordance with claim 33, further comprising capturing said microscope image bymoving a positioning unit for a microscope in a prespecified grid for recording said microscope images,recording a partial image (TB1) of a specimen affixed to said positioning unit at each grid position with a camera of said microscope, andstoring said partial images (TB1) in said mass storage device of said computer.

35. The microscope image processing method in accordance with claim 33, wherein each image segment (BAk) has an edge with a width of at least one pixel.

36. The microscope image processing method in accordance with claim 33, wherein breaking down said microscope image into at least two image segments (BAk) comprises partitioning said microscope image.

37. The microscope image processing method in accordance with claim 33, wherein n=3.

38. The microscope image processing method in accordance claim 33, wherein m=3.

39. The microscope image processing method in accordance with claim 33, wherein n=2.

40. The microscope image processing method in accordance with claim 33, wherein m=2.

41. The microscope image processing method in accordance with claim 33, wherein said image segments are rectangular.

42. The microscope image processing method in accordance with claim 40, wherein said image segments (BAk) include entire lines of said microscope image.

43. The microscope image processing method in accordance with claim 33, said computing operation further comprising a point operation, a proximity operation, an image transformation, a Fourier transformation or a combination of the foregoing.

44. The microscope image processing method in accordance claim 33, wherein said computing operation includes a calculation based on a measured value.

45. The microscope image processing method in accordance with claim 33, further comprising: assigning an identification parameter (p) for each area (Gp) to each result (Ek,p) of the application of said computing operation to the segment quantity of said image segment with said area (Gp).

46. A microscope that includes a digital mass storage device and a digital working memory, wherein said computer is set up for executing a microscope image processing method in accordance with claim 33.

47. A computer program that can be loaded into a digital working memory of a computer and codes a microscope image processing method in accordance with claim 33.

48. A data carrier on which a computer program in accordance with claim 33 is stored.