Fast 3D cytometry for information in tissue engineering

• US 20030184730A1
• Filed: 01/23/2003
• Published: 10/02/2003
• Est. Priority Date: 01/23/2002
• Status: Active Grant

• Current Assignee: Regents of the University of California (University of California)
• Original Assignee: Regents of the University of California (University of California)
• Inventors: Price, Jeffrey H.
• Granted Patent: US 7,756,305 B2
• Time in Patent Office: Days
• US Class Current: 356/39
• CPC Class Codes: G01N 15/01 specially adapted for biological cells, e.g. blood cells investigating sedimentation of particle suspensions in blood G01N15/05
• CPC Class Codes: G01N 15/1433 using image recognition
• CPC Class Codes: G01N 15/1475 using image analysis for extracting features of the particle
• CPC Class Codes: G01N 2015/0065 biological, e.g. blood
• CPC Class Codes: G01N 21/6458 Fluorescence microscopy fluorescence microscopes per se G02B21/0076 and G02B21/16
• CPC Class Codes: G02B 21/367 providing an output produced by processing a plurality of individual source images, e.g. image tiling, montage, composite images, depth sectioning, image comparison
• CPC Class Codes: G06T 5/004 Unsharp masking
• CPC Class Codes: G06T 5/50 using two or more images, e.g. averaging or subtraction
• CPC Class Codes: G06T 5/75 Unsharp masking
• CPC Class Codes: Y10S 128/922 including image analysis

Abstract

Methods and apparatus are described for enhancing operator independent image cytometry. Aspects of the invention include enhanced tissue surface tracking which can detect both tissue surfaces. The surface detection can aid cytometry, such as by reducing the amount of image data to be stored. Segmentation is described for 3D images in which 3D least squares filtering is applied to increase contrast for simplifying the delineation of objects from backgrounds. A method of creating 3D FIR image filters based on ideal objects is also described. A data structure is defined by which 3D object data may be organized for image representations if samples. Methods of performing remote segmentation processing are also described toward centralizing the necessary processor power and applications and reducing the burden on researchers and clinicians.

Claims

1. A method of controlling the autofocusing of a microscope having a focus mechanism, comprising:

(a) establishing an initial focal range for volume scanning of a sample by a microscope;

(b) detecting a surface of said sample in response to registered optical characteristics; and

(c) mapping of images from a set of optical planes in response to the location of said surface of said sample.

2. A method as recited in claim 1, wherein registered optical characteristics may be in response to optical energy that is reflected from, transmitted through, or the fluorescence from, said sample.

3. A method as recited in claim 1, wherein said sample comprises a cellular tissue sample.

4. A method as recited in claim 1, wherein said surface comprises an upper surface of said sample.

5. A method as recited in claim 1, wherein said surface comprises a lower surface of said sample.

6. A method as recited in claim 1, wherein said surface comprises both an upper and lower surface of said sample.

7. A method as recited in claim 1, wherein said reflected optical characteristics comprises the optical power of high spatial frequency components.

8. A method of distinguishing a 3D object from a background, comprising:

(a) recording a 3D image of a sample volume;

(b) enhancing object to background contrast ratios for said 3D image;

(c) thresholding said 3D image to delineate object boundaries; and

(d) generating information about said delineated said 3D objects.

9. A method as recited in claim 8, wherein said generation of said information comprises rendering surfaces of objects based on said object boundaries.

10. A method as recited in claim 8, wherein said generation of said information comprises generating quantitative information about objects based on said object boundaries.

11. A method as recited in claim 8, wherein said thresholding is performed in response to analyzing confocal volumes.

12. A method as recited in claim 8, wherein said thresholding was performed by selecting a minimum after the largest background intensity peak.

13. A method as recited in claim 12, wherein said minimum comprises a first minimum.

14. A method as recited in claim 8, wherein said enhancing object to background contrast is performed utilizing image filters.

15. A method as recited in claim 14, wherein said image filters comprise finite impulse response (FIR) filters.

16. A method as recited in claim 15, wherein said image filters are created based upon ideal image sections collected from a 3D object.

17. A method of remote segmentation of cytometry image data sets, comprising:

(a) establishing communication with a remote server configured for receiving cytometry image data sets;

(b) establishing a designated recipient for segmentation information;

(c) transmitting an image data set to said remote server;

(d) receiving said image data set by said server;

(e) generating segmentation output data in response to segmenting of said image data set; and

(f) transmitting segmentation output data to said designated recipient.

18. A method as recited in claim 17, further comprising logging in to said remote server after establishing communication.

19. A method as recited in claim 18, wherein said logging in comprises identifying the organization or individual from which said image data set has originated.

20. A method as recited in claim 18, wherein said logging in comprises specifying what information is to be returned based on the processing of said image data set.

21. A method as recited in claim 18, wherein said logging in comprises identifying the destination for the information to be returned for said image data set.

22. A method as recited in claim 17, further comprising the storage of said image data set upon receipt within said server.

23. A method as recited in claim 17, further comprising the storage of said image data set into electronic storage media accessible to said server.

24. A method as recited in claim 17, further comprising passing said image data set to a computer configured for performing image segmentation.

25. A method as recited in claim 24, wherein said computer configured for performing image segmentation comprises a computer system capable of performing multiprocessing.

26. A method as recited in claim 24, wherein said computer configured for performing image segmentation comprises multiple digital signal processors working in combination.

27. A method as recited in claim 17, further comprising executing a monetary transaction in response to the remote segmentation services performed.

28. A method as recited in claim 27, wherein the amount of said monetary transaction is based on the computational resources utilized for performing said segmentation on said image data set.

29. A method as recited in claim 28, wherein the amount of said monetary transaction is based on the type of information being generated during said segmentation on said image data set.

30. A method of limiting image storage to objects within a cellular tissue sample imaged with microscope, comprising:

(a) establishing an initial focal range for volume scanning of a sample by a microscope;

(b) detecting a surface of said sample in response to registered optical characteristics; and

(c) selecting images for storage that lie within said cellular tissue sample as determined in response to the positional relationship of the positions of said images with said detected surface.

31. A method of controlling the autofocusing of a microscope having a focus mechanism, comprising:

(a) establishing an initial focal range for volume scanning of a tissue sample by a microscope;

(b) detecting an upper or lower surface of said sample in response to the power of high spatial frequency components; and

(c) mapping of images from a set of optical planes in response to the location of said surface of said sample.

32. A method of distinguishing a 3D object from a background, comprising:

(a) recording a 3D image of a sample volume;

(b) enhancing object to background contrast ratios for said 3D image by applying least squares finite impulse response (FIR) filters;

(c) thresholding said 3D image in response to confocal volumes to delineate object boundaries; and

(d) generating information about said delineated said 3D objects enhancing object to background contrast is performed utilizing image filters.

33. A method of collecting 3D images a sample volume, comprising:

(a) establishing an initial focal range for volume scanning of a sample by a microscope;

(b) detecting a surface of said sample in response to registered optical characteristics;

(c) recording of images from a set of optical planes in response to the location of said surface of said sample;

(d) enhancing object to background contrast ratios for said 3D image;

(e) thresholding said 3D image to delineate object boundaries; and

(f) generating information about said delineated said 3D objects.

34. A method of collecting 3D images a sample cellular tissue volume, comprising:

(a) establishing an initial focal range for volume scanning of a cellular tissue sample by a microscope;

(b) detecting a top or bottom surface of said sample in response to power of high spatial frequency components;

(c) recording of images from a set of optical planes in response to the location of said surface of said cellular tissue sample;

(d) enhancing object to background contrast ratios for said 3D image by applying least squares finite impulse response (FIR) filters;

(e) thresholding said 3D image in response to confocal volumes to delineate object boundaries; and

(f) generating information about said delineated 3D objects within said cellular tissue sample.

35. An apparatus for controlling the autofocusing of a microscope having a focus mechanism, comprising:

a computer configured for controlling a microscope from which 3D imaging data is to be received; and

programming associated with said computer for,

establishing an initial focal range for volume scanning of a tissue sample by a microscope,

detecting an upper or lower surface of said sample in response to the power of high spatial frequency components,

mapping of images from a set of optical planes in response to the location of said surface of said sample.

36. An apparatus for limiting image storage to objects within a cellular tissue sample imaged with microscope, comprising:

a computer configured for controlling a microscope from which 3D imaging data is to be received; and

programming associated with said computer for,

establishing an initial focal range for volume scanning of a sample by a microscope,

detecting a surface of said sample in response to registered optical characteristics,

selecting images for storage that lie within said cellular tissue sample as determined in response to the positional relationship of the positions of said images with said detected surface.

37. An apparatus for performing image segmentation of 3D sample volumes from a microscope, comprising:

a computer configured for receiving 3D imaging data from a microscope;

programming associated with said computer for,

enhancing object to background contrast ratios for said 3D image by applying least squares finite impulse response (FIR) filters,

thresholding said 3D image in response to confocal volumes to delineate object boundaries,

generating information about said delineated said 3D objects.

38. An apparatus for collecting 3D images a sample cellular tissue volumes, comprising:

a computer configured for controlling a microscope from which 3D imaging data is to be received; and

programming associated with said computer for,

establishing an initial focal range for volume scanning of a tissue sample by a microscope,

detecting an upper or lower surface of said sample in response to the power of high spatial frequency components,

collecting of 3D images from a set of optical planes in response to the location of said surface of said sample as images by said microscope,

enhancing object to background contrast ratios for said 3D image by applying least squares finite impulse response (FIR) filters,

thresholding said 3D image in response to confocal volumes to delineate object boundaries,

generating information about said delineated said 3D objects.

39. An apparatus for performing segmentation for 3D cytometry image data sets of sample cellular tissue volumes which were collected remotely, comprising:

a computer configured for receiving 3D imaging data sets obtained from a microscope imaging a cellular tissue sample; and

programming associated with said computer for,

establishing communication with a remote server configured for receiving cytometry image data sets,

establishing a designated recipient for segmentation information,

transmitting an image data set to said remote server,

receiving said image data set by said server,

generating segmentation output data in response to segmenting of said image data set,

transmitting segmentation output data to said designated recipient.