초록 ▼

A method for automated image analysis of a biological specimen by histological reconstruction. Also provided is an automated cell image method for analyzing a biological specimen that has consecutively been stained by either an in situ hybridization (ISH) method, or an immunohistochemistry (IHC) met

A method for automated image analysis of a biological specimen by histological reconstruction. Also provided is an automated cell image method for analyzing a biological specimen that has consecutively been stained by either an in situ hybridization (ISH) method, or an immunohistochemistry (IHC) method or a nucleic acid stain, and counterstained. The method couples composite images in an automated manner for processing and analysis. To identify structure in tissue that cannot be captured in a single field of view image or a single staining technique, the disclosure provides a method for histological reconstruction to analyze many fields of view on potentially many slides simultaneously.

대표청구항 ▼

1. A method for automated image analysis of a plurality of biological samples, comprising:(a) providing a plurality of biological samples to be analyzed; (b) automatically scanning the plurality of biological samples at a plurality of different positions with different coordinates; (c) automatically

1. A method for automated image analysis of a plurality of biological samples, comprising:(a) providing a plurality of biological samples to be analyzed; (b) automatically scanning the plurality of biological samples at a plurality of different positions with different coordinates; (c) automatically obtaining an image at each of said different coordinates to produce different images from different locations; (d) automatically reconstructing an image of the plurality of samples from the obtained different images comprising pairing consecutive-corresponding images such that a reconstructed image of the plurality of samples is obtained; and (e) processing the reconstructed image to automatically identify a candidate object or area of interest. 2. The method of claim 1, wherein the reconstructed image is obtained by pairing spatially adjacent and different images of the plurality of samples.3. The method of claim 1, further comprising:(a) automatically identifying a coordinate of the candidate object or area of interest in the reconstructed image; and (b) automatically acquiring a selected image of the object or area of interest, at the location coordinates obtained from the reconstructed image, wherein the selected image includes image information from two different images obtained at two different coordinates during the scanning. 4. The method of claim 1, wherein the candidate object or area of interest is detected by immunohistochemistry.5. The method of claim 1, wherein the candidate object or area of interest is detected by in situ hybridization.6. The method of claim 1, wherein the candidate object or area of interest is detected by a stain.7. The method of claim 6, wherein the stain is a nucleic acid dye selected from the group consisting of hematoxylin, Giemsa stain, methyl green, Nuclear Fast-Red, Hoechst 33342, Hoechst 33258, thiazole orange, DAPI, ethidium bromide, propidium iodide, TOTO, YOYO-1, SYTOX Blue, SYTOX Green, 7-Aminoactinomycin, 9-Amimo-6-chloro-2-methoxyacridine, and acridine homodimer.8. The method of claim 6, wherein the object or area of interest is stained with a cytoplasmic dye including at least one of eosin or Kleihauer-Betke cytochemical stain or a combination thereof.9. The method of claim 1, wherein the candidate object or area of interest is a cell specific marker.10. The method of claim 9 wherein the cell specific marker is detected by a nuclear stain and counterstain.11. The method of claim 9, wherein the cell specific marker is detected by immunohistochemistry, in situ hybridization, staining or a combination thereof.12. The method of claim 1, wherein the reconstructed image is a digital image.13. The method as in claim 1, further comprising:operating an imaging system at a first magnification to obtain a first set of the different images and a first reconstructed image; setting the imaging system at a second magnification greater than the first magnification to obtain a second set of the different images and a second reconstructed image; using the first reconstructed image to identify a target therein; and using the second reconstructed image to extract desired information about the target. 14. A computer program, residing on a computer-readable medium, for automated image analysis of a plurality of biological samples, comprising instructions to cause an automated system to:(a) scan a plurality of biological samples at a plurality of different positions with different coordinates; (b) obtain an image at each of said different coordinates to produce different images from different locations; (d) reconstruct an image of the plurality of samples from the obtained different images comprising pairing consecutive-corresponding images such that a reconstructed image of the plurality of samples is obtained; and (e) process the reconstructed image to automatically identify a candidate object or area of interest. 15. The computer program of claim 14, wherein the reconstructed image of the plurality of sample is a digital image.