Abstract: A method and apparatus for automated cell analysis of biological specimens automatically scans at a low magnification to acquire images (288) which are analyzed to determine candidate cell objects of interest. The low magnification images are converted from a first color space to a second color space (290). The color space converted image is then low pass filtered (292) and compared to a threshold (294) to remove artifacts and background objects from the candidate object of interest pixels of the color converted image. The candidate object of interest pixels are morphologically processed (296) to group candidate object of interest pixels together into groups which are compared to blob parameters (298) to identify candidate objects of interest which correspond to cells or other structures relevant to medical diagnosis of the biological specimen. The location coordinates of the objects of interest are stored and additional images of the candidate cell objects are acquired at high magnification.

Abstract: 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.

Abstract: A method and apparatus for automated cell analysis of biological specimens automatically scans at a low magnification to acquire images (288) which are analyzed to determine candidate cell objects of interest. The low magnification images are converted from a first color space to a second color space (290). The color space converted image is then low pass filtered (292) and compared to a threshold (294) to remove artifacts and background objects from the candidate object of interest pixels of the color converted image. The candidate object of interest pixels are morphologically processed (296) to group candidate object of interest pixels together into groups which are compared to blob parameters (298) to identify candidate objects of interest which correspond to cells or other structures relevant to medical diagnosis of the biological specimen. The location coordinates of the objects of interest are stored and additional images of the candidate cell objects are acquired at high magnification.

Abstract: 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.

Abstract: A method and apparatus for automated cell analysis of biological specimens automatically scans at a low magnification to acquire images (288) which are analyzed to determine candidate cell objects of interest. The low magnification images are converted from a first color space to a second color space (290). The color space converted image is then low pass filtered (292) and compared to a threshold (294) to remove artifacts and background objects from the candidate object of interest pixels of the color converted image. The candidate object of interest pixels are morphologically processed (296) to group candidate object of interest pixels together into groups which are compared to blob parameters (298) to identify candidate objects of interest which correspond to cells or other structures relevant to medical diagnosis of the biological specimen. The location coordinates of the objects of interest are stored and additional images of the candidate cell objects are acquired at high magnification.

Abstract: 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.

Abstract: 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.

Abstract: 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.