Method and apparatus for automated image analysis of biological specimens

Histological reconstruction and automated image analysis

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.

Histological reconstruction and automated image analysis

Automated detection of objects in a biological sample

Histological reconstruction and automated image analysis

Method and apparatus for automated image analysis of biological specimens

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 ...

Method and apparatus for automated image analysis of biological specimens

A method including acquiring images of medical slides at a plurality of different focus positions, determining a position which produces a maximum value of pixel values relative to a pixel value mean, wherein said determining comprises using a pixel value mean as a coarse estimate of coarse focus position, and subsequently refining said coarse focus position to find a fine focus position, and wherein said refining comprises fitting to a polynomial, and using a specified portion of the polynomial as a fine estimate of focus position, and producing a focus control signal that is related to said maximum value to control a focus position.

Automated detection of objects in a biological sample

A method, system, and apparatus are provided for automated light microscopic for detection of proteins associated with cell proliferative disorders.

Method and Apparatus for Automated Image Analysis of Biological Specimens

A method and apparatus for automated cell analysis of biological specimens automatically scans at a low magnification to acquire images 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. The color space converted image is then filtered. The candidate interest pixels are morphologically processed and compared to blob parameters 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.

Method and apparatus for automated image analysis of biological specimens

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 ...

Histological reconstruction and automated image analysis

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.

Automated detection of objects in a biological sample

A method, system, and apparatus are provided for automated light microscopic for detection of proteins associated with cell proliferative disorders.

Automated detection of objects in a biological sample

A method, system, and apparatus are provided for automated light microscopic for detection of proteins associated with cell proliferative disorders.

Method and apparatus for automated image analysis of biological specimens

A method and apparatus for automated cell analysis of biological specimens automatically scans at a low magnification to acquire images 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. The color space converted image is then filtered. The candidate interest pixels are morphologically processed and compared to blob parameters 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.

Histological reconstruction and automated image analysis

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.

Automated Detection of Objects in a Biological Sample

A method, system, and apparatus are provided for automated light microscopic for detection of proteins associated with cell proliferative disorders.

Histological reconstruction and automated image analysis

A method for automated image analysis (Fig. 2, 42) of a biological specimen by histological reconstruction, 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 (Fig. 2, 44) or a single staining technique, the disclosure provides a method for histological reconstruction to analyze many fields of view on potentially many slides (Fig. 2, 37) simultaneously.

Method and apparatus for automated image analysis of biological specimens

A method including acquiring images of medical slides at a plurality of different focus positions, determining a position which produces a maximum value of pixel values relative to a pixel value mean, wherein said determining comprises using a pixel value mean as a coarse estimate of coarse focus position, and subsequently refining said coarse focus position to find a fine focus position, and wherein said refining comprises fitting to a polynomial, and using a specified portion of the polynomial as a fine estimate of focus position, and producing a focus control signal that is related to said maximum value to control a focus position.

Method and apparatus for automated image analysis of biological specimens