Abstract: Systems and methods for automated stereology are provided. A method can include providing an imager for capturing a Z-stack of images of a three-dimensional (3D) object; constructing extended depth of field (EDF) images from the Z-stack of images; performing a segmentation method on the EDF images including estimating a Gaussian Mixture Model (GMM), performing morphological operations, performing watershed segmentation, constructing Voronoi diagrams and performing boundary smoothing; and determining one or more stereology parameters such as number of cells in a region.

Abstract: Systems and methods for automated stereology are provided. A method can include providing an imager for capturing a Z-stack of images of a three-dimensional (3D) object; constructing extended depth of field (EDF) images from the Z-stack of images; performing a segmentation method on the EDF images including estimating a Gaussian Mixture Model (GMM), performing morphological operations, performing watershed segmentation, constructing Voronoi diagrams and performing boundary smoothing; and determining one or more stereology parameters such as number of cells in a region.

Abstract: Systems and methods for applying an ensemble of segmentations to microscopy images of a tissue sample to determine if the tissue sample is representative of cancerous tissue. The ensemble of segmentations is applied to a plurality of greyscale or color microscopy images to generate a final image level segmentation and a final blob level segmentation. The final image level segmentation and final blob level segmentation are used to calculate a mean nuclear volume to determine if the tissue sample is representative of cancerous tissue.

Abstract: This invention relates to a system and method for applying an ensemble of segmentations to microscopy images of a tissue sample to determine if the tissue sample is representative of cancerous tissue. The ensemble of segmentations is applied to a plurality of greyscale or color microscopy images to generate a final image level segmentation and a final blob level segmentation. The final image level segmentation and final blob level segmentation are used to calculate a mean nuclear volume to determine if the tissue sample is representative of cancerous tissue.

Abstract: Systems and methods are provided for automatic determination of slice thickness of an image stack in a computerized stereology system, as well as automatic quantification of biological objects of interest within an identified slice of the image stack. Top and bottom boundaries of a slice can be identified by applying a thresholded focus function to determine just-out-of-focus focal planes. Objects within an identified slice can be quantified by performing a color processing segmentation followed by a gray-level processing segmentation. The two segmentation processes generate unique identifiers for features in an image that can then be used to produce a count of the features.

Abstract: Systems and methods are provided for automatic determination of slice thickness of an image stack in a computerized stereology system, as well as automatic quantification of biological objects of interest within an identified slice of the image stack. Top and bottom boundaries of a slice can be identified by applying a thresholded focus function to determine just-out-of-focus focal planes. Objects within an identified slice can be quantified by performing a color processing segmentation followed by a gray-level processing segmentation. The two segmentation processes generate unique identifiers for features in an image that can then be used to produce a count of the features.