Abstract: A method and system for morphology based mitosis identification and classification of digital images. Luminance parameters such as intensity, etc. from a digital image of a biological sample (e.g., tissue cells) to which a chemical compound (e.g., a marker dye) has been applied are analyzed and corrected if necessary. Morphological parameters (e.g., size, elongation ratio, parallelism, boundary roughness, convex hull shape, etc.) from individual components within the biological sample are analyzed. A medical conclusion (e.g., type and count of mitotic cells) or a life science and biotechnology experiment conclusion is determined from the analyzed luminance and morphological parameters. The method and system may be used to develop applications for automatically obtaining a medical diagnosis (e.g., a carcinoma diagnosis).

Abstract: A method and system for morphology based mitosis identification and classification of digital images. Luminance parameters such as intensity, etc. from a digital image of a biological sample (e.g., tissue cells) to which a chemical compound (e.g., a marker dye) has been applied are analyzed and corrected if necessary. Morphological parameters (e.g., size, elongation ratio, parallelism, boundary roughness, convex hull shape, etc.) from individual components within the biological sample are analyzed. A medical conclusion (e.g., type and count of mitotic cells) or a life science and biotechnology experiment conclusion is determined from the analyzed luminance and morphological parameters. The method and system may be used to develop applications for automatically obtaining a medical diagnosis (e.g., a carcinoma diagnosis).

Abstract: A method and system for automated digital fluorescent in situ hybridization (FISH) image analysis. Luminance parameters from a digital image of a biological tissue sample to which a fluorescent compound (e.g., LSI-HER-2/neu and CEP-17 dyes) have been applied are analyzed to determine plural regions of interest. Fluorescent color signals in the plural regions of interest including plural cell nuclei are identified, classified and grouped into plural groups. Each of the plural groups is validated based on pre-defined conditions. A medical diagnosis or prognosis or medical, life science or biotechnology experiment conclusion determined using a count of plural ratios of validated fluorescent color signals within each of the cell nuclei within the plural groups.

Abstract: A method and system for automatically determining diagnostic saliency of digital images for medical and/or pathological purposes. Luminance parameters (e.g. intensity, etc.) from a digital image of a biological sample (e.g., tissue cells) to which a chemical compound (e.g., a marker dye) has been applied are automatically analyzed and automatically corrected if necessary. Morphological parameters (e.g., cell membrane, cell nucleus, mitotic cells, etc.) from individual components within the biological sample are automatically analyzed on the digital image. A medical conclusion (e.g., a medical diagnosis or prognosis) is automatically determined from the analyzed luminance and morphological parameters.