Abstract: An analysis system automatically analyzes and counts fluorescence signals present in biopsy tissue marked using Fluorescence in situ Hybridization (FISH). The user of the system specifies classes of a class network and process steps of a process hierarchy. Then pixel values in image slices of biopsy tissue are acquired in three dimensions. A computer-implemented network structure is generated by linking pixel values to objects of a data network according to the class network and process hierarchy. Objects associated with pixel values at different depths of the biopsy tissue are used to determine the number, volume and distance between cell components. In one application, fluorescence signals that mark Her2/neural genes and centromeres of chromosome seventeen are counted to diagnose breast cancer. Her2/neural genes that overlap one another or that are covered by centromeres can be accurately counted. Signal artifacts that do not mark genes can be identified by their excessive volume.

Abstract: An analysis system automatically analyzes and counts fluorescence signals present in biopsy tissue marked using Fluorescence in situ Hybridization (FISH). The user of the system specifies classes of a class network and process steps of a process hierarchy. Then pixel values in image slices of biopsy tissue are acquired in three dimensions. A computer-implemented network structure is generated by linking pixel values to objects of a data network according to the class network and process hierarchy. Objects associated with pixel values at different depths of the biopsy tissue are used to determine the number, volume and distance between cell components. In one application, fluorescence signals that mark Her2/neural genes and centromeres of chromosome seventeen are counted to diagnose breast cancer. Her2/neural genes that overlap one another or that are covered by centromeres can be accurately counted. Signal artifacts that do not mark genes can be identified by their excessive volume.

Abstract: An analysis system automatically analyzes and counts fluorescence signals present in biopsy tissue marked using Fluorescence in situ Hybridization (FISH). The user of the system specifies classes of a class network and process steps of a process hierarchy. Then pixel values in image slices of biopsy tissue are acquired in three dimensions. A computer-implemented network structure is generated by linking pixel values to objects of a data network according to the class network and process hierarchy. Objects associated with pixel values at different depths of the biopsy tissue are used to determine the number, volume and distance between cell components. In one application, fluorescence signals that mark Her2/neural genes and centromeres of chromosome seventeen are counted to diagnose breast cancer. Her2/neural genes that overlap one another or that are covered by centromeres can be accurately counted. Signal artifacts that do not mark genes can be identified by their excessive volume.

Abstract: An analysis system automatically analyzes and counts fluorescence signals present in biopsy tissue marked using Fluorescence in situ Hybridization (FISH). The user of the system specifies classes of a class network and process steps of a process hierarchy. Then pixel values in image slices of biopsy tissue are acquired in three dimensions. A computer-implemented network structure is generated by linking pixel values to objects of a data network according to the class network and process hierarchy. Objects associated with pixel values at different depths of the biopsy tissue are used to determine the number, volume and distance between cell components. In one application, fluorescence signals that mark Her2/neural genes and centromeres of chromosome seventeen are counted to diagnose breast cancer. Her2/neural genes that overlap one another or that are covered by centromeres can be accurately counted. Signal artifacts that do not mark genes can be identified by their excessive volume.

Abstract: An analysis system automatically analyzes and counts fluorescence signals present in biopsy tissue marked using Fluorescence in situ Hybridization (FISH). The user of the system specifies classes of a class network and process steps of a process hierarchy. Then pixel values in image slices of biopsy tissue are acquired in three dimensions. A computer-implemented network structure is generated by linking pixel values to objects of a data network according to the class network and process hierarchy. Objects associated with pixel values at different depths of the biopsy tissue are used to determine the number, volume and distance between cell components. In one application, fluorescence signals that mark Her2/neural genes and centromeres of chromosome seventeen are counted to diagnose breast cancer. Her2/neural genes that overlap one another or that are covered by centromeres can be accurately counted. Signal artifacts that do not mark genes can be identified by their excessive volume.