Abstract: A navigation system, apparatus and method utilizing a processor and a sensor, operatively coupled to the processor to determine a location of the navigation system. A navigation input module is configured to receive destination data specifying a destination and a plurality of point-of-interest (POI) data from a user, where the navigation input module is further configured to receive a POI search area value defining an area of search for the POI data from potential route segments. The processor may utilize the POI search area value to search a plurality of areas along the potential route segments to identify at least some of the plurality of POI data that are in closest proximity to the destination, and wherein the processor may be further configured to cluster the identified POI data for simultaneous presentation on a navigational map.

Abstract: A navigation system, apparatus and method utilizing a processor and a sensor, operatively coupled to the processor to determine a location of the navigation system. A navigation input module is configured to receive destination data specifying a destination and a plurality of point-of-interest (POI) data from a user, where the navigation input module is further configured to receive a POI search area value defining an area of search for the POI data from potential route segments. The processor may utilize the POI search area value to search a plurality of areas along the potential route segments to identify at least some of the plurality of POI data that are in closest proximity to the destination, and wherein the processor may be further configured to cluster the identified POI data for simultaneous presentation on a navigational map.

Abstract: Methods, code and apparatus analyze cell images to automatically identify and characterize the Golgi complex in individual cells. This is accomplished by first locating the cells in the image and defining boundaries of those cells that subsume some or all of the Golgi complex of those cells. The Golgi complex in the images typically have intensity values corresponding to the concentration of a Golgi component in the cell (e.g. a polysaccharide associated with the Golgi complex). The method/system then analyzes the Golgi components of the image (typically on a pixel-by-pixel basis) to mathematically characterize the Golgi complex of individual cells. This mathematical characterization represents phenotypic information about the cells' Golgi complex and can be used to classify cells. From this information, mechanism of action and other important biological information can be deduced.

Abstract: Methods, code and apparatus analyze cell images to automatically identify and characterize the Golgi complex in individual cells. This is accomplished by first locating the cells in the image and defining boundaries of those cells that subsume some or all of the Golgi complex of those cells. The Golgi complex in the images typically have intensity values corresponding to the concentration of a Golgi component in the cell (e.g. a polysaccharide associated with the Golgi complex). The method/system then analyzes the Golgi components of the image (typically on a pixel-by-pixel basis) to mathematically characterize the Golgi complex of individual cells. This mathematical characterization represents phenotypic information about the cells' Golgi complex and can be used to classify cells. From this information, mechanism of action and other important biological information can be deduced.

Abstract: Methods, code and apparatus analyze cell images to automatically identify and characterize the Golgi complex in individual cells. This is accomplished by first locating the cells in the image and defining boundaries of those cells that subsume some or all of the Golgi complex of those cells. The Golgi complex in the images typically have intensity values corresponding to the concentration of a Golgi component in the cell (e.g. a polysaccharide associated with the Golgi complex). The method/system then analyzes the Golgi components of the image (typically on a pixel-by-pixel basis) to mathematically characterize the Golgi complex of individual cells. This mathematical characterization represents phenotypic information about the cells' Golgi complex and can be used to classify cells. From this information, mechanism of action and other important biological information can be deduced.