Abstract: One embodiment of this invention provides an image processing method for use in locating a landmark in an acquired image. The method comprises a method to sample several features from an image patch, and a decision tree, which performs a regression to the location of the landmark relative to the image patch. The image is scanned by extracting an image patch in many translated locations and for each patch applies the regression decision tree to produce one or more votes for the location of the given target point within the acquired image. The method further accumulates the regression votes for all of the patches in the scan to generate a response image corresponding to the given target point. The method finally performs an estimate of the local maxima of the voting map as the likely locations of the landmark.

Abstract: One embodiment of this invention provides an image processing method for use in locating a landmark in an acquired image. The method comprises a method to sample several features from an image patch, and a decision tree, which performs a regression to the location of the landmark relative to the image patch. The image is scanned by extracting an image patch in many translated locations and for each patch applies the regression decision tree to produce one or more votes for the location of the given target point within the acquired image. The method further accumulates the regression votes for all of the patches in the scan to generate a response image corresponding to the given target point. The method finally performs an estimate of the local maxima of the voting map as the likely locations of the landmark.

Abstract: The present specification discloses a method, system and program product that can be used for self-management of any chronic disease. The invention involves the use of a device to enter patient's disease related data. Based on this data patient's habits are detected and presented in a graphical format. The user also has the option of setting up a reminder based on the detected habits.

Abstract: The invention is a method for estimating a skeletal maturity value of a human from a radiograph of one or more bones in the hand. The borders of the bones are represented by shape points, which are subjected to principal component analysis (PCA). Image intensities are sampled at points located relative to the shape point, and also compressed with PCA. From the features a skeletal maturity value is determined.

Abstract: The invention is a method for estimating a skeletal maturity value of a human from a radiograph of one or more bones in the hand. The borders of the bones are represented by shape points, which are subjected to principal component analysis (PCA). Image intensities are sampled at points located relative to the shape point, and also compressed with PCA. From the features a skeletal maturity value is determined.

Abstract: The present specification discloses a method, system and program product that can be used for self-management of any chronic disease. The invention involves the use of a device to enter patient's disease related data. Based on this data patient's habits are detected and presented in a graphical format. The user also has the option of setting up a reminder based on the detected habits.

Abstract: The invention provides for a method and a drug administration device for enhanced display of data in a modal day format. The method in accordance with the invention provides the user with an option to select one or more data points (430) on the graph and on selection all the corresponding points (to the selected points) are marked (440) giving an insight into the dairys' data.

Abstract: A method for estimating the bone quality or skeletal status of a vertebrate on the basis of two-dimensional image data comprising information relating to the cortical bone of at least a part of a bone of the vertebrate, the image data being data obtained by exposing at least the part of the bone to electromagnetic radiation, the method comprising estimating the bone quality or skeletal status on the basis of a a grey value difference between oblong density variations in the image data and other parts of the image data. These oblong density variations may be caused by osteoporosis, osteopenia or hyperparathyroidism or other bone disorders is called “intra cortical resorption”, “periosteal resorption”, “endosteal resorption”, “striation”, “scalloping”, or “spongiosation”.