Patent ID: 7426290

Claim:
A method for detection and identification of regions of concern of a multi-intensity image, said method comprising the steps of: providing the multi-intensity image; specifying a shape of at least one template for application to the multi-intensity image; designing an outer region of the at least one template to include a number of outer region data points; identifying an inner region of the at least one template as an area encompassed by the outer region; assigning data points for the inner region; estimating a statistical structure of background intensity from the outer region with a tail of a local probability density function using tolerance intervals; constructing a one-sided interval based on an ascending order statistic of the outer region data points such that a probability mass within the interval is less than the tail; estimating a threshold that represents the data points in the outer region for a specified location within the multi-intensity image with the estimated threshold based on the constructed one-sided interval; tessellating the at least one template to additional locations within the multi-intensity image and repeating said statistical structure estimating step, said interval constructing step and said threshold estimation step at each additional location; determining a plurality of threshold-crossing rates that represent the data points within the inner region wherein each threshold-crossing rate is the ratio of data points within the inner region greater than the threshold for each location divided by the area of the inner region; computing a centroid of threshold crossings of the data points of the inner region in relation to the estimated threshold for each location such that false negatives and false positives of the threshold crossing rates are determined; ranking the plurality of threshold-crossing rates in ascending order with the computed centroids corresponding to the plurality of threshold-crossing rates of said ranking such that each rank identifies a region; agglomerating the highest ranked regions as detected regions of concern; and representing the detected regions of concern as a processed image.