1. A method of computerized detection of clustered microcalcifications in a digital mammogram derived from an original radiographic image, comprising: producing a multi-pixel difference image of said digital mammogram to remove low-frequency structured anatomic background; performing a global gray-level thresholding of said difference image to produce a global thresholded image, including producing a histogram of the difference image, setting a global threshold based on a pre-selected percentage of pixels at the high end of the histogram, retaining unchanged in said difference image those pixels having a value above said global threshold, and setting to a predetermined constant the values of those pixels in the difference image which have a value below said global threshold; performing area filtering by means of morphological erosion on the image data resulting after global thresholding thereby to produce an area filtered image in which small signals are selectively removed; and processing said area filtered image in which small signals are selectively removed to identify microcalcifications; wherein said step of performing area filtering comprises: defining plural structuring elements each having a size of at least two pixels, sequentially defining each pixel in the image after global thresholding as an operating pixel and sequentially overlaying each operating pixel with each structuring element; determining, for each operating pixel sequentially overlaid by each structuring element, the minimum pixel value of the pixels overlaid by each structuring element in relation to the same operating pixel; determining the maximum of the minimum pixel values determined in relation to the same operating pixel; and setting the value of each pixel in the output area-filtered image corresponding to the position of the operating pixel in the global thresholded image to the respective maximum of said minimum values determined in the preceding step.
1. A method of computerized detection of clustered microcalcifications in a digital mammogram derived from an original radiographic image, comprising: producing a multi-pixel difference image of said digital mammogram to remove low-frequency structured anatomic background; performing a global gray-level thresholding of said difference image to produce a global thresholded image, including producing a histogram of the difference image, setting a global threshold based on a pre-selected percentage of pixels at the high end of the histogram, retaining unchanged in said difference image those pixels having a value above said global threshold, and setting to a predetermined constant the values of those pixels in the difference image which have a value below said global threshold; performing area filtering by means of morphological erosion on the image data resulting after global thresholding thereby to produce an area filtered image in which small signals are selectively removed; and processing said area filtered image in which small signals are selectively removed to identify microcalcifications; wherein said step of performing area filtering comprises: defining plural structuring elements each having a size of at least two pixels, sequentially defining each pixel in the image after global thresholding as an operating pixel and sequentially overlaying each operating pixel with each structuring element; determining, for each operating pixel sequentially overlaid by each structuring element, the minimum pixel value of the pixels overlaid by each structuring element in relation to the same operating pixel; determining the maximum of the minimum pixel values determined in relation to the same operating pixel; and setting the value of each pixel in the output area-filtered image corresponding to the position of the operating pixel in the global thresholded image to the respective maximum of said minimum values determined in the preceding step. 2. The method according to claim 1, wherein said step of processing said area filtered image comprises: performing local gray-level thresholding on the area filtered image to produce a threshold image in which pixels having a value below a local threshold are set to a uniform background value and pixels having values above the local threshold retain their values; performing texture discrimination on the threshold image by removing background trend therefrom and setting to a predetermined value those pixels having a first moment of power spectrum greater than a predetermined value thereby to produce a texture discriminated image; performing cluster filtering of the texture discriminated image to produce a cluster image of single-pixel signals identifying locations of potential microcalcifications; extracting predetermined features from locations in the digital mammogram identified in said cluster filtering step; and identifying microcalcifications based on the features extracted in said extracting step.