Method and apparatus for automated detection of masses in digital images

A method of detecting masses in a digital mammogram, comprising the steps of:

• computing a gradient plane from said digital mammogram, said gradient plane comprising pixels, each pixel having gradient magnitude and gradient direction information;
• selecting a set of candidate pixels in digital mammogram image;
• for each candidate pixel, computing a first density metric based on a first set of surrounding pixels having gradient magnitudes above a first threshold and having gradient directions pointing generally toward said candidate pixel;
• and
• evaluating said first density metrics for determining the locations of masses in said digital mammogram.

A method of detecting masses in a digital mammogram, comprising the steps of:

• computing a gradient plane from said digital mammogram, said gradient plane comprising pixels, each pixel having gradient magnitude and gradient direction information;
• selecting a set of candidate pixels in said gradient plane, said candidate pixels being denoted by an index icand;
• for each candidate pixel icand, computing a first density metric G1icand according to the steps of:
• selecting a neighborhood of pixels NHicand around said candidate pixel;
• selecting a small region Ricand around said candidate pixel;
• selecting a first set of pixels in said neighborhood NHicand having gradient directions pointing toward said small region Ricand and having a gradient magnitude greater than a predetermined lower threshold, said first set of pixels being denoted by the counter variable jpoint;
• and
• counting the number of pixels in said first set, wherein said first density metric G1icand is proportional to the number of pixels in said first set;
• for each candidate pixel icand, computing a second density metric G2icand according to the steps of:
• selecting K spatial bins (icand,k) extending radially from said candidate pixel and being arranged in a radially symmetric manner around said candidate pixel;
• for each pixel (icand,jpoint) of said first set of pixels, identifying the spatial bin (icand,k) in which said pixel (icand,jpoint) is located;
• and
• computing a number of pixels nicand,k in each spatial bin (icand,k), wherein said second density metric G2icand is based on the statistical distribution of the number nicand,k as k is varied;
• and
• evaluating said first and second density metrics G1icand and G2icand according to a linear classifier method for determining the locations of masses in said digital mammogram.