This paper presents a method for associating regions of sequential
mammograms automatically using graph matching. The graph matching
utilises relative spatial relationships between the regions of a
mammogram to establish regional correspondences between two
mammograms. As a first step of the method, the mammogram is
segmented into separate regions using an adaptive pyramid
segmentation algorithm. This process produces both segmented
regions of the mammogram and a graph. The nodes of the graph
represent the segmented regions, and the lines represent the
relationships between the regions. The regions are then filtered
to remove undesired regions. To express the spatial relations
between the regions, we use a fuzzy logic expression, which takes
into account the characteristics of each region including the
shape, size and orientation. The spatial relations between regions
are utilised as weights of the graph. The backtrack algorithm is
then used to find the common subgraph between two graphs. The
proposed method is applied to 95 temporal pairs of mammograms. For
each temporal mammogram pair, an average of 13.2 regions are
matched. All region matches are classified as "good", "average",
"poor" and "unknown" by one of the authors (FM) based on visual
perception. 63.5% of region matches are identified as "good",
and 23.6% as "average". The percentages of "poor" and
"unknown" are 10.9% and 2% respectively. These results
indicate that our registration method may be useful for
establishing regional correspondence between sequential
mammograms.
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