A mammogram contains two distinctive regions: the exposed breast region and the unexposed air-background region. The background region often contains radiopaque artifacts in the form of identification labels, radiopaque markers, and wedges. The primary motivation for removing such artifacts from mammograms is too lessen their effect on subsequent processing algorithms. For example, accurate segmentation of the breast region is an important pre-processing step in the computerized analysis of mammograms. It allows the search for abnormalities to be limited to the breast region of the mammogram without undue influence from the background. One of the problems with precise segmentation of the breast region is that high-intensity radiopaque artifacts can result in a non-uniform background region, and interfere with deriving an accurate representation of the breast contour. This paper proposes a new approach for removing radiopaque artifacts from the background region of mammograms based on the concept of area morphology. Area morphology uses attributes of structures rather than a fixed shape structuring element as used in classical morphology. This allows radiopaque artifacts to be removed, irrespective of shape.
The process of contrast enhancement refers to the accentuation, or sharpening of image structures to allow for improved
image analysis and interpretation. A mammogram is a x-ray projection of the 3D structures of the breast obtained by
compressing the breast between two plates. Unlike most other x-ray or Computed Tomography images, mammograms
have an inherent "fuzzy" or diffuse appearance. This is due in part to the superimposition of densities from differing
breast tissues, and the differential x-ray attenuation (absorption) characteristics associated with these various tissues.
Much of the difficulty in accurately interpreting a mammogram is related to there being insufficient contrast to
accurately identify potential abnormalities. Recently, morphology-based algorithms based on structuring elements have
been proposed for contrast enhancement. One of the limitations of these approaches from traditional morphology is their
dependence on the shape of structuring elements. In certain circumstances it may be more appropriate to filter an image
using attributes of structures such as their size, irrespective of shape. This paper introduces a novel nonlinear
enhancement technique that is based on the concept of area morphology. Various mammogram structures are enhanced
to illustrate the technique and a comparison is made with enhancement techniques such as “Contrast Limited Adaptive
Histogram Equalization” and classical morphological enhancement.
The largest single feature on a mammogram is the skin-air interface, or breast contour. Extraction of the breast contour is useful for a number of reasons. Foremost it allows the search for abnormalities to be limited to the region of the breast without undue influence from the background of the mammogram. Segmentation of the breast-region from the background is made difficult by the tapering nature of the breast, such that the breast contour lies in between the soft-tissue and the non-breast region. This paper explores the application of active contours to the problem of extracting the breast region in mammograms.
Of the papers dealing with the task of mammogram registration, the majority deal with the task by matching corresponding control-points derived from anatomical landmark points. One of the caveats encountered when using pure point-matching techniques is their reliance on accurately extracted anatomical features-points. This paper proposes an innovative approach to matching mammograms which combines the use of a similarity-measure and a point-based spatial transformation. Mutual information is a cost-function used to determine the degree of similarity between the two mammograms. An initial rigid registration is performed to remove global differences and bring the mammograms into approximate alignment. The mammograms are then subdivided into smaller regions and each of the corresponding subimages is matched independently using mutual information. The centroids of each of the matched subimages are then used as corresponding control-point pairs in association with the Thin-Plate Spline radial basis function. The resulting spatial transformation generates a nonrigid match of the mammograms. The technique is illustrated by matching mammograms from the MIAS mammogram database. An experimental comparison is made between mutual information incorporating purely rigid behavior, and that incorporating a more nonrigid behavior. The effectiveness of the registration process is evaluated using image differences.
The process of comparative analysis involves inspecting mammograms for characteristic signs of potential cancer by comparing various analogous mammograms. Factors such as the deformable behavior of the breast, changes in breast positioning, and the amount/geometry of compression may contribute to spatial differences between corresponding structures in corresponding mammograms, thereby significantly complicating comparative analysis. Mammogram registration is a process whereby spatial differences between mammograms can be reduced. Presented in this paper is a nonrigid approach to matching corresponding mammograms based on a physical registration model. Many of the earliest approaches to mammogram registration used spatial transformations which were innately rigid or affine in nature. More recently algorithms have incorporated radial basis functions such as the Thin-Plate Spline to match mammograms. The approach presented here focuses on the use of the Cauchy-Navier Spline, a deformable registration model which offers approximate nonrigid registration. The utility of the Cauchy-Navier Spline is illustrated by matching both temporal and bilateral mammograms.
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