Paper
24 June 1998 Three-dimensional reconstruction of clustered microcalcifications from two digitized mammograms
Rainer Stotzka, Tim Oliver Mueller, Wolfgang Epper, Hartmut Gemmeke
Author Affiliations +
Abstract
X-ray mammography is one of the most significant diagnosis methods in early detection of breast cancer. Usually two X- ray images from different angles are taken from each mamma to make even overlapping structures visible. X-ray mammography has a very high spatial resolution and can show microcalcifications of 50 - 200 micron in size. Clusters of microcalcifications are one of the most important and often the only indicator for malignant tumors. These calcifications are in some cases extremely difficult to detect. Computer assisted diagnosis of digitized mammograms may improve detection and interpretation of microcalcifications and cause more reliable diagnostic findings. We build a low-cost mammography workstation to detect and classify clusters of microcalcifications and tissue densities automatically. New in this approach is the estimation of the 3D formation of segmented microcalcifications and its visualization which will put additional diagnostic information at the radiologists disposal. The real problem using only two or three projections for reconstruction is the big loss of volume information. Therefore the arrangement of a cluster is estimated using only the positions of segmented microcalcifications. The arrangement of microcalcifications is visualized to the physician by rotating.
© (1998) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Rainer Stotzka, Tim Oliver Mueller, Wolfgang Epper, and Hartmut Gemmeke "Three-dimensional reconstruction of clustered microcalcifications from two digitized mammograms", Proc. SPIE 3338, Medical Imaging 1998: Image Processing, (24 June 1998); https://doi.org/10.1117/12.310930
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Cited by 3 scholarly publications.
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KEYWORDS
Mammography

Ions

Tissues

Visualization

Image segmentation

Tin

3D image processing

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