Title :
3-D reconstruction of microcalcification clusters using stereo imaging: algorithm and mammographic unit calibration
Author :
Daul, Christian ; Graebling, Pierre ; Tiedeu, Alain ; Wolf, Didier
Author_Institution :
Inst. Nat. Polytechnique de Lorraine, Vandoeuvre-les-Nancy, France
Abstract :
The three-dimensional (3-D) shape of microcalcification clusters is an important indicator in early breast cancer detection. In fact, there is a relationship between the cluster topology and the type of lesion (malignant or benign). This paper presents a 3-D reconstruction method for such clusters using two 2-D views acquired during standard mammographic examinations. For this purpose, the mammographic unit was modeled using a camera with virtual optics. This model was used to calibrate the acquisition unit and then to reconstruct the clusters in the 3-D space after microcalcification segmentation and matching. The proposed model is hardware independent since it is suitable for digital mammographic units with different geometries and with various physical acquisition principles. Three-dimensional reconstruction results are presented here to prove the validity of the method. Tests were first performed using a phantom with a well-known geometry. The latter contained X-ray opaque glass balls representing microcalcifications. The positions of these balls were reconstructed with a 16.25-μm mean accuracy. This very high inherent algorithm accuracy is more than enough for a precise 3-D cluster representation. Further validation tests were carried out using a second phantom including a spherical cluster. This phantom was built with materials simulating the behavior of both mammary tissue and microcalcifications toward Xrays. The reconstructed shape was effectively spherical. Finally, reconstructions were carried out for real clusters and their results are also presented.
Keywords :
biological organs; cancer; image matching; image reconstruction; image representation; image segmentation; mammography; medical image processing; pattern clustering; phantoms; stereo image processing; 3-D microcalcification cluster reconstruction; X-ray opaque glass balls; benign lesion; early breast cancer detection; malignant lesion; mammary tissue; mammographic unit calibration; microcalcification matching; microcalcification representation; microcalcification segmentation; phantom; stereo imaging; virtual optics; Breast cancer; Calibration; Clustering algorithms; Image reconstruction; Imaging phantoms; Optical imaging; Shape; Stereo image processing; Testing; Three dimensional displays; 3-D reconstruction; Mammographic unit calibration; microcalcification clusters; microcalcification matching; microcalcification segmentation; virtual optics model; Algorithms; Artificial Intelligence; Breast Neoplasms; Calcinosis; Female; Humans; Imaging, Three-Dimensional; Mammography; Pattern Recognition, Automated; Phantoms, Imaging; Photogrammetry; Precancerous Conditions; Radiographic Image Enhancement; Radiographic Image Interpretation, Computer-Assisted; Reproducibility of Results; Sensitivity and Specificity;
Journal_Title :
Biomedical Engineering, IEEE Transactions on
DOI :
10.1109/TBME.2005.857642