High-resolution 3D micro-CT imaging of breast microcalcifications: a preliminary analysis.

BACKGROUND: Detection of microcalcifications on mammograms indicates the presence of breast lesion, and the shapes of the microcalcifications as seen by conventional mammography correlates with the probability of malignancy. This preliminary study evaluated the 3D shape of breast microcalcifications using micro-computed tomography (micro-CT) and compared the findings with those obtained using anatomopathological analysis. METHODS: The study analyzed breast biopsy samples from 11 women with findings of suspicious microcalcifications on routine mammograms. The samples were imaged using a micro-CT (SkyScan 1076) at a resolution of 35 µm. Images were reconstructed using filtered back-projection and analyzed in 3D using surface rendering. The samples were subsequently analyzed by the pathology service. Reconstructed 3D images were compared with the corresponding histological slices. RESULTS: Anatomopathological analysis showed that 5 of 11 patients had ductal breast carcinoma in situ. One patient was diagnosed with invasive ductal carcinoma.Individual object analysis was performed on 597 microcalcifications. Malignant microcalcifications tended to be thinner and to have a smaller volume and surface area, while their surface area-to-volume ratio was greater than that of benign microcalcifications. The structure model index values were the same for malignant and benign microcalcifications. CONCLUSIONS: This is the first study to use micro-CT for quantitative 3D analysis of microcalcifications. This high-resolution imaging technique will be valuable for gaining a greater understanding of the morphologic characteristics of malignant and benign microcalcifications. The presence of many small microcalcifications can be an indication of malignancy. For the larger microcalcifications, 3D parameters confirmed the more irregular shape of malignant microcalcifications.

3D human pose recognition for home monitoring of elderly.

A toolbox for the automatic monitoring of elderly in a nursing home or in the natural home environment is proposed. Rather than monitoring vital signs or other biomedical parameters, the toolbox is focussed on the monitoring of activity patterns and changes therein. Activity information is derived from visual information using image processing algorithms. The visual information is acquired using 3D camera technology. Besides a traditional visual image, 3D cameras also provide highly accurate depth information. The 3D position of the subject is derived and serves as the primary information source for the different components in the toolbox.