Breast cancer and other breast pathologies often manifest as an area of increased tissue stiffness. The gold standard for breast cancer screening is mammography, which records the radioopacity of tissues in the breast, and therefore depends on factors other than stiffness. Tactile imaging uses an array of pressure sensors to noninvasively record the palpable extent of breast tissue stiffness. Tactile imaging quantifies palpation, and holds promise for increasing the positive predictive value of screening mammography by highlighting areas of abnormal stiffness. We propose a method for registering tactile images obtained in the same plane and immediately after the corresponding mammogram. A finite element model-based approach is presented which is used to account for the spreading of the breast tissue induced by the mammographic compression that is not present in obtaining the tactile image. We devise an algorithm that can register the modeled tactile images to within 6% of the modeled mammograms for breasts of varying size and stiffness. Clinical mammograms and tactile images were collected on 11 subjects, and the registration algorithm applied to the images. The registered tactile images and mammograms correlate well over stiff, radioopaque areas such as glandular and fibrous tissue, and highlight areas of increased stiffness not indicated by the mammogram alone. © Springer-Verlag Berlin Heidelberg 2003.
CITATION STYLE
Galea, A. M., & Howe, R. D. (2003). Mammography registered tactile imaging. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2673, 183–193. https://doi.org/10.1007/3-540-45015-7_18
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