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Mammography Registered Tactile Imaging Anna M Galea Harvard University - Division of Engineering and Applied Sciences HST-MEMP, 1999 Robert D. Howe, PhD Harvard University - Division of Engineering and Applied Sciences | ||||||
| Modern clinical breast cancer screening combines a two-pronged approach: breast exams wherein clinicians feel for lumps with their fingers, and mammograms, which are low-dose x-rays. Mammograms are considered to be the gold standard for breast cancer screening, partly because of their repeatability and objectivity. Breast exams, however, are directly related to the physical manifestation of many pathologies, namely a local increased stiffness. Our hypothesis is that we can improve breast cancer screening by combining the two tests currently performed. Tactile imaging can quantify palpation, and we propose a method of presenting a tactile image alongside a mammogram. This requires that we obtain the tactile image in the same plane as a mammogram, and then stretching the tactile image to account for the spreading that occurs under mammographic compression. The study presented here discusses developing the technique for accurately stretching (i.e. registering) the tactile image to the associated mammogram based on computer breast models. The technique is then applied to preliminary clinical data. 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. | ||||||
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