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Alternative Breast Imaging Four Model-Based Approaches by Keith D. Paulsen, Paul M. Meaney, Larry Gilman

By Keith D. Paulsen, Paul M. Meaney, Larry Gilman

This ebook explores our learn on 4 such modalities, fairly with reference to imaging of the breast: (1) MR elastography (MRE), (2) electric impedance spectroscopy (EIS), (3) microwave imaging spectroscopy (MIS), and (4) close to infrared spectroscopic imaging (NIS).

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20), where M is the bandwidth of the sparse matrix [A]. For large N, the savings can be significant. Finally, this approach is quite general and can be readily expanded to 3D for each modality. 4 Iterative Reconstruction in MRE In the MRE system, tissue is vibrated along a single axis at low amplitude and low frequency. This excitation is phase-locked to the sequencing of the MR system to measure the harmonic displacement of each pixel in space. Because an information-rich volumetric data set is acquired in this case, strategies other than those described above (which exploit the fact that there are relatively few observations) must be utilized to improve computational efficiency.

18 Model-Based Breast Imaging Figure 5. Relationship between pathological vessel density (MVD, expressed as a number between 0 and 1 rather than as a percentage) and percent blood, as determined from imaged NIS parameters. Error bars show the standard deviations in both dimensions. TEAM LinG - Live, Informative, Non-cost and Genuine ! Four Alternative Modalities 19 An additional remark concerning the MVD measure is called for. We originally selected mean MVD as a morphometric measure following work by Weidner et al.

The first is a spatial filtering approach. When the property distribution is updated at each iteration, uneven fluctuations in the intermediate image can occur, especially during the early stages of the process. We have devised a spatial filter which can be applied through a matrix-vector multiplication that forms a weighted average of the value at node i with those of its surrounding neighbors [24]: Here, q is chosen to be between 0 and 1, T is the number of nodes to be averaged, and the superscripts “old” and “new” refer to the property values before and after application of the filter, respectively.

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