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Fused microwave and ultrasonic breast imaging within the framework of a joint variational Bayesian approximation

Abstract : Early diagnosis of breast tumors can in principle be achieved by jointly running electromagnetic and acoustic probings, more precisely Microwave (MW) and ultrasound (US). Indeed, such modalities are non-invasive, non-ionizing, low-cost, and proceed without registration for free pending breasts, not like other joint modalities that impose compression. In view of the strongly-contrasted electromagnetic parameters of breast constituents, MW yields high-contrast images of low resolution, the converse with US since faced with weakly refracting elements. The key benefit is the common breast structure, and fusion should produce images with both high contrast and resolution. A Bayesian formalism is chosen, an unsupervised Joint Variational Bayesian Approximation or JVBA being developed, edges hid- den variables, hyper-parameters automatically tuned along the optimization. The mathematics is detailed in a general setting of fusion, then one proposes imaging of realistic MRI-derived breast slices. A wealth of numerical simulations from noisy single- frequency MW and multiple-frequency US data preserved from inverse crime yields means (i.e., breast maps) and variances of the unknown electromagnetic and acoustic parameter distributions as probabilistic realizations, evolutions of hyper-parameters, as well as global indicators of accuracy. Comparisons with a joint edge-preserving contrast source inversion (JCSI-EP) developed earlier in a determlnistic framework illustrate the methodology.
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Contributor : Dominique Lesselier Connect in order to contact the contributor
Submitted on : Wednesday, February 9, 2022 - 6:13:25 PM
Last modification on : Monday, February 21, 2022 - 3:38:21 PM


  • HAL Id : hal-03563568, version 1


Yingying Qin, Thomas Rodet, Dominique Lesselier. Fused microwave and ultrasonic breast imaging within the framework of a joint variational Bayesian approximation. 2022. ⟨hal-03563568⟩



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