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A forward model incorporating elevation-focused transducer properties for 3D full-waveform inversion in ultrasound computed tomography.
ArXiv ; 2023 Sep 14.
Article in En | MEDLINE | ID: mdl-36713246
ABSTRACT
Ultrasound computed tomography (USCT) is an emerging medical imaging modality that holds great promise for improving human health. Full-waveform inversion (FWI)-based image reconstruction methods account for the relevant wave physics to produce high spatial resolution images of the acoustic properties of the breast tissues. A practical USCT design employs a circular ring-array comprised of elevation-focused ultrasonic transducers, and volumentric imaging is achieved by translating the ring-array orthogonally to the imaging plane. In commonly deployed slice-by-slice (SBS) reconstruction approaches, the three-dimensional (3D) volume is reconstructed by stacking together two-dimensional (2D) images reconstructed for each position of the ring-array. A limitation of the SBS reconstruction approach is that it does not account for 3D wave propagation physics and the focusing properties of the transducers, which can result in significant image artifacts and inaccuracies. To perform 3D image reconstruction when elevation-focused transducers are employed, a numerical description of the focusing properties of the transducers should be included in the forward model. To address this, a 3D computational model of an elevation-focused transducer is developed to enable 3D FWI-based reconstruction methods to be deployed in ring-array-based USCT. The focusing is achieved by applying a spatially varying temporal delay to the ultrasound pulse (emitter mode) and recorded signal (receiver mode). The proposed numerical transducer model is quantitatively validated and employed in computer-simulation studies that demonstrate its use in image reconstruction for ring-array USCT.

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: ArXiv Year: 2023 Document type: Article

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: ArXiv Year: 2023 Document type: Article