3D inverse scattering ultrasound tomography (3D UT) is quantitative and not subject to artifacts from 2D algorithms and data and does not require contrast agents or ionizing radiation. However, it is time consuming, so it is important to have timing results for 3D inverse scattering reconstructions of the whole breast with 3D algorithms and full 3D data and in the clinically relevant context of a diverse population of dense, heterogeneously dense and fatty breasts. The adaptive algorithm uses different reconstruction frequencies and iteration counts for different breasts. We compare a computational complexity count with the observed fit of reconstruction times vs breast size that and show performance comparable to published TFLOP performance for nVidia cards. We show a reconstruction time of 24 minutes for an average size breast and show substantial speed up with more efficient nVidia cards. These numbers indicate clinical viability for 3D transmission ultrasound even in the clinical setting with diverse demographics in low income areas. The cohort of 23 cases of different types of breasts were reconstructed on two P6000's and compared with the same data reconstructed on two RTX6000's with 24GB on-board memory and some optimization of the CUDA code. The resulting speed up is better than linear with increasing computation time, indicating increasing efficiency with computational complexity, larger breasts. Image quality is also affected, since increasing iteration and frequency counts give generally better images as long as overconvergence is avoided. These results further validate the 3D Quantitative UT as clinically viable, especially for underserved populations.
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