Compact reverse time migration: A real-time approach for full waveform ultrasound imaging for breast.

We present compact reverse time migration (CRTM), a real-time ultrasound imaging method that can exploit the full waveform information of ultrasonic wave records for imaging breast tissue. Conventional reverse time migration (RTM) computes the gradient of the reflective ultrasound data with respect to the perturbation of the velocity model of the soft tissues and the gradient can indicate the interface between different types of body tissue. In contrast to conventional reflection ultrasound (B-mode), which is based on the high-frequency approximation to the wave equation, the RTM algorithm is based on the complete wave equation, and can thus exploit the full waveform (wide-spectrum) information of the data and provide an image with higher resolution. Unfortunately, the computational burden of RTM is noticeably higher than the ray-based B-mode. This precludes real-time applications, one of the most important features of ultrasound imaging. The proposed CRTM algorithm can significantly reduce the computational costs of RTM, such that it can be applied for real-time imaging. We demonstrate the performance of CRTM through a synthetic experiment of ultrasound breast imaging. CRTM can be potentially adapted to related signal-processing fields, such as seismic imaging, acoustic camera systems, and radar imaging.

Multi-Disciplinary Monitoring Networks for Mesoscale Underground Experiments: Advances in the Bedretto Reservoir Project.

The Bedretto Underground Laboratory for Geosciences and Geoenergies (BULGG) allows the implementation of hectometer (>100 m) scale in situ experiments to study ambitious research questions. The first experiment on hectometer scale is the Bedretto Reservoir Project (BRP), which studies geothermal exploration. Compared with decameter scale experiments, the financial and organizational costs are significantly increased in hectometer scale experiments and the implementation of high-resolution monitoring comes with considerable risks. We discuss in detail risks for monitoring equipment in hectometer scale experiments and introduce the BRP monitoring network, a multi-component monitoring system combining sensors from seismology, applied geophysics, hydrology, and geomechanics. The multi-sensor network is installed inside long boreholes (up to 300 m length), drilled from the Bedretto tunnel. Boreholes are sealed with a purpose-made cementing system to reach (as far as possible) rock integrity within the experiment volume. The approach incorporates different sensor types, namely, piezoelectric accelerometers, in situ acoustic emission (AE) sensors, fiber-optic cables for distributed acoustic sensing (DAS), distributed strain sensing (DSS) and distributed temperature sensing (DTS), fiber Bragg grating (FBG) sensors, geophones, ultrasonic transmitters, and pore pressure sensors. The network was realized after intense technical development, including the development of the following key elements: rotatable centralizer with integrated cable clamp, multi-sensor in situ AE sensor chain, and cementable tube pore pressure sensor.

Optimal experimental design for joint reflection-transmission ultrasound breast imaging: From ray- to wave-based methods.

Ultrasound computed tomography (USCT) is an emerging modality to image the acoustic properties of the breast tissue for cancer diagnosis. With the need of improving the diagnostic accuracy of USCT, while maintaining the cost low, recent research is mainly focused on improving (1) the reconstruction methods and (2) the acquisition systems. D-optimal sequential experimental design (D-SOED) offers a method to integrate these aspects into a common systematic framework. The transducer configuration is optimized to minimize the uncertainties in the estimated model parameters, and to reduce the time to solution by identifying redundancies in the data. This work presents a formulation to jointly optimize the experiment for transmission and reflection data and, in particular, to estimate the speed of sound and reflectivity of the tissue using either ray-based or wave-based imaging methods. Uncertainties in the parameters can be quantified by extracting properties of the posterior covariance operator, which is analytically computed by linearizing the forward problem with respect to the prior knowledge about parameters. D-SOED is first introduced by an illustrative toy example, and then applied to real data. This shows that the time to solution can be substantially reduced, without altering the final image, by selecting the most informative measurements.