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Learning the Imaging Model of Speed-of-Sound Reconstruction via a Convolutional Formulation
This operates based on a forward model that relates the sought local values of SoS to observed speckle shifts, for which the associated image reconstruction inverse problem is solved.
Training Variational Networks with Multi-Domain Simulations: Speed-of-Sound Image Reconstruction
In this work, we present for the first time a VN solution for a pulse-echo SoS image reconstruction problem using diverging waves with conventional transducers and single-sided tissue access.
Deep Variational Networks with Exponential Weighting for Learning Computed Tomography
Tomographic image reconstruction is relevant for many medical imaging modalities including X-ray, ultrasound (US) computed tomography (CT) and photoacoustics, for which the access to full angular range tomographic projections might be not available in clinical practice due to physical or time constraints.
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