Interferometry is an approach to extract the Green's function between two receivers as if the virtual source is at one of the receiver locations. The Green's function which is the response to an impulsive source, accounts for the wave propagation in the medium between the two receivers. It is commonly thought that Green's function estimates obtained from interferometry accurately represent the full Green's function, but this is not always the case. In fact, the accuracy of the retrieved Green's function, which consists of the surface and body waves, is in practice restricted by the limited distribution of the sources of field fluctuations. We demonstrate the importance of adequate source distribution for the accuracy of the retrieved Green's function, using examples from interferometry applications. In these examples, sources are controlled (as in exploration seismology) or uncontrolled (as in crustal seismology).
Purpose
Three‐dimensional in‐vivo dose verification is one of the standing challenges in radiation therapy. X‐ray‐induced acoustic tomography has recently been proposed as an imaging method for use in in‐vivo dosimetry. The aim of this study was to investigate the accuracy of reconstructing three‐dimensional (3D) absolute dose using x‐ray‐induced acoustic tomography. We performed this investigation using two different tomographic dose reconstruction techniques.
Methods
Two examples of 3D dose reconstruction techniques for x‐ray acoustic imaging are investigated. Dose distributions are calculated for varying field sizes using a clinical treatment planning system. The induced acoustic pressure waves which are generated by the increase in temperature due to the absorption of pulsed MV x‐rays are simulated using an advanced numerical modeling package for acoustic wave propagation in the time domain. Two imaging techniques, back projection and iterative time reversal, are used to reconstruct the 3D dose distribution in a water phantom with open fields. Image analysis is performed and reconstructed depth dose curves from x‐ray acoustic imaging are compared to the depth dose curves calculated from the treatment planning system. Calculated field sizes from the reconstructed dose profiles by back projection and time reversal are compared to the planned field size to determine their accuracy. The iterative time reversal imaging technique is also used to reconstruct dose in an example clinical dose distribution. Image analysis of this clinical test case is performed using the gamma passing rate. In addition, gamma passing rates are used to validate the stopping criteria in the iterative time reversal method.
Results
Water phantom simulations showed that back projection does not adequately reconstruct the shape and intensity of the depth dose. When compared to the depth of maximum dose calculated by a treatment planning system, the maximum dose depth by back projection is shifted deeper by 55 and 75 mm for 4 × 4 cm and 10 × 10 cm field sizes, respectively. The reconstructed depth dose by iterative time reversal accurately agrees with the planned depth dose for a 4 × 4 cm field size and is shifted deeper by 12 mm for the 10 × 10 cm field size. When reconstructing field sizes, the back projection method leads to 18% and 35% larger sizes for the 4 × 4 cm and 10 × 10 cm fields, respectively, whereas the iterative time reversal method reconstructs both field sizes with < 2% error. For the clinical dose distribution, we were able to reconstruct the dose delivered by a 1 degree sub‐arc with a good accuracy. The reconstructed and planned doses were compared using gamma analysis, with> 96% gamma passing rate at 3%/2 mm.
Conclusions
Our results show that the 3D x‐ray acoustic reconstructed dose by iterative time reversal is considerably more accurate than the dose reconstructed by back projection. Iterative time reversal imaging has a potential for use in 3D absolute dosimetry.
Existing methods of internal multiple prediction are either computationally expensive or not automated. Here, based on stationary phase arguments, we introduce a method for predicting internal multiples that is not only fully automated but also computationally inexpensive. The procedure is completely data driven and requires no velocity information or reflector identification. An additional advantage of the proposed method is that it can also be used to predict source-and receiver-ghosts. The method, however, is limited to gently-dipping reflectors. Through synthetic examples and field data, we demonstrate the effectiveness of our methodology.
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