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WE‐EF‐303‐04: An Advanced Image Processing Method to Improve the Spatial Resolution of Proton Radiographies
Author(s) -
Rinaldi I,
Parodi K,
Krah N
Publication year - 2015
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.4925995
Subject(s) - imaging phantom , image resolution , optics , monte carlo method , kernel (algebra) , optical transfer function , pixel , materials science , beam (structure) , physics , detector , mathematics , statistics , combinatorics
Purpose: We present an optimization method to improve the spatial resolution and the water equivalent thickness accuracy of proton radiographies. Methods: The method is designed for imaging systems measuring only the residual range of protons without relying on tracker detectors to determine the beam trajectory before and after the target. Specifically, the method was used for an imaging set‐up consisting of a stack of 61 parallel‐plate ionization chambers (PPIC) working as a range telescope. The method uses a decomposition approach of the residual range signal measured by the PPIC and constructs subimages with small size pixels geometrically rearranged and appropriately averaged to be merged into a final single radiography. The method was tested using Monte Carlo simulated and experimental proton radiographies of a PMMA step phantom and an anthropomorphic head phantom. Results: For the step phantom, the effective spatial resolution was found to be 4 and 3 times higher than the nominal resolution for the simulated and experimental radiographies, respectively. For the head phantom, a gamma index was calculated to quantify the conformity of the simulated proton radiographies with a digitally reconstructed X‐ray radiography convolved with a Gaussian kernel equal to the proton beam spot‐size. For DTA=2.5 mm and RD=2.5%, the passing ratio was 100%/85% for the optimized/non‐optimized case, respectively. An extension of the method allows reducing the dose given to the patient during radiography acquisition. We show that despite a dose reduction of 25 times (leading to a dose of 0.016 mGy for the current imaging set‐up), the image quality of the optimized radiographies remains fairly unaffected for both the simulated and experimental results. Conclusion: The optimization method leads to a significant increase of the spatial resolution allowing recovering image details that are unresolved in non‐optimized radiographies. These results represent a major step towards clinical application of proton radiography.