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WE‐G‐207‐08: Imaging Dose Reduction and Scatter Removal in Cone Beam CT Via Random Undersampling: A Simulation Study
Author(s) -
Shen C,
Chen L,
Xu Y,
Tian Z,
Ng M,
Zeng T,
Lou Y,
Zhu L,
Jia X
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 - 10.1118/1.4926101
Subject(s) - undersampling , cone beam computed tomography , projection (relational algebra) , iterative reconstruction , monte carlo method , image quality , imaging phantom , computer science , mathematics , algorithm , optics , artificial intelligence , physics , image (mathematics) , statistics , medicine , computed tomography , radiology
Purpose: Cone‐beam CT (CBCT) is widely used in image‐guided radiation therapy. The high imaging dose from repeated uses is a clinical concern and its image quality is impeded by a large amount of scattered photons. We propose to solve these two problems via a random undersampling method. We have performed Monte Carlo (MC) simulation studies for an initial test of the method. Methods: We propose to place a moving beam blocker with a random blocking pattern in front of the x‐ray source. It blocks a projection with a random pattern, which varies among projections. Scatter signal is measured in the deliberately created shadows, which is further interpolated to the entire projection. After removing the interpolated scatter from the total signal in the un‐blocked area, the cleaned data were used for CBCT reconstruction under a Tight Frame (TF) based iterative method. The random sampling yields a projection matrix that has a better numerical property compared to regular undersampling, permitting better image reconstruction. Results: 360 CBCT projections of a head‐and‐neck cancer patient were generated via MC simulations. We first reconstructed CBCTs using 90 full projections with only primary data. The RMS error was 16%. When scattered photons were included in the projection, reduced contrast was observed and the RMS error was 22%. In our proposed method, 360 projections were used, but each of them was randomly blocked by 75% of pixels. Scatter estimation and was performed and the corrected data were used in reconstruction, yielding a reconstruction error of 15%. In these two approaches, the imaging doses were both reduced by ∼75% compared to a full scan with 360 unblocked projections. Conclusion: we proposed a method to solve the imaging dose and scatter problem in CBCT in a unified manner. Preliminary simulation studies demonstrated its efficacy.