Analysis of primary modulation based x‐ray scatter correction methods. Issue 11 (5th October 2016)

• Record Type: Journal Article
• Authors: Horváth, Áron; Hadházi, Dániel; Horváth, Gábor
• Is Part Of: Medical physics. Volume 43:Issue 11(2016)
• Page Start: 5794
• Page End: 5807
• Publication Date: 2016-10-05
• Subjects: computerised tomography -- gradient methods -- image denoising -- image sampling -- image texture -- medical image processing -- modulators; Computed tomography -- Noise; Computerised tomographs -- Biological material, e.g. blood, urine; Haemocytometers -- Digital computing or data processing equipment or methods, specially adapted for specific applications -- Image data processing or generation, in general -- Image enhancement or restoration, e.g. from bit‐mapped to bit‐mapped creating a similar image -- Analysis of texture -- Modulation; primary modulation -- scatter correction -- backscatter; X‐ray scattering -- Modulators -- X‐ray detectors -- Image sensors -- Medical X‐ray imaging -- Cone beam computed tomography -- Image reconstruction -- Medical image reconstruction -- Backscattering; Medical physics -- Periodicals; Medical physics; Geneeskunde; Natuurkunde; Toepassingen; Biophysics; Periodicals; Periodicals; Electronic journals; 610.153
• DOI: 10.1118/1.4963209
• Languages: English
• ISSNs: 0094-2405

Abstract

Abstract : Purpose: The purpose of this study is to provide an overview of primary modulation based scatter estimation techniques and evaluate their performance as well as to propose improvements. There have been published two distinct approaches to estimate scatter with primary modulators; however they have not been compared, so far. This work seeks to quantify their performance (focusing on how accurately they can estimate a smooth scatter from primary modulated images with real textures and signal to noise ratios) along with that of proposed improved variants. The influence of the parameters of the described algorithms on the estimation error is also investigated. Methods: Simulations were carried out using primary components derived from real chest DTS projections. After modulation, artificial scatter distributions were added to these projections, and the difference between the estimated and the artificial scatter distributions was quantified. Two existing and four proposed methods were assessed. The performance of the scatter estimators was examined under noisy and noiseless circumstances and with scatter distributions of different bandwidths. The proposed methods (SSE, SSENP, ADASE) solve the problem of varying effective transmission factors in the case of cell‐image based methods, and they include an improved gradient based method (LSGSE) as well, which estimates scatter distribution more accurately. Results: It was found that the gradient based algorithms outperformed the cell‐image based algorithms under noiseless conditions, while the cell‐image based solutions proved to be insensitive to noise. The proposed improved methods reached considerably lower scatter estimation errors than the existing ones. Modulator cell sampling windows of different sizes and shapes were examined. Although much lower effective transmission factors (higher contrast between the attenuated and unattenuated cells) can be achieved using narrow windows, in our case the best estimation results are provided by windows that cover about half of the pixels of a modulator cell. The effect of detector backscatter on scatter estimation was also studied, and a solution was proposed to incorporate this type of scatter into the primary modulation framework. Conclusions: Considering all the above results, the authors suggest the use of LSGE for scatter estimation with primary modulation.