X-ray scatter is a major degrading factor in x-ray cone beam (CB) CT imaging. In the scatter corrections by using Monte
Carlo (MC) simulation, the initial MC modeling is not accurate based on the scatter-polluted volume images, thus the
correction has to be performed iteratively, which is one of the reasons that MC based correction is computational
demanding. In this paper, we found a relationship that the ratio of IS (scatter) to IP+S (primary plus scatter) can be
approximated by the weighted data in Radon space. On this basis, we develop a strategy called Projection Contrast
Enhancement based Pre-Correction (PCEPC). PCEPC is efficient, achieving a scatter pre-correction with enhanced
image Quality (Q) of ~0.7 (Q=1 for scatter-free images; Q=0 for scatter-contaminated images without correction). By
using the results of PCEPC, more accurate MC modeling on the scanned object is feasible with less iterations or even in
a non-iterative way, namely as the PCEPC-MC method. An exemplary non-iterative PCEPC-MC is implemented, in
which the scatter fluence of eighteen views equally distributed over 2π is simulated by MC toolkit EGSnrc, enhancing
the Q further to ~0.8.
X-ray scatter leads to erroneous calculations of dual-energy digital mammography (DEDM). The existing methods for
scatter correction in DEDM are using anti-scatter grids or the pinhole-array interpolation method which is complicated
and impractical. In this paper, a scatter correction algorithm for DEDM is developed based on the knowledge that scatter
radiation in mammograms varies slowly and most pixels in mammograms are non-microcalcification pixels. The
proposed algorithm only uses the information of low-energy (LE) and high-energy (HE) images. And it doesn't need
anti-scatter grids, lead sheet and extra exposures. Our results show that the proposed scatter correction algorithm is
effective. When using the simple least-squares fit and linear interpolation, the scatter to primary ratio (SPR) can be
decreased from ~33.4% to ~2.8% for LE image and from ~26.2% to ~0.8% for HE image. Applying scatter correction to
LE and HE images, the resultant background signal in the DE (dual-energy) calcification image can be reduced
X-ray scatter correction is an open problem in the research of cone beam CT (CBCT). In this paper, using
semitransparent beam stop array (BSA) introduced recently1, an improved BSA method2 is proposed. A simple iterative
correction algorithm is developed based on the knowledge that mostly primary varies continuously. With the proposed
method, scatter correction could be accomplished without extra scan. Experiments are carried out based on the Monte
Carlo (MC) simulation (EGSnrc), the mean square error (MSE) is reduced from 50.71% (with no correction) to 2.54%,
and there is no visible negative impact introduced by the correction.
We aimed to evaluate the effect of different components of chest image on performances of both human observer and
channelized Fisher-Hotelling model (CFH) in nodule detection task. Irrelevant and relevant components were separated
from clinical chest radiography by employing Principal Component Analysis (PCA) methods. Human observer
performance was evaluated in two-alternative forced-choice (2AFC) on original clinical images and anatomical structure
only images obtained by PCA methods. Channelized Fisher-Hotelling model with Laguerre-Gauss basis function was
evaluated to predict human performance. We show that relevant component is the primary factor influencing on nodule
detection in chest radiography. There is obvious difference of detectability between human observer and CFH model for
nodule detection in images only containing anatomical structure. CFH model should be used more carefully.
To calibrate step gauges, a new linear measuring system was improved in our laboratory that combines the Leitz universal measuring machine of the 1960s with a laser interferometer. This paper introduces the measurement method and the calculation of the expanded uncertainty of the measurement. The expanded uncertainty of the system is (0.3 + L) μm at k=2, where L is given in meter.
In paper, we present a new correction algorithm for the unfunctional cell distortions in conventional CT imaging, based on the Chebyshev orthogonal polynomials series expressions. This algorithm first reevaluates the projection sinograms by the least mean square algorithm, and then the filtered backprojection (FBP) algorithm are executed for the reconstruction of CT image. Through the simulation experiment, the feasibility of this method is validated.