Abstract
The digital X-ray detectors often generate stripe artifact in the sinogram which in turn creates ring artifact in the reconstructed micro-Computed Tomography (-CT), C-Arm CT, and most recent dental CT images. Such ring artifacts not only obscure image details in the regions of interest but also mask the whole image with some artifacts. In this paper, novel techniques are proposed for the detection and suppression of ring artifacts in the sinogram domain. As ring artifacts are manifested as edge creating stripes, single or contiguous, in the sinogram, they are detected based on a set of specific conditions derived from the second derivative of the sinogram and a new self-adaptive threshold computed from its first derivative. A new method for the detection of wide band contiguous stripes using the mean curve and multilevel polyphase decomposition of the given sinogram is also proposed here. For the correction of ring artifacts, novel variable window moving average (VWMA) and weighted moving average (WMA) filters are proposed in this work. To evaluate and compare the performance of the proposed algorithm, various types of synthetic and real -CT images are used. Experimental results show that the proposed method can detect ring artifacts with high accuracy and thus remove them more effectively without imparting noticeable distortion in the image as compared to other reported techniques.
Highlights
Computed tomography (CT) is an imaging technique capable of generating high-resolution three-dimensional (3D) images of an object from two-dimensional (2D) X-ray projection data or 2D slices from 1D projection data [1, 2]
To overcome the limitations of the conventional moving average- (MA-) based schemes, the new variable window moving average (VWMA) and weighted moving average (WMA) filters proposed in this work are used appropriately to correct both the isolated and contiguous stripes
The test images were acquired with a home made micro-CT which consists of a flat-panel detector (C7943CA02, Hamamatsu, Japan) and a microfocus X-ray tube (L812101, Hamamatsu, Japan)
Summary
Computed tomography (CT) is an imaging technique capable of generating high-resolution three-dimensional (3D) images of an object from two-dimensional (2D) X-ray projection data or 2D slices from 1D projection data [1, 2]. While it may be tempting to detect and remove the artifact in the image domain rather than the sinogram domain, the extra artifacts inherently generated along with the ring artifacts due to the filtered back projection reconstruction procedure cannot be detected and removed by a signal processing technique in the image domain Since it is the 2D radiographic projection data, generally known as the sinogram [1], which are corrupted, some reported methods dealt with the raw sinogram, referred to as the preprocessing approaches [10,11,12,13,14,15,16]. Very recently a waveletFourier filter has been reported in [16] for the correction of stripes in the sinogram The performance of this method, significantly degrades when an image is corrupted by a sharp ring of varying intensity. We propose novel self-adaptive approaches for the detection and correction of stripes in the sinogram with a view to suppress ring artifacts in CT imaging.
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