- Open Access
Inter-plane artifact suppression in tomosynthesis using 3D CT image data
© Kim et al.; licensee BioMed Central Ltd. 2011
- Received: 29 October 2011
- Accepted: 10 December 2011
- Published: 10 December 2011
Despite its superb lateral resolution, flat-panel-detector (FPD) based tomosynthesis suffers from low contrast and inter-plane artifacts caused by incomplete cancellation of the projection components stemming from outside the focal plane. The incomplete cancellation of the projection components, mostly due to the limited scan angle in the conventional tomosynthesis scan geometry, often makes the image contrast too low to differentiate the malignant tissues from the background tissues with confidence.
In this paper, we propose a new method to suppress the inter-plane artifacts in FPD-based tomosynthesis. If 3D whole volume CT images are available before the tomosynthesis scan, the CT image data can be incorporated into the tomosynthesis image reconstruction to suppress the inter-plane artifacts, hence, improving the image contrast. In the proposed technique, the projection components stemming from outside the region-of-interest (ROI) are subtracted from the measured tomosynthesis projection data to suppress the inter-plane artifacts. The projection components stemming from outside the ROI are calculated from the 3D whole volume CT images which usually have lower lateral resolution than the tomosynthesis images. The tomosynthesis images are reconstructed from the subtracted projection data which account for the x-ray attenuation through the ROI. After verifying the proposed method by simulation, we have performed both CT scan and tomosynthesis scan on a phantom and a sacrificed rat using a FPD-based micro-CT.
We have measured contrast-to-noise ratio (CNR) from the tomosynthesis images which is an indicator of the residual inter-plane artifacts on the focal-plane image. In both cases of the simulation and experimental imaging studies of the contrast evaluating phantom, CNRs have been significantly improved by the proposed method. In the rat imaging also, we have observed better visual contrast from the tomosynthesis images reconstructed by the proposed method.
The proposed tomosynthesis technique can improve image contrast with aids of 3D whole volume CT images. Even though local tomosynthesis needs extra 3D CT scanning, it may find clinical applications in special situations in which extra 3D CT scan is already available or allowed.
- Projection Data
- Projection View
- Projection Component
- Magnification Ratio
- Tomosynthesis Image
Tomosynthesis is now gaining its important roles in clinical diagnosis owing to its dual features of CT and radiography. Tomosynthesis can be incorporated into many kinds of x-ray imaging systems that are equipped with a flat panel detector (FPD) as an image acquisition device. Such FPD-based x-ray imaging systems include C-arm imaging systems, mammography systems, and some DR systems. As compared to image intensifiers, FPDs have no spatial distortion in image acquisition, which is essential for accurate image reconstruction in tomosynthesis. Unlike CT imaging where axial resolution is of main concern, tomosynthesis aims at taking high lateral-resolution images for which fine pixel-pitch FPDs are well fitted [1, 2]. Aside from the superior lateral resolution, tomosynthesis has great clinical potential because of its lower x-ray dose as compared to CT [3, 4].
Due to the limited scan angle of tomosynthesis, usually less than 60°, the off-focal plane components are not completely cancelled out in the tomosynthesis image reconstruction [5–7]. The partial cancellation of the off-focal components limits the depth resolving power of thomosynthesis and it makes the slice profile in the depth direction extended far away from the focal plane . The extended slice profile often makes inter-plane artifacts particularly when high intensity structures exist in off-focal planes . The inter-plane artifacts, also called ghost artifacts, could mislead the diagnosis severely compromising the clinical utility of tomosynthesis.
With a cone-beam CT equipped with a FPD as an image acquisition device, tomosynthesis scan can be easily performed by simply limiting the scan angle [9, 10]. By taking high-resolution projection images at multiple viewing angles in the CT scan geometry and combining the multiple projection images in a way that those are coherently added on a focal plane, tomosynthesis images can be made in the framework of cone-beam CT. When repetitive follow-up imaging of a region of interest (ROI) is necessary after localizing the ROI by CT scan as in the case of radio-therapy and dental implanting, tomosynthesis would be suitable for the follow-up imaging because of its faster scan time and lower x-ray dose than CT's. In such a situation, the CT image data can be incorporated into the tomosynthesis image reconstruction to remove the inter-plane artifacts. Once the off-focal components, which account for the projection components outside the ROI, have been computed from the 3D CT image data, the off-focal components can be subtracted from the tomosynthesis projection data for removal of the inter-plane artifacts. We call this technique local tomosynthesis in that the projection components stemming from a local ROI are only involved in the tomosynthesis image reconstruction. We have verified the local tomosynthesis concept through simulations and real experiments with a micro-CT, and we present experimental results of the local tomosynthesis in comparison with the ones obtained from the conventional tomosynthesis.
Calculation of the projection components stemming from outside the region of interest
The measured projection data would have higher spatial resolution, owing to the high magnification ratio at the tomosynthesis scan, than the projection data computed from the CT image. Therefore, low-resolution and high-resolution projection components may be mixed together in.
Tomosynthesis image reconstruction
where a ij,n is the path length of the ray at the j-th pixel that reaches the i-th detector element in the n-th projection view, k is the iteration number, I i,n is the measured projection data at the i-th detector element in the n-th projection view, 〈a, x〉 i,n is the line integral of the estimated attenuation coefficients along the x-ray path that hits the i-th detector element in the n-th projection view, and I 0,n is the incident x-ray beam intensity in the n-th view. N and I are the total number of projection views and the number of detector elements, respectively. In the reconstruction of tomosynthesis images using the ML-convex method, we use uniform images as the initial guess of the reconstruction and we set the step size λ to 1. We stop the iteration evaluating the image quality by visual inspection.
Image quality evaluation
where I s is the mean pixel intensity at the feature region, I B is the mean pixel intensity at the nearby background and σ BG is the standard deviation of the pixel intensity at the nearby background.
Experimental set up
Simulations and imaging experiments
CNRs measured at the three feature patterns in the simulated images
CNRs measured at the three feature patterns in the experimental images
The contrast improvement in the proposed local tomosynthesis is largely due to the suppression of inter-plane artifacts stemming from the off-focal planes. Therefore, the degree of contrast improvement will be spatially variant depending on the tissue inhomogeneity in off-focal planes. The contrast enhancement will be maximized when the two projection data, one from the CT scan and the other from the tomosynthesis scan, are best registered in terms of scan geometry and x-ray attenuation. If the two scan geometries are not registered perfectly in the subtraction of the two projection data, the cancellation of the off-focal components will not be complete and residual inter-plane artifacts may persist. We have performed the experiments with a small-scale micro-CT in which the scan geometry can be rather precisely controlled by precision mechanism. But, in a large-scale human imaging device, changing the scan geometry in precision will be a technical challenge. The two projection data may not be registered well due to different x-ray attenuation along the different projection lines in the CT and tomosynthesis scans. The polychromatic x-ray attenuation is never linear due to beam hardening and scattering of the x-ray beam. So, the two projection data obtained with different magnification ratios may not be registered well in the subtraction. But, the experimental results obtained under different magnification settings in this study have shown that inter-plane artifacts in tomosynthesis can be suppressed to some degree by the proposed technique. The advantage of high magnification ratio imaging in tomosynthesis may be offset due to the penumbra effect caused by the finite-sized x-ray focal spot. Therefore, we have to carefully choose the magnification ratio to get optimal spatial resolution in the tomosynthesis scan.
For practical use of the proposed method, we have to address many technical issues. Firstly, we have to establish an efficient way to exactly register the two scan geometries, one for the CT scan and the other for the tomosynthesis scan. For given scan geometries for the CT and tomosynthesis scans, we have to register them in the framework of the projection data subtraction in a fast and automatic way. Since the estimation of the projection components stemming from the ROI is based on the subtraction, the local tomosynthesis images are sensitive to the subtraction errors. In the present experiments, we have manually measured the scan geometries by taking two projection images of a thin planar structure with different magnification ratios. After taking the two projection images, we found the magnification ratios of the two scans and translational/rotational mismatches between the two scans using the image registration technique. Secondly, we have to find the extent of ROI size to which we can take advantage of local tomosynthesis. If the ROI is too small as compared to the whole volume size, small minor errors in estimating the projection components from the CT images may lead to significant errors in reconstructing tomosynthesis images. In the future studies, we should perform further investigations on the effects of the aforementioned factors on the local tomosynthesis image quality.
A clear limitation of the proposed method is that we need an extra CT scan to get the 3D information about attenuation coefficient distribution. In most cases, 3D CT scanning would suffice since 3D CT images usually provide sufficient anatomical information of the imaging region. However, in the situation where extra tomosynthesis scan is allowed in addition to the 3D CT scan or vice versa, the proposed local tomosynthesis technique will find advantages over the conventional tomosynthesis technique. We think local tomosynthesis may find its clinical application particularly in dental imaging. For dental implanting, we usually obtain 3D CT images of the whole teeth. However, it is often the case that we need high-resolution lateral views of the teeth of interest or the dental implants to better position them on the mandibula or maxilla bones. Considering the fact that low dose CT imaging techniques have been widely developing [17–20], we may consider extra low dose CT scan for the local tomosynthesis in some clinical applications using a C-arm CT.
The proposed local tomosynthesis technique can significantly suppress the inter-plane artifacts improving tomosynthesis image contrast with aids of 3D whole volume CT images. Even though local tomosynthesis needs extra 3D CT scanning, it may find clinical applications in special situations in which extra 3D CT scan is already available or allowed.
This work was supported by the National Research Foundation (NRF) of Korea funded by the Korean government (MEST) (No: 2009-0078310).
- Dobbins JT III, Godfrey DJ: Digital X-ray tomosynthesis: current state of the art and clinical potential. Phy Med Biol 2003, 48: R65–106. 10.1088/0031-9155/48/19/R01View ArticleGoogle Scholar
- Zhao B, Zhao W: Three-dimensional linear system analysis for breast tomosynthesis. Med Phys 2008, 35(12):5219–5232. 10.1118/1.2996014View ArticleGoogle Scholar
- Dobbins JT III, McAdams HP: Chest tomosynthesis: technical principles and clinical update. Eur J Radiol 2009, 72(2):244–251. 10.1016/j.ejrad.2009.05.054View ArticleGoogle Scholar
- Tingberg A: A X-ray tomosynthesis: a review of its use for breast and chest imaging. Radiat Prot Dosimetry 2010, 139(1–3):100–107. 10.1093/rpd/ncq099View ArticleGoogle Scholar
- Grass M, Kohler T, Proksa R: 3D cone-beam CT reconstruction for circular trajectories. Phys Med Biol 2000, 45(2):329–347. 10.1088/0031-9155/45/2/306View ArticleGoogle Scholar
- Wu T, Srewart A, Stanton M, McCauley T, Phillips W, Kopans DB, Moore RH, Eberhard JW, Opsahi-Ong B, Niklason L, Williams MB: Tomographic mammography using a limited number of low-dose cone-beam projection images. Med Phys 2003, 30(3):365–380. 10.1118/1.1543934View ArticleGoogle Scholar
- Zhang Y, Chang H-P, Sahiner B, Wei J, Goodstitt MM, Hadjiiski LM, Ge J, Zhou C: A comparative study of limited-angle cone-beam reconstruction methods for breast tomosynthesis. Med Phys 2006, 33(10):3781–3795. 10.1118/1.2237543View ArticleGoogle Scholar
- Hu Y-H, Zhao B, Zhao W: Image artifacts in digital tomosynthesis: investigation of the effects of system geometry and reconstruction parameters using a linear system approach. Med Phys 2008, 35(12):5242–52. 10.1118/1.2996110View ArticleGoogle Scholar
- Jaffray DA, Siewerdsen JH: Cone-beam computed tomography with a flat-panel imager: initial performance characterization. Med Phys 2000, 27(6):1311–23. 10.1118/1.599009View ArticleGoogle Scholar
- Rakowski JT, Dennis MJ: A comparison of reconstruction algorithm for C-arm mammography tomosynthesis. Med Phys 2006, 33(8):3018–3032. 10.1118/1.2219090View ArticleGoogle Scholar
- Chun IK, Cho MH, Lee SC, Cho MH, Lee SY: X-ray micro-tomography system for smallanimal imaging with zoom-in imaging capability. Phys Med Biol 2004, 49(17):3889–3902. 10.1088/0031-9155/49/17/005View ArticleGoogle Scholar
- Cho MH, Chun IK, Lee SC, Cho MH, Lee SY: Trabecular bone thickness measurement using the zoom-in micro tomography technique. Physio Meas 2005, 26(5):667–676. 10.1088/0967-3334/26/5/008View ArticleGoogle Scholar
- Chun IK, Cho MH, Park J-H, Lee SY: In vivo trabecular thickness measurement in cancellous bones: longitudinal rat imaging studies. Physio Meas 2006, 27(8):695–702. 10.1088/0967-3334/27/8/004View ArticleGoogle Scholar
- Lee SC, Kim HK, Chun IK, Cho MH, Lee SY, Cho MH: A flat-panel detector based micro-CT system: performance evaluation for small-animal imaging. Phys Med Biol 2003, 48(24):4173–85. 10.1088/0031-9155/48/24/014View ArticleGoogle Scholar
- Youn H, Han JC, Cho MK, Jan SY, Kim HK, Kim JH, Tanguay J, Cunningham IA: Numerical generation of digital mammograms considering imaging characteristics of an imager. Nucl Instrum Meth A 2011, 652(1):810–814. 10.1016/j.nima.2010.09.088View ArticleGoogle Scholar
- Feldkamp LA, Davis LC, Kress JW: Practical cone-beam algorithms. J Opt Soc Am 1984, 1(6):612–619. 10.1364/JOSAA.1.000612View ArticleGoogle Scholar
- Bian J, Siewerdsen JH, Han X, Sidky EY, Prince JL, Pelizzari CA, Pan X: Evaluation of sparse-view reconstruction from flat-panel-detector cone-beam CT. Phys Med Biol 2010, 55(22):6575–6599. 10.1088/0031-9155/55/22/001View ArticleGoogle Scholar
- Chen G-H, Tang J, Leng S: Prior image constrained compressed sensing (PICCS): A method to accurately reconstruct dynamic CT images from highly undersampled projection data sets. Med Phys 2008, 35(2):660–663. 10.1118/1.2836423View ArticleGoogle Scholar
- Nett B, Tang J, Leng S, Chen G-H: Tomosynthesis via total variation minimization reconstruction and prior image constrained compressed sensing (PICSS) on a C-arm system. Proc Soc Photo Opt Instrum Eng 2008, 6913. doi:10.1117/12.771294Google Scholar
- Sidky EY, Pan X: Image reconstruction in circular cone-beam computed tomography by constrained, total-variation minimization. Phys Med Biol 2008, 53(17):4777–807. 10.1088/0031-9155/53/17/021View ArticleGoogle Scholar
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