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Biomedical subjects

Hengyong Yu

Publications and source records attributed to Hengyong Yu.

13 recordsLinked to original sources

Data consistency based translational motion artifact reduction in fan-beam CT.

A basic assumption in the classic computed tomography (CT) theory is that an object remains stationary in an entire scan. In biomedical CT/micro-CT, this assumption is often violated. To produce high-resolution images, such as for our recently proposed clinical micro-CT (CMCT) prototype, it is desirable to develop a precise motion estimation and image reconstruction scheme. In this paper, we first extend the Helgason-Ludwig consistency condition (HLCC) from parallel-beam to fan-beam geometry when an object is subject to a translation. Then, we propose a novel method to estimate the motion parameters only from sinograms based on the HLCC. To reconstruct the moving object, we formulate two generalized fan-beam reconstruction methods, which are in filtered backprojection and backprojection filtering formats, respectively. Furthermore, we present numerical simulation results to show that our approach is accurate and robust.

Algorithms↗

Cone-beam mammo-computed tomography from data along two tilting arcs.

Over the past several years there has been an increasing interest in cone-beam computed tomography (CT) for breast imaging. In this article, we propose a new scheme for theoretically exact cone-beam mammo-CT and develop a corresponding Katsevich-type reconstruction algorithm. In our scheme, cone-beam scans are performed along two tilting arcs to collect a sufficient amount of information for exact reconstruction. In our algorithm, cone-beam data are filtered in a shift-invariant fashion and then weighted backprojected into the three-dimensional space for the final reconstruction. Our approach has several desirable features, including tolerance of axial data truncation, efficiency in sequential/parallel implementation, and accuracy for quantitative analysis. We also demonstrate the system performance and clinical utility of the proposed technique in numerical simulations.

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Practical cone-beam lambda tomography.

As a potentially important technology for medical x-ray computed tomography (CT), lambda tomography (LT) is to reconstruct a gradient-like image only from local projection data. Based on our recently derived exact fan-beam LT formula, [H. Y. Gu and G. Wang, Int. J. Biomed. Imaging 2006(1), 1-9 (2006)] here we propose a practical cone-beam LT algorithm for LT reconstruction from local data collected along an arbitrary smooth three-dimensional curve. A key step in our algorithm is to determine an appropriate vector perpendicular to the line connecting the x-ray source and an image point. The algorithm is implemented assuming an equispatial planar detector and a nonstandard spiral trajectory. The numerical simulation results demonstrate the merits of our method.

Algorithms↗

A differentiable Shepp-Logan phantom and its applications in exact cone-beam CT.

Recently, several exact cone-beam reconstruction algorithms, such as the generalized filtered-backprojection (FBP) and backprojection-filtration (BPF) methods, have been developed to solve the long object problem. Although the well-known 3D Shepp-Logan phantom (SLP) is often used to validate these algorithms, it is deficient due to the discontinuity of the SLP. In this paper, we first construct a differentiable polynomial function to approximate the unit rectangular function on [-1, 1]. Then, we use this function to obtain a differentiable ellipsoid phantom, whose x-ray transform is differentiable for any smooth scanning trajectory. Finally, we propose a differentiable Shepp-Logan phantom (DSLP) for numerical simulation of the exact cone-beam CT algorithms. Our numerical simulation shows that the reconstructed DSLP has a better image quality than the reconstructed SLP, and is complementary to the traditional SLP for evaluation of the exact cone-beam CT algorithms.

Algorithms↗

A backprojection-filtration algorithm for nonstandard spiral cone-beam CT with an n-PI-window.

For applications in bolus-chasing computed tomography (CT) angiography and electron-beam micro-CT, the backprojection-filtration (BPF) formula developed by Zou and Pan was recently generalized by Ye et al to reconstruct images from cone-beam data collected along a rather flexible scanning locus, including a nonstandard spiral. A major implication of the generalized BPF formula is that it can be applied for n-PI-window-based reconstruction in the nonstandard spiral scanning case. In this paper, we design an n-PI-window-based BPF algorithm, and report the numerical simulation results with the 3D Shepp-Logan phantom and Defrise disk phantom. The proposed BPF algorithm consists of three steps: cone-beam data differentiation, weighted backprojection and inverse Hilbert filtration. Our simulated results demonstrate the feasibility and merits of the proposed algorithm.

Algorithms↗

Design, analysis and simulation for development of the first clinical micro-CT scanner.

In this article, we propose to develop the first clinical micro-CT (CMCT) system for human temporal bone imaging in vivo. This CMCT system consists of medical CT and micro-CT scanners either as separate components or in a combination, a cross-modality registration mechanism such as a facial surface scanner, and associated software. This system integrates the strengths of state-of-the-art medical CT and micro-CT techniques to achieve a spatial resolution that is much higher than currently available for inner ear imaging at acceptable dose levels. Our design, analysis, and simulation results demonstrate that the CMCT system is feasible for inner ear imaging and other clinical applications. For example, the CMCT system has the potential to improve the safety of guiding cochlear implant electrodes within the inner ear and assist the placement of inner ear microcatheters for delivery of gene modification therapy or administration of neurotrophic factors. Imaging of microarchitectures of the cancellous bone would be also an important application.

Animals↗

A general exact reconstruction for cone-beam CT via backprojection-filtration.

In this paper, we prove a generalized backprojection-filtration formula for exact cone-beam image reconstruction with an arbitrary scanning locus. Our proof is independent of the shape of the scanning locus, as long as the object is contained in a region where there is a chord through any interior point. As special cases, this generalized formula can be applied with cone-beam scanning along nonstandard spiral and saddle curves, as well as in an n-PI window setting. The algorithmic implementation and numerical results are described to support the correctness of our general claim.

Algorithms↗

A unified framework for exact cone-beam reconstruction formulas.

In this paper, we present concise proofs of several recently developed exact cone-beam reconstruction methods in the Tuy inversion framework, including both filtered-backprojection and backprojection-filtration formulas in the cases of standard spiral, nonstandard spiral, and more general scanning loci. While a similar proof of the Katsevich formula was previously reported, we present a new proof of the Zou and Pan backprojection-filtration formula. Our proof combines both odd and even data extensions so that only the cone-beam transform itself is utilized in the backprojection-filtration inversion. More importantly, our formulation is valid for general smooth scanning curves, in agreement with an earlier paper from our group [Ye, Zhao, Yu, and Wang, Proc. SPIE 5535, 293-300 (Aug. 6 2004)]. As a consequence of that proof, we obtain a new inversion formula, which is in a two-dimensional filtering backprojection format. A possibility for generalization of the Katsevich filtered-backprojection reconstruction method is also discussed from the viewpoint of this framework.

Algorithms↗

Exact BPF and FBP algorithms for nonstandard saddle curves.

A hot topic in cone-beam CT research is exact cone-beam reconstruction from a general scanning trajectory. Particularly, a nonstandard saddle curve attracts attention, as this construct allows the continuous periodic scanning of a volume-of-interest (VOI). Here we evaluate two algorithms for reconstruction from data collected along a nonstandard saddle curve, which are in the filtered backprojection (FBP) and backprojection filtration (BPF) formats, respectively. Both the algorithms are implemented in a chord-based coordinate system. Then, a rebinning procedure is utilized to transform the reconstructed results into the natural coordinate system. The simulation results demonstrate that the FBP algorithm produces better image quality than the BPF algorithm, while both the algorithms exhibit similar noise characteristics.

Algorithms↗

Feldkamp-type VOI reconstruction from super-short-scan cone-beam data.

Based on the fan-beam reconstruction formula recently developed by Noo et al. [Phys. Med. Biol. 47, 2525-2546 (2002)] we develop a Feldkamp-type algorithm for the reconstruction of a volume of interest (VOI) from super-short-scan data. With either a circular or spiral scanning locus in our VOI reconstruction scheme, we first estimate fan-beam data from cone-beam data using the popular "cosine correction" scheme, and perform reconstruction based on Noo's FBP-type fan-beam reconstruction. Our proposed algorithm is tested using the three-dimensional (3-D) Shepp-Logan phantom. The experimental results show that the new algorithm can be applied to multi-source 4-D CT with significantly superior temporal resolution and temporal consistency relative to the Katsevich algorithm, which is the state of the art for exact helical cone-beam reconstruction.

Algorithms↗

[Review of evaluation techniques for medical image reconstruction].

This article reviews the research progress in qualitative evaluation of medical image reconstruction, especially the binary image reconstruction. According to the affected point and evaluation character, the evaluation criteria are classified into four categories. Based on the brief introduction of all kinds of evaluation criteria, the paper makes an analytical comparison, and points out their merit and fault. This study provides a useful basis for selection and design of medical image reconstruction algorithms.

Algorithms↗

[Slice reconstruction of 3D vessel based on object-oriented quantization].

Aiming at the problem of inaccurate imaging model of three-dimensional (3D) reconstruction of rotational digital subtraction angiography (DSA), a nonlinear model based on object-oriented quantization is introduced first. The model quantizes the projection pixel of 3D vessel slice as the number of vessels which the X-ray goes through. Furthermore, a slice reconstruction algorithm named segment self-guide reconstruction (SSGR) is developed. The SSGR is especially suitable for solving the problem of sparse projection and limited-views. Finally, the simulated results have proved the feasibility of the model and the validity of the algorithm.

Algorithms↗

Projection-based bolus detection for computed tomographic angiography.

Computed tomographic (CT) angiography is important for imaging studies on cardiovascular structures, peripheral vessels, and solid organs. In practice, a CT angiography scan is triggered by the bolus arrival at a prespecified anatomical location, which is determined using CT fluoroscopy. In this article, we propose a projection-based method adapted from the Grangeat formula to detect the bolus arrival. Then, we evaluate our new method in numerical and animal studies. Our results indicate that this method allows significantly better temporal resolution and is computationally more efficient, as compared with the image-based methods.

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