Biomedical subjects

Zhengrong Liang

Publications and source records attributed to Zhengrong Liang.

13 recordsLinked to original sources

PubMed2006

An improved electronic colon cleansing method for detection of colonic polyps by virtual colonoscopy.

Electronic colon cleansing (ECC) aims to segment the colon lumen from a patient abdominal image acquired using an oral contrast agent for colonic material tagging, so that a virtual colon model can be constructed. Virtual colonoscopy (VC) provides fly-through navigation within the colon model, looking for polyps on the inner surface in a manner analogous to that of fiber optic colonoscopy. We have built an ECC pipeline for a commercial VC navigation system. In this paper, we present an improved ECC method. It is based on a partial-volume (PV) image-segmentation framework, which is derived using the well-established statistical expectation-maximization algorithm. The presented ECC method was evaluated by both visual inspection and computer-aided detection of polyps (CADpolyp) within the cleansed colon lumens obtained using 20 patient datasets. Compared to our previous ECC pipeline, which does not sufficiently consider the PV effect, the method presented in this paper demonstrates improved polyp detection by both visual judgment and CADpolyp measure.

Algorithms↗

PubMed2006

Noise Reduction for Low-Dose Single-Slice Helical CT Sinograms.

Helical computed tomography (HCT) has several advantages over conventional step-and-shoot CT for imaging a relatively large object, especially for dynamic studies. However, HCT may increase X-ray exposure significantly. This work aims to reduce the radiation by lowering X-ray tube current (mA) and filtering low-mA (or dose) sinogram noise of HCT. The noise reduction method is based on three observations on HCT: (1) the axial sampling of HCT projections is nearly continuous as detection system rotates; (2) the noise distribution in sinogram space is nearly a Gaussian after system calibration (including logarithmic transform); and (3) the relationship between the calibrated data mean and variance can be expressed as an exponential functional across the field-of-view. Based on the second and third observations, a penalized weighted least-squares (PWLS) solution is an optimal choice, where the weight is given by the mean-variance relationship. The first observation encourages the use of Karhunen-Loève (KL) transform along the axial direction because of the associated correlation. In the KL domain, the eigenvalue of each principal component and the derived data variance provide the signal-to-noise ratio (SNR) information, resulting in a SNR-adaptive noise reduction. The KL-PWLS noise-reduction method was implemented analytically for efficient restoration of large volume HCT sinograms. Simulation studies showed a noticeable improvement, in terms of image quality and defect detectability, of the proposed noise-reduction method over the Ordered-Subsets Expectation-Maximization reconstruction and the conventional low-pass noise filtering with optimal cutoff frequency and/or other filter parameters.

Journal Article↗

PubMed2006

An inversion formula for the exponential radon transform in spatial domain with variable focal-length fan-beam collimation geometry.

Inverting the exponential Radon transform has a potential use for SPECT (single photon emission computed tomography) imaging in cases where a uniform attenuation can be approximated, such as in brain and abdominal imaging. Tretiak and Metz derived in the frequency domain an explicit inversion formula for the exponential Radon transform in two dimensions for parallel-beam collimator geometry. Progress has been made to extend the inversion formula for fan-beam and varying focal-length fan-beam (VFF) collimator geometries. These previous fan-beam and VFF inversion formulas require a spatially variant filtering operation, which complicates the implementation and imposes a heavy computing burden. In this paper, we present an explicit inversion formula, in which a spatially invariant filter is involved. The formula is derived and implemented in the spatial domain for VFF geometry (where parallel-beam and fan-beam geometries are two special cases). Phantom simulations mimicking SPECT studies demonstrate its accuracy in reconstructing the phantom images and efficiency in computation for the considered collimator geometries.

Algorithms↗

PubMed2006

Reconstruction for proton computed tomography by tracing proton trajectories: a Monte Carlo study.

Proton computed tomography (pCT) has been explored in the past decades because of its unique imaging characteristics, low radiation dose, and its possible use for treatment planning and on-line target localization in proton therapy. However, reconstruction of pCT images is challenging because the proton path within the object to be imaged is statistically affected by multiple Coulomb scattering. In this paper, we employ GEANT4-based Monte Carlo simulations of the two-dimensional pCT reconstruction of an elliptical phantom to investigate the possible use of the algebraic reconstruction technique (ART) with three different path-estimation methods for pCT reconstruction. The first method assumes a straight-line path (SLP) connecting the proton entry and exit positions, the second method adapts the most-likely path (MLP) theoretically determined for a uniform medium, and the third method employs a cubic spline path (CSP). The ART reconstructions showed progressive improvement of spatial resolution when going from the SLP [2 line pairs (lp) cm(-1)] to the curved CSP and MLP path estimates (5 lp cm(-1)). The MLP-based ART algorithm had the fastest convergence and smallest residual error of all three estimates. This work demonstrates the advantage of tracking curved proton paths in conjunction with the ART algorithm and curved path estimates.

Algorithms↗

PubMed2005

FBP Algorithms for Attenuated Fan-Beam Projections.

A filtered backprojection (FBP) reconstruction algorithm for attenuated fan-beam projections has been derived based on Novikov's inversion formula. The derivation uses a common transformation between parallel-beam and fan-beam coordinates. The filtering is shift-invariant. Numerical evaluation of the FBP algorithm is presented as well. As a special application, we also present a shift-invariant FBP algorithm for fan-beam SPECT reconstruction with uniform attenuation compensation. Several other fan-beam reconstruction algorithms are also discussed. In the attenuation-free case, our algorithm reduces to the conventional fan-beam FBP reconstruction algorithm.

Journal Article↗

PubMed2005

Evaluation of an efficient compensation method for quantitative fan-beam brain SPECT reconstruction.

Fan-beam collimators are designed to improve the system sensitivity and resolution for imaging small objects such as the human brain and breasts in single photon emission computed tomography (SPECT). Many reconstruction algorithms have been studied and applied to this geometry to deal with every kind of degradation factor. This paper presents a new reconstruction approach for SPECT with circular orbit, which demonstrated good performance in terms of both accuracy and efficiency. The new approach compensates for degradation factors including noise, scatter, attenuation, and spatially variant detector response. Its uniform attenuation approximation strategy avoids the additional transmission scan for the brain attenuation map, hence reducing the patient radiation dose and furthermore simplifying the imaging procedure. We evaluate and compare this new approach with the well-established ordered-subset expectation-maximization iterative method, using Monte Carlo simulations. We perform quantitative analysis with regional bias-variance, receiver operating characteristics, and Hotelling trace studies for both methods. The results demonstrate that our reconstruction strategy has comparable performance with a significant reduction of computing time.

Algorithms↗

PubMed2005

An efficient reconstruction method for nonuniform attenuation compensation in nonparallel beam geometries based on Novikov's explicit inversion formula.

This paper investigates an accurate reconstruction method to invert the attenuated Radon transform in nonparallel beam (NPB) geometries. The reconstruction method contains three major steps: 1) performing one-dimensional phase-shift rebinning; 2) implementing nonuniform Hilbert transform; and 3) applying Novikov's explicit inversion formula. The method seems to be adaptive to different settings of fan-beam geometry from very long to very short focal lengths without sacrificing reconstruction accuracy. Compared to the conventional bilinear rebinning technique, the presented method showed a better spatial resolution, as measured by modulation transfer function. Numerical experiments demonstrated its computational efficiency and stability to different levels of Poisson noise. Even with complicated geometries such as varying focal-length and asymmetrical fan-beam collimation, the presented method achieved nearly the same reconstruction quality of parallel-beam geometry. This effort can facilitate quantitative reconstruction of single photon emission computed tomography for cardiac imaging, which may need NPB collimation geometries and require high computational efficiency.

Algorithms↗

PubMed2005

Speedup OS-EM Image Reconstruction by PC Graphics Card Technologies for Quantitative SPECT with Varying Focal-Length Fan-Beam Collimation.

In the paper, we present a new hardware acceleration method to speedup the ordered-subsets expectation-maximization (OS-EM) algorithm for quantitative SPECT (single photon emission computed tomography) image reconstruction with varying focal-length fan-beam (VFF) collimation. By utilizing the geometrical symmetry of VFF point-spread function (PSF), compensation for object-specific attenuation and system-specific PSF are accelerated using currently available PC video/graphics card technologies. A ten-fold acceleration of quantitative SPECT reconstruction is achieved.

Journal Article↗

PubMed2005

Partial volume segmentation of brain magnetic resonance images based on maximum a posteriori probability.

Noise, partial volume (PV) effect, and image-intensity inhomogeneity render a challenging task for segmentation of brain magnetic resonance (MR) images. Most of the current MR image segmentation methods focus on only one or two of the above-mentioned effects. The objective of this paper is to propose a unified framework, based on the maximum a posteriori probability principle, by taking all these effects into account simultaneously in order to improve image segmentation performance. Instead of labeling each image voxel with a unique tissue type, the percentage of each voxel belonging to different tissues, which we call a mixture, is considered to address the PV effect. A Markov random field model is used to describe the noise effect by considering the nearby spatial information of the tissue mixture. The inhomogeneity effect is modeled as a bias field characterized by a zero mean Gaussian prior probability. The well-known fuzzy C-mean model is extended to define the likelihood function of the observed image. This framework reduces theoretically, under some assumptions, to the adaptive fuzzy C-mean (AFCM) algorithm proposed by Pham and Prince. Digital phantom and real clinical MR images were used to test the proposed framework. Improved performance over the AFCM algorithm was observed in a clinical environment where the inhomogeneity, noise level, and PV effect are commonly encountered.

Algorithms↗

PubMed2005

An alternative solution to the nonuniform noise propagation problem in fan-beam FBP image reconstruction.

It has been observed that the variances in reconstructed images from stationary noisy projection data by fan-beam filtered backprojection (fFBP) algorithm with ramp in the filtering step and linear interpolation in the backprojection step are nonuniform across the field-of-view. This is believed to be caused by the distance-dependent 1/L2 factor in the fFBP reconstruction formula. Shift-variant filtration approach in the filtering step has been investigated to address the nonuniform noise propagation problem in fFBP. In this work, we present an alternative solution by the use of spatially variant weighting, instead of spatially invariant interpolation, in the backprojection step, while maintaining the homogeneous ramp filtering. Both theoretically predicted and empirically determined results concur and demonstrate the effectiveness of the presented alternative solution.

Algorithms↗

PubMed2005

Reduction of false positives by internal features for polyp detection in CT-based virtual colonoscopy.

In this paper, we present a computer-aided detection (CAD) method to extract and use internal features to reduce false positive (FP) rate generated by surface-based measures on the inner colon wall in computed tomographic (CT) colonography. Firstly, a new shape description global curvature, which can provide an overall shape description of the colon wall, is introduced to improve the detection of suspicious patches on the colon wall whose geometrical features are similar to that of the colonic polyps. By a ray-driven edge finder, the volume of each detected patch is extracted as a fitted ellipsoid model. Within the ellipsoid model, CT image density distribution is analyzed. Three types of (geometrical, morphological, and textural) internal features are extracted and applied to eliminate the FPs from the detected patches. The presented CAD method was tested by a total of 153 patient datasets in which 45 patients were found with 61 polyps of sizes 4-30 mm by optical colonoscopy. For a 100% detection sensitivity (on polyps), the presented CAD method had an average FPs of 2.68 per patient dataset and eliminated 93.1% of FPs generated by the surface-based measures. The presented CAD method was also evaluated by different polyp sizes. For polyp sizes of 10-30 mm, the method achieved mean number of FPs per dataset of 2.0 with 100% sensitivity. For polyp sizes of 4-10 mm, the method achieved 3.44 FP per dataset with 100% sensitivity.

Biophysical Phenomena↗

PubMed2002

Automatic centerline extraction for virtual colonoscopy.

In this paper, we introduce a concise and concrete definition of an accurate colon centerline and provide an efficient automatic means to extract the centerline and its associated branches (caused by a forceful touching of colon and small bowel or a deep fold in twisted colon lumen). We further discuss its applications on fly-through path planning and endoscopic simulation, as well as its potential to solve the challenging touching and colon collapse problems in virtual colonoscopy. Experimental results demonstrated its centeredness, robustness, and efficiency.

Algorithms↗

PubMed2000

Penalized weighted least-squares image reconstruction for dual energy X-ray transmission tomography.

We present a dual-energy (DE) transmission computed tomography (CT) reconstruction method. It is statistically motivated and features nonnegativity constraints in the density domain. A penalized weighted least squares (PWLS) objective function has been chosen to handle the non-Poisson noise added by amorphous silicon (aSi:H) detectors. A Gauss-Seidel algorithm has been used to minimize the objective function. The behavior of the method in terms of bias/standard deviation tradeoff has been compared to that of a DE method that is based on filtered back projection (FBP). The advantages of the DE PWLS method are largest for high noise and/or low flux cases. Qualitative results suggest this as well. Also, the reconstructed images of an object with opaque regions are presented. Possible applications of the method are: attenuation correction for positron emission tomography (PET) images, various quantitative computed tomography (QCT) methods such as bone mineral densitometry (BMD), and the removal of metal streak artifacts.

Algorithms↗