Temporal bone volumetric image deblurring in spiral computed tomography scanning

Airway wall attenuation: a biomarker of airway disease in subjects with COPD

The computed tomographic (CT) densities of imaged structures are a function of the CT scanning protocol, the structure size, and the structure density. For objects that are of a dimension similar to the scanner point spread function, CT will underestimate true structure density. Prior investigation suggests that this process, termed contrast reduction, could be used to estimate the strength of thin structures, such as cortical bone. In this investigation, we endeavored to exploit this process to provide a CT-based measure of airway disease that can assess changes in airway wall thickening and density that may be associated with the mural remodeling process in subjects with chronic obstructive pulmonary disease (COPD). An initial computer-based study using a range of simulated airway wall sizes and densities suggested that CT measures of airway wall attenuation could detect changes in both wall thickness and structure density. A second phantom-based study was performed using a series of polycarbonate tubes of known density. The results of this again demonstrated the process of contrast reduction and further validated the computer-based simulation. Finally, measures of airway wall attenuation, wall thickness, and wall area (WA) divided by total cross-sectional area, WA percent (WA%), were performed in a cohort of 224 subjects with COPD and correlated with spirometric measures of lung function. The results of this analysis demonstrated that wall attenuation is comparable to WA% in predicting lung function on univariate correlation and remain as a statistically significant correlate to the percent forced expiratory volume in 1 s predicted when adjusted for measures of both emphysema and WA%. These latter findings suggest that the quantitative assessment of airway wall attenuation may offer complementary information to WA% in characterizing airway disease in subjects with COPD.

Selective deblurring for improved calcification visualization and quantification in carotid CT angiography: validation using micro-CT

Visualization and quantification of small structures with computed tomography (CT) is hampered by the limited spatial resolution of the system. Histogram-based selective deblurring (HiSD) is a deconvolution method that restores small high-density structures, i.e., calcifications, of a CT image, using the high-intensity voxel information of the deconvolved image, while preserving the original hounsfield Units (HUs) in the remaining tissues. In this study, high resolution micro-CT data are used to validate the potential of HiSD to improve calcium visualization and quantification in the carotid arteries on in vivo contrast-enhanced CTA data. The evaluation is performed qualitatively and quantitatively on 15 atherosclerotic plaques obtained from ten different patients. HiSD in combination with vessel segmentation significantly improves calcification visualization and quantification on in vivo contrast-enhanced CT images. Calcification blur is reduced, while avoiding noise amplification and edge-ringing artifacts in the surrounding tissues. Calcification quantification errors are reduced by 23.5% on average.

Histogram-Based Selective Deblurring to Improve Computed Tomography Imaging of Calcifications

OBJECTIVES

Computed tomography (CT) imaging of small high-density structures, eg, calcifications, is hampered by image blur. This study aims to deconvolve calcifications in the transverse and longitudinal directions while avoiding noise amplification and edge-ringing artifacts in the surrounding low-density structures.

MATERIALS AND METHODS

A method referred to as histogram-based selective deblurring (HiSD) has been developed to generate a restored image by combining the low-intensity (ie, Hounsfield Units) information of the original image with the high-intensity information of the deconvolved image. HiSD is evaluated on phantom and in vitro atherosclerotic plaque CT images by comparing the original and restored images with their corresponding reference micro-CT images both qualitatively and quantitatively.

RESULTS

HiSD reduces calcification blur in the transverse and longitudinal directions without introducing noise and ringing-artifacts in the surrounding tissues. Calcification area and volume measurements are significantly improved in the restored images (reducing on average overestimation by 32% and 83%, respectively).

CONCLUSIONS

HiSD significantly improves CT visualization and quantification of small high-density structures imaged in vitro.

The point spread function of spiral CT

Computed tomography (CT) scanners are usually described by their in-plane resolution and slice-sensitivity profile (SSP). Other imaging systems are characterized by their point spread function (PSF). The PSF is an excellent basis for the analysis, design and enhancement of imaging systems. The 3D PSF of CT systems has rarely been considered, and has usually been approximated by a 3D Gaussian. We present mathematical analysis of the PSF of single-slice and multi-slice fan-beam and cone-beam CT, for major reconstruction algorithms. We show that the PSF has a complicated, non-separable 3D shape. It is anisotropic in the xy plane and twisted in the z direction. Furthermore, the PSF is space variant in all three axes. In particular, it rotates as the input impulse function moves in the z direction. The PSF may also have effective discontinuities that can lead to streaking artefacts. Indirect measurements of the PSF can be misleading. We support the theoretical results by direct experimental measurements of the PSF.

Maximizing quantitative accuracy of lung airway lumen and wall measures obtained from X-ray CT imaging

To objectively quantify airway geometry from three-dimensional computed tomographic (CT) images, an idealized (circular cross section) airway model is parameterized by airway luminal caliber, wall thickness, and tilt angle. Using a two-dimensional CT slice, an initial guess for the airway center, and the full-width-half-maximum principle, we form an estimate of inner and outer airway wall locations. We then fit ellipses to the inner and outer airway walls via a direct least squares fit and use the major and minor axes of the ellipses to estimate the tilt and in-plane rotation angles. Convolving the airway model, initialized with these estimates, with the three-dimensional scanner point-spread function forms the predicted image. The difference between predicted and actual images is minimized by refining the model parameter estimates via a multidimensional, unconstrained, nonlinear minimization routine. When optimization converges, airway model parameters estimate the airway inner and outer radii and tilt angle. Results using a Plexiglas phantom show that tilt angle is estimated to within +/-4 degrees and both inner and outer radii to within one-half pixel when a "standard" CT reconstruction kernel is used. By opening up the ability to measure airways that are not oriented perpendicular to the scanning plane, this method allows evaluation of a greater sampling of airways in a two-dimensional CT slice than previously possible. In addition, by combining the tilt-angle compensation with the deconvolution method, we provide significant improvement over the previous full-width-half-maximum method for assessing location of the luminal edge but not the outer edge of the airway wall.

Three-dimensional modeling and visualization of the cochlea on the Internet

Three-dimensional (3-D) modeling and visualization of the cochlea using the World Wide Web (WWW) is an effective way of sharing anatomic information for cochlear implantation over the Internet, particularly for morphometry-based research and resident training in otolaryngology and neuroradiology. In this paper, 3-D modeling, visualization, and animation techniques are integrated in an interactive and platform-independent manner and implemented over the WWW. Cohen's template shape with mean cross-sectional areas of the human cochlea is extended into a 3-D geometrical model. Also, spiral computer tomography data of a patient's cochlea is digitally segmented and geometrically represented. The cochlear electrode array is synthesized according to its specification. Then, cochlear implantation is animated with both idealized and real cochlear models. Insertion length, angular position, and characteristic frequency of individual electrodes are estimated online during the virtual insertion. The optimization of the processing parameters is done to demonstrate the feasibility of this technology for clinical applications.

Spiral CT image deblurring for cochlear implantation

Cochlear implantation is the standard treatment for profound hearing loss. Preimplantation and postimplantation spiral computed tomography (CT) is essential in several key clinical and research aspects. The maximum image resolution with commercial spiral CT scanners is insufficient to define clearly anatomical features and implant electrode positions in the inner ear. In this paper, we develop an expectation-maximization (EM)-like iterative deblurring algorithm to achieve spiral CT image super-resolution for cochlear implantation, assuming a spatially invariant linear spiral CT system with a three-dimensional (3-D) separable Gaussian point spread function (PSF). We experimentally validate the 3-D Gaussian blurring model via phantom measurement and profile fitting. The imaging process is further expressed as convolution of an isotropic 3-D Gaussian PSF and a blurred underlying volumetric image. Under practical conditions, an oblique reconstructed section is approximated as convolution of an isotropic two-dimensional (2-D) Gaussian PSF and the corresponding actual cross section. The spiral CT image deblurring algorithm is formulated with sieve and resolution kernels for suppressing noise and edge artifacts. A typical cochlear cross section is used for evaluation, demonstrating a resolution gain up to 30%40% according to the correlation criterion. Physical phantoms, preimplantation and postimplantation patients are reconstructed into volumes of 0.1-mm cubic voxels. The patient images are digitally unwrapped along the central axis of the cochlea and the implanted electrode array respectively, then oblique sections orthogonal to the central axis formed. After deblurring, representation of structural features is substantially improved in all the cases.