Deep Efficient End-to-end Reconstruction (DEER) Network for Few-view Breast CT Image Reconstruction.

Breast CT provides image volumes with isotropic resolution in high contrast, enabling detection of small calcification (down to a few hundred microns in size) and subtle density differences. Since breast is sensitive to x-ray radiation, dose reduction of breast CT is an important topic, and for this purpose, few-view scanning is a main approach. In this article, we propose a Deep Efficient End-to-end Reconstruction (DEER) network for few-view breast CT image reconstruction. The major merits of our network include high dose efficiency, excellent image quality, and low model complexity. By the design, the proposed network can learn the reconstruction process with as few as O ( N ) parameters, where N is the side length of an image to be reconstructed, which represents orders of magnitude improvements relative to the state-of-the-art deep-learning-based reconstruction methods that map raw data to tomographic images directly. Also, validated on a cone-beam breast CT dataset prepared by Koning Corporation on a commercial scanner, our method demonstrates a competitive performance over the state-of-the-art reconstruction networks in terms of image quality. The source code of this paper is available at: https://github.com/HuidongXie/DEER.

Evaluation of differential phase contrast cone beam CT imaging system.

Grating-based differential phase contrast (DPC) imaging enables the use of a hospital-grade X-ray tube, but compromises the image quality due to insufficiently coherent illumination. In this research, a bench-top DPC cone beam CT (DPC-CBCT) was systematically evaluated and compared with the traditional attenuation-based CBCT in terms of contrast to noise ratio, noise property, and contrast resolution through phantom studies. In order to evaluate DPC-CBCT for soft tissue imaging, breast specimen and small animal studies were carried out. Phantom studies indicate that phase image has lower-frequency noise, higher CNR, and improved contrast resolution. However, phase image quality was degraded in soft tissue imaging due to coherence loss caused by small-angle scattering. Hence dark-field imaging was introduced to quantitatively investigate small-angle scattering caused by an object. Experimental results indicate that inhomogeneous objects affect phase contrast imaging, phase image is more sensitive to noise, and its performance is material dependent. Dark-field imaging could also be used to locate and reduce phase image noise and artifact caused by small-angle scattering.

Cone beam breast CT with multiplanar and three dimensional visualization in differentiating breast masses compared with mammography.

OBJECTIVE: This pilot study was to evaluate cone beam breast computed tomography (CBBCT) with multiplanar and three dimensional (3D) visualization in differentiating breast masses in comparison with two-view mammograms. METHODS: Sixty-five consecutive female patients (67 breasts) were scanned by CBBCT after conventional two-view mammography (Hologic, Motarget, compression factor 0.8). For CBBCT imaging, three hundred (1024 × 768 × 16b) two-dimensional (2D) projection images were acquired by rotating the x-ray tube and a flat panel detector (FPD) 360 degree around one breast. Three-dimensional CBBCT images were reconstructed from the 2D projections. Visage CS 3.0 and Amira 5.2.2 were used to visualize reconstructed CBBCT images. RESULTS: Eighty-five breast masses in this study were evaluated and categorized under the breast imaging reporting and data system (BI-RADS) according to plain CBBCT images and two-view mammograms, respectively, prior to biopsy. BI-RADS category of each breast was compared with biopsy histopathology. The results showed that CBBCT with multiplanar and 3D visualization would be helpful to identify the margin and characteristics of breast masses. The category variance ratios for CBBCT under the BI-RADS were 23.5% for malignant tumors (MTs) and 27.3% for benign lesions in comparison with pathology, which were evidently closer to the histopathology results than those of two-view mammograms, p value <0.01. With the receiver operating characteristic (ROC) curve analysis, the area under the curve (AUC) of CBBCT was 0.911, larger than that (AUC 0.827) of two-view mammograms, p value <0.01. CONCLUSION: CBBCT will be a distinctive noninvasive technology in differentiating and categorizing breast masses under BI-RADS. CBBCT may be considerably more effective to identify breast masses, especially some small, uncertain or multifocal masses than conventional two-view mammography.

Investigating the use of texture features for analysis of breast lesions on contrast-enhanced cone beam CT.

Cone beam computed tomography (CBCT) has found use in mammography for imaging the entire breast with sufficient spatial resolution at a radiation dose within the range of that of conventional mammography. Recently, enhancement of lesion tissue through the use of contrast agents has been proposed for cone beam CT. This study investigates whether the use of such contrast agents improves the ability of texture features to differentiate lesion texture from healthy tissue on CBCT in an automated manner. For this purpose, 9 lesions were annotated by an experienced radiologist on both regular and contrast-enhanced CBCT images using two-dimensional (2D) square ROIs. These lesions were then segmented, and each pixel within the lesion ROI was assigned a label - lesion or non-lesion, based on the segmentation mask. On both sets of CBCT images, four three-dimensional (3D) Minkowski Functionals were used to characterize the local topology at each pixel. The resulting feature vectors were then used in a machine learning task involving support vector regression with a linear kernel (SVRlin) to classify each pixel as belonging to the lesion or non-lesion region of the ROI. Classification performance was assessed using the area under the receiver-operating characteristic (ROC) curve (AUC). Minkowski Functionals derived from contrast-enhanced CBCT images were found to exhibit significantly better performance at distinguishing between lesion and non-lesion areas within the ROI when compared to those extracted from CBCT images without contrast enhancement (p < 0.05). Thus, contrast enhancement in CBCT can improve the ability of texture features to distinguish lesions from surrounding healthy tissue.

Enhancement of breast calcification visualization and detection using a modified PG method in Cone Beam Breast CT.

Cone Beam Breast CT is a promising diagnostic modality in breast imaging. Its isotropic 3D spatial resolution enhances the characterization of micro-calcifications in breasts that might not be easily distinguishable in mammography. However, due to dose level considerations, it is beneficial to further enhance the visualization of calcifications in Cone Beam Breast CT images that might be masked by noise. In this work, the Papoulis-Gerchberg method was modified and implemented in Cone Beam Breast CT images to improve the visualization and detectability of calcifications. First, the PG method was modified and applied to the projections acquired during the scanning process; its effects on the reconstructed images were analyzed by measuring the Modulation Transfer Function and the Noise Power Spectrum. Second, Cone Beam Breast CT images acquired at different dose levels were pre-processed using this technique to enhance the visualization of calcification. Finally, a computer-aided diagnostic algorithm was utilized to evaluate the efficacy of this method to improve calcification detectability. The results demonstrated that this technique can effectively improve image quality by improving the Modulation Transfer Function with a minor increase in noise level. Consequently, the visualization and detectability of calcifications were improved in Cone Beam Breast CT images. This technique was also proved to be useful in reducing the x-ray dose without degrading visualization and detectability of calcifications.

Dynamic cone beam CT angiography of carotid and cerebral arteries using canine model.

PURPOSE: This research is designed to develop and evaluate a flat-panel detector-based dynamic cone beam CT system for dynamic angiography imaging, which is able to provide both dynamic functional information and dynamic anatomic information from one multirevolution cone beam CT scan. METHODS: A dynamic cone beam CT scan acquired projections over four revolutions within a time window of 40 s after contrast agent injection through a femoral vein to cover the entire wash-in and wash-out phases. A dynamic cone beam CT reconstruction algorithm was utilized and a novel recovery method was developed to correct the time-enhancement curve of contrast flow. From the same data set, both projection-based subtraction and reconstruction-based subtraction approaches were utilized and compared to remove the background tissues and visualize the 3D vascular structure to provide the dynamic anatomic information. RESULTS: Through computer simulations, the new recovery algorithm for dynamic time-enhancement curves was optimized and showed excellent accuracy to recover the actual contrast flow. Canine model experiments also indicated that the recovered time-enhancement curves from dynamic cone beam CT imaging agreed well with that of an IV-digital subtraction angiography (DSA) study. The dynamic vascular structures reconstructed using both projection-based subtraction and reconstruction-based subtraction were almost identical as the differences between them were comparable to the background noise level. At the enhancement peak, all the major carotid and cerebral arteries and the Circle of Willis could be clearly observed. CONCLUSIONS: The proposed dynamic cone beam CT approach can accurately recover the actual contrast flow, and dynamic anatomic imaging can be obtained with high isotropic 3D resolution. This approach is promising for diagnosis and treatment planning of vascular diseases and strokes.

Investigation of Moiré Pattern-based Phase Retrieval Approach for Differential Phase-contrast Cone Beam CT Imaging Using a Hospital-grade Tube.

The phase stepping algorithm is commonly used for phase retrieval in grating-based differential phase-contrast (DPC) imaging, which requires multiple intensity images to compute one DPC image. It is not efficient for data acquisition, especially in the case of dynamic imaging using either DPC imaging or DPC-based come beam CT (DPC-CBCT) imaging. A Fourier transform-based approach has been developed for fringe pattern analysis in optics, and it was recently implemented into a synchrotron-based DPC tomography system. In this research, this approach is further developed for a bench-top DPC-CBCT imaging system with a hospital-grade x-ray tube. The key idea is to separate carrier fringes and object information in Fourier domain of the interferogram and to reconstruct the differentiated phase information using the object information. Only one interferogram is required for phase retrieval at a cost of spatial resolution. The fringes of moiré patterns are used as the carrier fringes, and a phantom is scanned to evaluate the approach. Various interferograms with different carrier fringe frequencies are investigated and the reconstruction image quality is evaluated in terms of contrast, noise and sharpness. The results indicated that the DPC images can be effectively retrieved using the Fourier transform-based approach and the reconstructed phase coefficient showed better contrast compared to that of attenuation-based contrast. The spatial resolution is acceptable in the phantom studies although it is not as good as the results of phase-stepping approach. The Fourier transform-based phase retrieval approach is able to greatly simplify data acquisition, to improve the temporal resolution and to make it possible for dynamic DPC-CBCT imaging. It is promising for perfusion imaging where spatial resolution is not a concern.

Investigation of Source Grating Stepping for Differential Phase-contrast Cone Beam CT (DPC-CBCT) System.

Differential phase contrast (DPC) imaging, which utilizes phase shift information of X-ray, has the potential of dramatically increasing the contrast in biological sample imaging compared to attenuation-based method that relies on X-ray absorption information, since the X-ray phase is much more sensitive than the attenuation during transmission. In a DPC imaging system, the phase stepping method is widely used to obtain DPC images: at each angle the phase grating is shifted incrementally to produce a set of images and then the so obtained images are used to retrieve DPC image. However, DPC imaging requires a high mechanical precision to perform phase stepping, which is generally one order higher than the period of phase grating. Given that phase grating period is generally 2-4 um, the requirement of mechanical accuracy and stability are very demanding (<0.5um) and difficult to meet in a system with rotating gantry. In this paper, we present a method that is able to greatly relax the requirement of mechanical accuracy and stability by stepping the source grating rather than the analyzer grating. This method is able to increase the system's mechanical tolerance without compromising image quality and make it feasible to install the system on a rotating gantry to perform differential phase-contrast cone beam CT (DPC-CBCT). It is also able to increase the grating shifting precision and as a result improve the reconstructed image quality. Mechanical tolerance investigation and image quality investigation at different phase stepping schemes and different dose levels will be carried out on both the original modality and the new modality, the results will be evaluated and compared. We will deliberately create random mechanical errors in phase stepping and evaluate the resulting DPC images and DPC-CBCT reconstructions. The contrast, noise level and sharpness will be evaluated to assess the influence of mechanical errors. By stepping the source grating, the system is expected to tolerate an error of 6-7 times bigger than that with analyzer grating stepping.

Performance Investigation of a Hospital-grade X-ray Tube-based Differential Phase-contrast Cone Beam CT System.

Differential phase contrast technique could be the next breakthrough in the field of CT imaging. While traditional absorption-based X-ray CT imaging is inefficient at differentiating soft tissues, phase-contrast technique offers great advantage as being able to produce higher contrast images utilizing the phase information of objects. Our long term goal is to develop a gantry-based hospital-grade X-ray tube differential phase contrast cone-beam CT (DPC-CBCT) technology which is able to achieve higher contrast noise ratio (CNR) in soft tissue imaging without increasing the dose level. Based on the micro-focus system built last year, a bench-top hospital-grade X-ray tube DPC-CBCT system is designed and constructed. The DPC-CBCT system consists of an X-ray source, i.e. a hospital-grade X-ray tube and a source grating, a high-resolution detector, a rotating phantom holder, a phase grating and an analyzer grating. Three-dimensional (3-D) phase-coefficients are reconstructed, providing us with images enjoying higher CNR than, yet equivalent dose level to, a conventional CBCT scan. Three important aspects of the system are investigated: a) The The system's performance in term of CNR of the reconstruction image with regard to dose levels, b) the impacts of different phase stepping schemes, i.e. 5 steps to 8 steps, in term of CNR on the reconstruction images, and c) the influence of magnification or position of the phantom on image quality, chiefly CNR. The investigations are accomplished via phantom study.

Scatter correction for clinical cone beam CT breast imaging based on breast phantom studies.

In flat-panel detector-based cone beam CT breast imaging (CBCTBI) systems, scattering is an important factor that degrades image quality. It is not practical to measure the scattering profiles of a breast for all view angles in a patient study, but it is possible to develop a method to estimate the scattering profiles based on information acquired from breast phantom studies. A new scattering correction method is proposed for clinical CBCTBI in this study. The scattering profiles of three anthropomorphic uncompressed breast phantoms of different sizes were thoroughly investigated, and the results indicated that though phantom size differed, the scattering profiles were mainly determined by local breast diameters, which are the approximate diameters of coronal slices that are perpendicular to the nipple-to-chestwall direction. Thus for scattering correction purposes it is possible to establish a relationship between location breast diameters and local scattering profiles, namely the fitted smooth curves of scatter-to-primary ratios (SPR) and normalized scattered radiations (NSR). In clinical CBCTBI studies, after the local breast diameters are sampled and measured on projection images, the scattering image for every projection image can be generated based on the established relationship, and the projection images can be corrected using either the SPR based method or the NSR based method. Phantom studies and clinical studies showed that both the SPR and NSR methods are able to correct cupping artifacts and reduce reconstruction error. The SPR method does not increase tissue contrast or noise while the NSR method increases both.

Performance Evaluation of a Differential Phase-contrast Cone-beam (DPC-CBCT) System for Soft Tissue Imaging.

Differential phase-contrast (DPC) technique is promising as the next breakthrough in the field of X-ray CT imaging. Utilizing the long ignored X-ray phase information, Differential phase-contrast (DPC) technique has the potential of providing us with projection images with higher contrast in a CT scan without increasing the X-ray dose. While traditional absorption-based X-ray imaging is not very efficient at differentiating soft tissues, differential phase-contrast (DPC) is promising as a new method to boast the quality of the CT reconstruction images in term of contrast noise ratio (CNR) in soft tissue imaging. In order to validate and investigate the use of DPC technique in cone-beam CT imaging scheme, a new bench-top micro-focus DPC-based cone-beam computed tomography DPC-CBCT system has been designed and constructed in our lab for soft tissue imaging. The DPC-CBCT system consists of a micro-focus X-ray tube (focal spot 8 µm), a high-resolution detector, a rotating phantom holder and two gratings, i.e. a phase grating and an analysis. The detector system has a phosphor screen, an optical fiber coupling unit and a CMOS chip with an effective pixel pitch of 22.5 microns. The optical elements are aligned to minimize unexpected moiré patterns, and system parameters, including tube voltage (or equivalently X-ray spectrum), distances between gratings, source-to-object distance and object-to-detector distance are chosen as practicable to be applied in a rotating system. The system is tested with two simple phantoms for performance evaluation. 3-D volumetric phase-coefficients are reconstructed. The performance of the system is compared with conventional absorption-based CT in term of contrast noise ratio (CNR) under the condition of equal X-ray dose level.

Cone-beam CT for breast imaging: Radiation dose, breast coverage, and image quality.

OBJECTIVE: The primary objectives of this pilot study were to evaluate the radiation dose, breast coverage, and image quality of cone-beam breast CT compared with a conventional mammographic examination. Image quality analysis was focused on the concordance of cone-beam breast CT with conventional mammography in terms of mammographic findings. SUBJECTS AND METHODS: This prospective study was performed from July 2006 through August 2008. Twenty-three women were enrolled who met the inclusion criteria, which were age 40 years or older with final BI-RADS assessment category 1 or 2 lesions on conventional mammograms within the previous 6 months. The breasts were imaged with a flat-panel detector-based cone-beam CT system, and the images were reviewed with a 3D visualization system. Cone-beam breast CT image data sets and the corresponding mammograms were reviewed by three qualified mammographers. The parameters assessed and compared in this pilot study were radiation dose, breast tissue coverage, and image quality, including detectability of masses and calcifications. The mammograms and cone-beam breast CT images were independently reviewed side by side, and the reviewers were not blinded to the other technique. The observed agreement and Cohen's kappa were used to evaluate agreement between the mammographic and cone-beam breast CT findings and interobserver agreement. Each subject responded to a questionnaire on multiple parameters, including comfort of the cone-beam breast CT examination compared with mammography. RESULTS: For a conventional mammographic examination, the average glandular radiation dose ranged from 2.2 to 15 mGy (mean, 6.5 [SD, 2.9] mGy). For cone-beam breast CT, the average glandular dose ranged from 4 to 12.8 mGy (mean, 8.2 [SD, 1.4] mGy). The average glandular dose from cone-beam breast CT was generally within the range of that from conventional mammography. For heterogeneously dense and extremely dense breasts, the difference between the mean dose of conventional mammography and that of cone-beam breast CT was not statistically significant (7.0 vs 8.1 mGy, p = 0.06). Breast tissue coverage was statistically significantly better with cone-beam breast CT than with mammography in the lateral (p < 0.0001), medial (p < 0.0001), and posterior (p = 0.0002) aspects. Mammography had statistically significantly better coverage than cone-beam breast CT in the axilla and axillary tail (p < 0.0001). Overall, most calcifications and all masses detected with mammography were also detected with cone-beam breast CT. The interobserver agreement on cone-beam breast CT was 83.7% in the detectability of imaging findings. The overall interobserver agreement on type of findings, size of findings (<1, 1-4.99, and > or = 5 mm), and location of findings was 77.2%, 84.8%, and 78.3%, respectively. CONCLUSION: The results of this study show that cone-beam breast CT can be used to image the entire breast from chest wall to nipple with sufficient spatial and contrast resolution for detection of masses and calcifications at a radiation dose within the range of that of conventional mammography.

Measurements of the modulation transfer function, normalized noise power spectrum and detective quantum efficiency for two flat panel detectors: a fluoroscopic and a cone beam computer tomography flat panel detectors.

The physical performance of two Flat Panel Detectors has been evaluated. The first Flat Panel Detector is for Fluoroscopic applications, Varian PaxScan 2520, and the second is for Cone Beam Computer Tomography applications, Varian PaxScan 4030CB. First, the spectrum of the X-ray source was measured. Second, the linearity of the detectors was investigated by using an ionization chamber and the average ADU values of the detectors. Third, the temporal resolution was characterized by evaluating their image lag. Fourth, their spatial resolution was characterized by the pre-sampling Modulation Transfer Function. Fifth, the Normalized Noise Power Spectrum was calculated for various exposures levels. Finally, the Detective Quantum Efficiency was obtained as a function of spatial frequency and entrance exposure. The results illustrate that the physical performance in Detective Quantum Efficiency and Normalized Noise Power Spectrum of the Cone Beam Computer Tomography detector is superior to that of the fluoroscopic detector whereas the latter detector has a higher spatial resolution as demonstrated by larger values of its Modulation Transfer Function at large spatial frequencies.

Cone Beam Breast CT noise reduction using 3D adaptive Gaussian filtering.

In Cone Beam Breast CT (CBBCT) imaging, noise causes degradation of three dimensional breast images, impeding correct diagnosis of breast cancer. Within Feldkamp's cone beam reconstruction framework, applying weighted reconstruction filters to the projection images after pre-processing procedures has long been used to reduce noise and improve image quality. However, CBBCT noise is distributed across frequencies along with the useful signal. Various reconstruction filters working in the frequency domain suppress noise as well as the edge detail signal. Based on fuzzy c-means clustering and the two-dimensional histogram analysis of a large number of clinical CBBCT data, we managed to discriminate fatty stroma, glandular tissues and the transition areas between these tissues by the local mean and standard deviation values. We also proposed a three-dimensional Gaussian filtering scheme to reduce the noise in 3D reconstructed images adaptively without much blurring of detail signal.

NPS characterization and evaluation of a cone beam CT breast imaging system.

The Noise Power Spectrum (NPS) is a function that yields information about the spatial frequency composition of noise in images obtained by a system. It is evaluated by calculating the absolute value squared of the noise image and normalizing it with respect to the voxel and matrix sizes. Consequently, the NPS has been one of the physical characteristics that is commonly used to quantitatively measure the physical performance of a system. In this article, we evaluated the NPS of a Cone Beam CT Breast Imaging system by considering the following factors. First, we evaluated its symmetry around the x- and y-axis along with the influence of the cone angle and the matrix size on the NPS. Then, an analytical curve was suggested to best represent the NPS. Second, we analyzed the influence on the NPS of a set of seven parameters, namely the pixel size, exposure level, kVp value, number of projections acquired, voxel size, back projection filter, and the reconstruction algorithm employed. In addition, since the breast induced scattering in the image, we investigated the effect of the scattering-correction algorithm used in this system. Finally, we evaluated the uniformity of the NPS as a function of z with the matrix center located at {r = 0 mm}. The results demonstrate that the proposed curve is an ideal candidate that best represents the NPS. Hence, two parameters, the amplitude (A) and the width (sigma), can be used to characterize the curve. The results also demonstrate that the voxel size and the cone angle are the only two parameters investigated in this study that do not affect the NPS. On the other hand, the matrix and pixel sizes, the back-projection filter and the reconstruction algorithm, the exposure level and the scattering correction, all influence the NPS. Finally, the results of the last part of this investigation suggest that this imaging system does not have a 3D isotropic noise distribution along the z-axis; yielding less noisy images at around z = 0.00 m and z = 80 mm.

Circle plus partial helical scan scheme for a flat panel detector-based cone beam breast X-ray CT.

Flat panel detector-based cone beam breast CT (CBBCT) can provide 3D image of the scanned breast with 3D isotropic spatial resolution, overcoming the disadvantage of the structure superimposition associated with X-ray projection mammography. It is very difficult for Mammography to detect a small carcinoma (a few millimeters in size) when the tumor is occult or in dense breast. CBBCT featured with circular scan might be the most desirable mode in breast imaging due to its simple geometrical configuration and potential applications in functional imaging. An inherited large cone angle in CBBCT, however, will yield artifacts in the reconstruction images when only a single circular scan is employed. These artifacts usually manifest themselves as density drop and object geometrical distortion that are more noticeable in the reconstructed image areas that are further away from the circular scanning plane. In order to combat this drawback, a circle plus partial helical scan scheme is proposed. An exact circle plus straight line scan scheme is also conducted in computer simulation for the purpose of comparison. Computer simulations using a numerical breast phantom demonstrated the practical feasibility of this new scheme and correction to those artifacts to a certain degree.

Volume fusion for two-circular-orbit cone-beam tomography.

By using the Feldkamp-Davis-Kress (FDK) algorithm, we can efficiently produce a digital volume, called the FDK volume, from cone-beam data acquired along a circular scan orbit. Due to the insufficiency of the cone-beam data set, the FDK volume suffers from nonuniform reproduction exactness. Specifically, the midplane (on the scan-orbit plane) can be exactly reproduced, and the reproduction exactness of off-midplanes decreases as the distance from the midplane increases. We describe the longitudinal falling-off degradation by a hatlike function and the spatial distribution over the object domain by an exactness volume. With two orthogonal circular scan orbits, we can reconstruct two FDK volumes and generate two exactness volumes. We propose a volume fusion scheme to combine the two FDK volumes into a single volume. Let Va and Vb denote the two FDK volumes, let Ea and Eb denote the exactness volumes for orbits Gamma(a) and Gamma(b), respectively, then the volume fusion is defined by Vab=VaWa+VbWb, with Wa=Ea/(Ea+Eb) and Wb=1-Wa. In the result, the overall reproduction exactness of Vab is expected to outperform that of Va, or Vb, or (Va+Vb)/2. In principle, this volume-fusion scheme is applicable for general cone-beam tomography with multiple nonorthogonal and noncircular orbits.

Early detection and measurement of urothelial tumors in mice.

OBJECTIVES: To establish reliable noninvasive in vivo methods to detect, measure, and monitor experimentally induced urothelial tumors in mice. METHODS: UPII-SV40T transgenic mice reliably develop bladder tumors by expression of simian virus 40 large T antigen specifically in bladder urothelium through the use of the uroplakin II promoter. Two wild-type and 10 UPII-SV40T transgenic mice were monitored for microhematuria two to three times weekly using dipstick analysis. A unique flat panel detector-based cone beam computed tomography (FPD-CBCT) system imaged the urinary tracts of anesthetized mice after tail vein injection of an iodinated contrast agent (Omnipaque) that is excreted in urine. Within 10 seconds, the FPD-CBCT system acquired 290 two-dimensional images, which produced three-dimensional volumes with true isotropic resolution (180 microm)3 using a filtered back projection-based modified Feldkamp reconstruction algorithm. Amira, version 3.1.1-1, for MacOSX was used for data analysis and advanced visualization of the three-dimensional reconstructed FPD-CBCT images. RESULTS: Hematuria was present in UPII-SV40T transgenic mice at 32 days of age; the wild-type animals exhibited no hematuria. Filling defects, associated with histologically confirmed tumors, in the bladders of the UPII-SV40T transgenic mice were visualized in the reconstructed FPD-CBCT images 1 to 45 minutes after contrast agent injection. Longitudinal FPD-CBCT imaging sessions showed the tumor position, volume, and growth. CONCLUSIONS: The combination of early detection of hematuria and high-resolution in vivo FPD-CBCT imaging of murine bladder tumors enabled accurate longitudinal assessment of tumor growth and progression in individual animals. This approach could provide an important alternative to serial sacrifice experimental designs, while refining statistical power and reducing animal use.

FDK Half-Scan with a Heuristic Weighting Scheme on a Flat Panel Detector-Based Cone Beam CT (FDKHSCW).

A cone beam circular half-scan scheme is becoming an attractive imaging method in cone beam CT since it improves the temporal resolution. Traditionally, the redundant data in the circular half-scan range is weighted by a central scanning plane-dependent weighting function; FDK algorithm is then applied on the weighted projection data for reconstruction. However, this scheme still suffers the attenuation coefficient drop inherited with FDK when the cone angle becomes large. A new heuristic cone beam geometry-dependent weighting scheme is proposed based on the idea that there exists less redundancy for the projection data away from the central scanning plane. The performance of FDKHSCW scheme is evaluated by comparing it to the FDK full-scan (FDKFS) scheme and the traditional FDK half-scan scheme with Parker's fan beam weighting function (FDKHSFW). Computer simulation is employed and conducted on a 3D Shepp-Logan phantom. The result illustrates a correction of FDKHSCW to the attenuation coefficient drop in the off-scanning plane associated with FDKFS and FDKHSFW while maintaining the same spatial resolution.

Image denoising based on wavelets and multifractals for singularity detection.

This paper presents a very efficient algorithm for image denoising based on wavelets and multifractals for singularity detection. A challenge of image denoising is how to preserve the edges of an image when reducing noise. By modeling the intensity surface of a noisy image as statistically self-similar multifractal processes and taking advantage of the multiresolution analysis with wavelet transform to exploit the local statistical self-similarity at different scales, the pointwise singularity strength value characterizing the local singularity at each scale was calculated. By thresholding the singularity strength, wavelet coefficients at each scale were classified into two categories: the edge-related and regular wavelet coefficients and the irregular coefficients. The irregular coefficients were denoised using an approximate minimum mean-squared error (MMSE) estimation method, while the edge-related and regular wavelet coefficients were smoothed using the fuzzy weighted mean (FWM) filter aiming at preserving the edges and details when reducing noise. Furthermore, to make the FWM-based filtering more efficient for noise reduction at the lowest decomposition level, the MMSE-based filtering was performed as the first pass of denoising followed by performing the FWM-based filtering. Experimental results demonstrated that this algorithm could achieve both good visual quality and high PSNR for the denoised images.