In this paper, we developed a framework for comparison and optimization of x-ray imaging configurations for x-ray digital tomosynthesis. Digital tomosynthesis is a novel technology to reconstruct three-dimensional information with limited number of low-dose two-dimensional projection images. Breast cancer is the most common cancer among American women. Early breast cancer detection is the best hope to decrease breast cancer mortality. Breast cancer is sometimes found after symptoms appear. Many women with breast cancer have no symptoms. Mammography has long been the leading technology for breast cancer detection. Although mammography has been the primary technology for breast cancer detection, digital tomosynthesis has become increasingly popular for breast cancer detection. In digital breast tomosynthesis imaging fields, most current breast tomosynthesis systems utilize a design where a single x-ray tube moves along an arc above objects over a certain angular range. Parallel imaging configurations is utilized in a few tomosynthesis imaging area such as digital chest tomosynthesis, and multi-beam stationary breast tomosynthesis imaging field as well. In this paper we present the preliminary investigation on computational analysis of impulse response and wire simulation characterization for optimization of digital tomosynthesis imaging configurations using our framework.
Digital tomosynthesis is a novel technology to volumetrically reconstruct three-dimensional information with a finite number of low-dose two-dimensional projection images. In digital breast tomosynthesis imaging fields, most current breast tomosynthesis systems utilize a design where a single x-ray tube moves along an arc above objects over a certain angular range. Parallel imaging configurations also exist with new nanotechnology enabled multi-beam x-ray sources. In this paper, a framework is described for comparison and optimization of imaging configurations for digital tomosynthesis. The framework is designed to allow the flexibility of comparison and optimization of various imaging configurations such as parallel imaging, partial iso-centrical imaging, rectangular imaging, etc., with uniform and non-uniform beam distributions where imaging parameters of x-ray tube and detector can be assigned. The proposed framework may assist in the study of digital tomosynthesis and expand tomosynthesis applications to various diagnostic and interventional procedures.
Distance driven represents a state of art method that used for reconstruction for x-ray techniques. C-arm
tomography is an x-ray imaging technique that provides three dimensional information of the object by
moving the C-shaped gantry around the patient. With limited view angle, C-arm system was investigated to
generate volumetric data of the object with low radiation dosage and examination time. This paper is a new
simulation study with two reconstruction methods based on distance driven including: simultaneous algebraic
reconstruction technique (SART) and Maximum Likelihood expectation maximization (MLEM). Distance
driven is an efficient method that has low computation cost and free artifacts compared with other methods
such as ray driven and pixel driven methods. Projection images of spherical objects were simulated with a
virtual C-arm system with a total view angle of 40 degrees. Results show the ability of limited angle C-arm
technique to generate three dimensional images with distance driven reconstruction.
C-arm tomosynthesis is a three dimensional imaging technique. Both x-ray source and the detector are mounted on a C-arm wheeled structure to provide wide variety of movement around the object. In this paper, C-arm tomosynthesis was introduced to provide three dimensional information over a limited view angle (less than 180o) to reduce radiation exposure and examination time. Reconstruction algorithms based on ray tracing method such as ray tracing back projection (BP), simultaneous algebraic reconstruction technique (SART) and maximum likelihood expectation maximization (MLEM) were developed for C-arm tomosynthesis. C-arm tomosynthesis projection images of simulated spherical object were simulated with a virtual geometric configuration with a total view angle of 40 degrees. This study demonstrated the sharpness of in-plane reconstructed structure and effectiveness of removing out-of-plane blur for each reconstruction algorithms. Results showed the ability of ray tracing based reconstruction algorithms to provide three dimensional information with limited angle C-arm tomosynthesis.
KEYWORDS: Reconstruction algorithms, Signal attenuation, X-rays, Digital breast tomosynthesis, Breast, Mammography, Expectation maximization algorithms, 3D modeling, X-ray detectors, Breast cancer
As a breast-imaging technique, digital breast tomosynthesis has great potential to improve the diagnosis of early breast cancer over mammography. Ray-tracing-based reconstruction algorithms, such as ray-tracing back projection, maximum-likelihood expectation maximization (MLEM), ordered-subset MLEM (OS-MLEM), and simultaneous algebraic reconstruction technique (SART), have been developed as reconstruction methods for different breast tomosynthesis systems. This paper provides a comparative study to investigate these algorithms by computer simulation and phantom study. Experimental results suggested that, among the four investigated reconstruction algorithms, OS-MLEM and SART performed better in interplane artifact removal with a fast speed convergence.
In this paper, distance driven (DD) back projection image reconstruction was investigated for digital tomosysthesis. Digital tomosysthesis is an imaging technique to produce three dimensional information of the object with low radiation dosage. This paper is our new study of DD back projection for image reconstruction in digital tomosysthesis. Since DD considers that the image pixel and detector cell have width, the convolution operation is used to calculate DD coefficients. The approximation characteristics of some other methods such as ray driven method (RD) can be avoided. A computer simulation result of DD with Maximum Likelihood Expectation Maximization (MLEM) of tomosysthesis reconstruction algorithm was studied. The sequence of projection images were simulated with 25 projections and a total view angle of 48 degrees. DD with MLEM reconstruction results were demonstrated. Line profile along x direction was used to evaluate DD and RD methods. Compared with RD, the computation time in DD with MLEM to provide the reconstruction results was shorter, since the main loop of DD is over x-y plane intercepts, not over the image pixels or detectors cells. In clinical applications, both the accuracy and computation speed of implementation condition are necessary requirements. DD back projection may satisfy the required conditions.
In this paper, C-arm tomosynthesis with digital detector was investigated as a novel three dimensional (3D) imaging technique. Digital tomosythses is an imaging technique to provide 3D information of the object by reconstructing slices passing through the object, based on a series of angular projection views with respect to the object. C-arm tomosynthesis provides two dimensional (2D) X-ray projection images with rotation (∓20 angular range) of both X-ray source and detector. In this paper, four representative reconstruction algorithms including point by point back projection (BP), filtered back projection (FBP), simultaneous algebraic reconstruction technique (SART) and maximum likelihood expectation maximization (MLEM) were investigated. Dataset of 25 projection views of 3D spherical object that located at center of C-arm imaging space was simulated from 25 angular locations over a total view angle of 40 degrees. With reconstructed images, 3D mesh plot and 2D line profile of normalized pixel intensities on focus reconstruction plane crossing the center of the object were studied with each reconstruction algorithm. Results demonstrated the capability to generate 3D information from limited angle C-arm tomosynthesis. Since C-arm tomosynthesis is relatively compact, portable and can avoid moving patients, it has been investigated for different clinical applications ranging from tumor surgery to interventional radiology. It is very important to evaluate C-arm tomosynthesis for valuable applications.
Statistical iterative reconstruction exhibits particularly promising since it provides the flexibility of accurate
physical noise modeling and geometric system description in transmission tomography system. However, to solve
the objective function is computationally intensive compared to analytical reconstruction methods due to multiple
iterations needed for convergence and each iteration involving forward/back-projections by using a complex
geometric system model. Optimization transfer (OT) is a general algorithm converting a high dimensional
optimization to a parallel 1-D update. OT-based algorithm provides a monotonic convergence and a parallel
computing framework but slower convergence rate especially around the global optimal. Based on an indirect
estimation on the spectrum of the OT convergence rate matrix, we proposed a successively increasing factor-
scaled optimization transfer (OT) algorithm to seek an optimal step size for a faster rate. Compared to a
representative OT based method such as separable parabolic surrogate with pre-computed curvature (PC-SPS),
our algorithm provides comparable image quality (IQ) with fewer iterations. Each iteration retains a similar
computational cost to PC-SPS. The initial experiment with a simulated Digital Breast Tomosynthesis (DBT)
system shows that a total 40% computing time is saved by the proposed algorithm. In general, the successively
increasing factor-scaled OT exhibits a tremendous potential to be a iterative method with a parallel computation,
a monotonic and global convergence with fast rate.
KEYWORDS: X-rays, Digital breast tomosynthesis, 3D acquisition, 3D image processing, Denoising, X-ray detectors, Image resolution, Image quality, Modulation transfer functions, Iterative methods
Stationary Digital Breast Tomosynthesis (sDBT) is a carbon nanotube based breast imaging device with fast
data acquisition and decent projection resolution to provide three dimensional (3-D) volume information. To-
mosynthesis 3-D image reconstruction is faced with the challenges of the cone beam geometry and the incomplete
and nonsymmetric sampling due to the sparse views and limited view angle. Among all available reconstruction
methods, statistical iterative method exhibits particular promising since it relies on an accurate physical and
statistical model with prior knowledge. In this paper, we present the application of an edge-preserved regularizer
to our previously proposed precomputed backprojection based penalized-likelihood (PPL) reconstruction. By
using the edge-preserved regularizer, our experiments show that through tuning several parameters, resolution
can be retained while noise is reduced significantly. Compared to other conventional noise reduction techniques
in image reconstruction, less resolution is lost in order to gain certain noise reduction, which may benefit the
research of low dose tomosynthesis.
Digital tomosynthesis is an innovative imaging technology for early breast cancer detection by providing three-dimensional anatomical information with fast image acquisition and low-dose radiation. Most of current breast tomosynthesis systems utilize a design where a single x-ray tube moves along an arc above objects over a certain angular range. The mechanical movement and patient motion during the scan may degrade image quality. With a carbon nanotube–based multibeam x-ray source, a new breast tomosynthesis modality is innovated, which will potentially produce better image quality with stationary beam sources and faster scan and it enables a variety of beam distributions. In this study, several beam distributions, such as beam sources spanning along a one-dimensional (1-D) parallel configuration and sources over a two-dimensional (2-D) rectangle shape are investigated based on computer simulations. Preliminary results show that 2-D rectangle shapes outperform 1-D parallel shapes by providing better Z-resolution, enhanced image contrast, reduced out-of-plane blur and artifacts and lower reconstruction noise. These benefits may expand tomosynthesis applications to diagnostic and interventional procedures.
This paper presents a Pre-computed BackProjection (BP) based Penalized-likelihood (PPL) method for limited angle X-ray tomography based on the theory of resolution properties of regularized image reconstruction. Pre computed BP based penalty is a simplified version of the modified quadratic penalty proposed in the literature. 1
By inserting a BP equivalent estimation into a quadratic penalty, the data-related terms in the impulse response and noise reconstructed by PPL are absorbed, such that the effects of smoothing parameter of the penalty can be evaluated in advance through the simulated data. A simulation based two-step procedure is proposed to apply PPL method in real applications. It reconstructs images with predictable resolution properties by choosing a corresponding smoothing parameter. The effectiveness and robustness of the two-step strategy is validated through simulation based experiments.
KEYWORDS: Digital breast tomosynthesis, X-rays, Image restoration, Image resolution, Sensors, 3D acquisition, 3D image processing, Imaging systems, Modulation transfer functions, 3D image reconstruction
Stationary Digital Breast Tomosynthesis (s-DBT) is a carbon nanotube based breast imaging device with fast image acquisition and decent resolution. In this paper, we investigate several representative reconstruction methods with the recently improved s-DBT system and also introduce a two-step reconstruction strategy with Pre-computed Backprojection based penalized-likelihood (PPL). This strategy reconstructs three dimensional (3-D) images with a desired resolution properties by choosing the corresponding smoothing parameter, which is evaluated in advance by studying simulated data. Our experiments show that the current s-DBT system has been greatly improved with respect to the performance of image reconstructions. PPL method exhibits controllable pixel precision, high image contrast and low noise on reconstructed images. Therefore, the enhanced Contrast Noise Ratio (CNR) from PPL method benefits both micro-calcifications and mass of the breast-equivalent phantom.
The recent commercialization of digital breast tomosynthesis systems realizes the clinical applications of
this novel three-dimensional imaging technology. The total dosage of breast tomosynthesis for single
patient is comparable to that of the traditional mammography. This paper presents our continuous work
on image quality analysis for the optimization of a new multi-beam breast tomosynthesis system based on
carbon nanotube X-ray emission technology. Several tomosynthesis reconstruction algorithms were
implemented to reconstruct the phantom data. Noise power spectrum and modulation transfer function
were investigated to evaluate the image quality.
Early detection, diagnosis, and suitable treatment are known to significantly improve the chance of survival for breast
cancer (BC) patients. To date, the most cost effective method for screening and early detection is mammography, which
is also the tool that has demonstrated its ability to reduce BC mortality. Tomosynthesis is an emerging technology that
offers an alternative to conventional two-dimensional mammography. Tomosynthesis produces three-dimensional
(volumetric) images of the breast that may be superior to planar imaging due to improved visualization. In this paper we
examined the effect of varying the number of projections (N) and total view angle (VA) on the shift-and-add (SAA),
back projection (BP) and filtered back projection (FBP) image reconstruction response characterized by impulse
response (IR) simulations. IR data were generated by simulating the projection images of a very thin wire, using various
combinations of VA and N. Results suggested that BP and FBP performed better for in-plane performance than that of SAA. With bigger number of projection images, the investigated reconstruction algorithms performed the best by obtaining sharper in-focus IR with simulated parallel imaging configurations.
Digital breast tomosynthesis is a new technique to improve the early detection of breast cancer by providing threedimensional
reconstruction volume of the object with limited-angle projection images. This paper investigated the image reconstruction with a standard biopsy training breast phantom using a novel multi-beam X-ray sources breast tomosynthesis system. Carbon nanotube technology based X-ray tubes were lined up along a parallel-imaging geometry
to decrease the motion blur. Five representative reconstruction algorithms, including back projection (BP), filtered back
projection (FBP), matrix inversion tomosynthesis (MITS), maximum likelihood expectation maximization (MLEM) and
simultaneous algebraic reconstruction technique (SART), were investigated to evaluate the image reconstruction of the
tomosynthesis system. Reconstructed images of the masses and
micro-calcification clusters embedded in the phantom
were studied. The evaluated multi-beam X-ray breast tomosynthesis system is able to generate three-dimensional
information of the breast phantom with clearly-identified regions of the masses and calcifications. Future study will be
done soon to further improve the imaging parameters' measurement and reconstruction.
As a new three-dimensional breast imaging technique, breast tomosynthesis allows the reconstruction of an arbitrary set
of planes in the breast from a limited-angle series of x-ray projection images. The breast tomosynthesis technique has
been demonstrated as promising to improve early breast cancer detection. This paper represents a preliminary phantom
study and computer simulation results of different breast tomosynthesis reconstruction algorithms with a novel carbon
nanotube based multi-beam x-ray source. Five representative tomosynthesis reconstruction algorithms, including back
projection (BP), filtered back projection (FBP), matrix inversion tomosynthesis (MITS), maximum likelihood
expectation maximization (MLEM), and simultaneous algebraic reconstruction technique (SART) were investigated.
Tomosynthesis projection images of a phantom were acquired with the stationary multi-beam x-ray tomosynthesis
system. Reconstruction results from different algorithms were studied. A computer simulation study was further done to
investigate the sharpness of reconstructed in-plane structures and to see how effective each algorithm is at removing
out-of-plane blur with parallel-imaging geometries. Datasets with 9 and 25 projection images of a defined 3D spherical
object were simulated with a total view angle of 50 degrees. Results showed that the multi-beam x-ray system is capable
to generate 3D tomosynthesis images with faster speed compared with current commercial prototype systems. With
simulated parallel-imaging geometry, MITS and FBP showed edge enhancement in-plane performance. BP, FBP and
MLEM performed better at out-of-plane structure removal with larger number of projection images.
As a new three-dimensional imaging technique, digital breast tomosynthesis allows the reconstruction of an arbitrary
set of planes in the breast from a limited-angle series of projection images. Though several tomosynthesis algorithms
have been proposed, no complete optimization and comparison of different tomosynthesis acquisition techniques for
available methods has been conducted as of yet. This paper represents a methodology of noise-equivalent quanta
NEQ (f) analysis to optimize and compare the efficacy of tomosynthesis algorithms and imaging acquisition
techniques for digital breast tomosynthesis. It combines the modulation transfer function (MTF) of system signal
performance and the noise power spectrum (NPS) of noise characteristics. It enables one to evaluate the
performance of different acquisition parameters and algorithms for comparison and optimization purposes. An
example of this methodology was evaluated on a selenium-based direct-conversion flat-panel Siemens Mammomat
Novation prototype system. An edge method was used to measure the presampled MTF of the detector. The MTF
associated with the reconstruction algorithm and specific acquisition technique was investigated by calculating the
Fourier Transform of simulated impulse responses. Flat field tomosynthesis projection sequences were acquired and
then reconstructed. A mean-subtracted NPS on the reconstructed plane was studied to remove fixed pattern noise.
An example of the application of this methodology was illustrated in this paper using a point-by-point Back
Projection correction (BP) reconstruction algorithm and an acquisition technique of 25 projections with 25 degrees
total angular tube movement.
KEYWORDS: Reconstruction algorithms, Received signal strength, Breast, Gaussian filters, Digital breast tomosynthesis, Sensors, Medical imaging, Physics, Image stacking, Spectrum analysis
Digital breast tomosynthesis is a three-dimensional imaging technique that allows the reconstruction of an arbitrary set of planes in the breast from limited-angle series of projection images. Though several tomosynthesis algorithms have been proposed, no complete optimization and comparison of all available methods has been conducted as of yet. This paper presents an analysis of noise power spectrum to examine the noise characteristics of several tomosynthesis algorithms with different imaging acquisition techniques. Flat images were acquired with the following acquisition parameters: 13, 25, 49 projections with ±12.5 and ±25 degrees of angular ranges. Three algorithms, including Shift-And-Add (SAA), Matrix Inversion Tomosynthesis (MITS), and Filtered Back Projection (FBP) were investigated with reconstruction slice spacing of 1mm, 2mm, and 4mm. The noise power spectra of the reconstruction plane at 23.5mm above the detector surface were analyzed. Results showed that MITS has better noise responses with narrower slice spacing for low-to-middle frequencies. No substantial difference was noticed for SAA and FBP with different slice spacings. With the same acquisition technique and slice spacing, MITS performed better than FBP at middle frequencies, but FBP showed better performance at high frequencies because of applied Hamming and Gaussian low-pass filters. For different imaging acquisition techniques, SAA, MITS and FBP performed the best with 49 projections and ±25 degrees. For 25 projections specifically, FBP performed better with wider angular range, while MITS performed better with narrower angular range. For SAA, narrow angular range is slightly better for 25 projections and 13 projections.
KEYWORDS: Gaussian filters, Reconstruction algorithms, Breast, Mammography, Tissues, Breast cancer, 3D image processing, Human subjects, Medical imaging, Image filtering
Breast cancer is a major problem and the most common cancer among women. The nature of conventional mammpgraphy makes it very difficult to distinguish a cancer from overlying breast tissues. Digital Tomosynthesis refers to a three-dimensional imaging technique that allows reconstruction of an arbitrary set of planes in the breast from limited-angle series of projection images as the x-ray source moves. Several tomosynthesis algorithms have been proposed, including Matrix Inversion Tomosynthesis (MITS) and Filtered Back Projection (FBP) that have been investigated in our lab. MITS shows better high frequency response in removing out-of-plane blur, while FBP shows better low frequency noise propertities. This paper presents an effort to combine MITS and FBP for better breast tomosynthesis reconstruction. A high-pass Gaussian filter was designed and applied to three-slice "slabbing" MITS reconstructions. A low-pass Gaussian filter was designed and applied to the FBP reconstructions. A frequency weighting parameter was studied to blend the high-passed MITS with low-passed FBP frequency components. Four different reconstruction methods were investigated and compared with human subject images: 1) MITS blended with Shift-And-Add (SAA), 2) FBP alone, 3) FBP with applied Hamming and Gaussian Filters, and 4) Gaussian Frequency Blending (GFB) of MITS and FBP. Results showed that, compared with FBP, Gaussian Frequency Blending (GFB) has better performance for high frequency content such as better reconstruction of micro-calcifications and removal of high frequency noise. Compared with MITS, GFB showed more low frequency breast tissue content.
Digital tomosynthesis mammography algorithms allow reconstructions of arbitrary planes in the breast from limited-angle series of projection images as the x-ray source moves along an arc above the breast. Though several tomosynthesis algorithms have been proposed, no complete comparison of the methods has previously been conducted. This paper presents an analysis of impulse response for four different tomosynthesis mammography reconstruction algorithms. Simulated impulses at different 3-D locations were simulated to investigate the sharpness of reconstructed in-plane structures and to see how effective each algorithm is at removing out-of-plane blur. Datasets with 41, 21 and 11 projection images of the impulse were generated with a total angular movement of +/- 10 degrees of the simulated x-ray point source. Four algorithms, including shift-and-add method, Niklason algorithm, filtered back projection (FBP), and matrix inversion tomosynthesis (MITS) are investigated. Compared with shift-and-add algorithm and Niklason method, MITS and FBP performed better for in-plane response and out-of-plane blur removal. MITS showed better out-of-plane blur removal in general. MITS and FBP performed better when projection numbers increase.
A prototype breast tomosynthesis system has been developed, allowing a total angular view of ±25°. The detector used in this system is an amorphous selenium direct-conversion digital flat-panel detector suitable for digital tomosynthesis. The system is equipped with various readout sequences to allow the investigation of different tomosynthetic data acquisition modes. In this paper, we will present basic physical properties -- such as MTF, NPS, and DQE -- measured for the full resolution mode and a binned readout mode of the detector. From the measured projections, slices are reconstructed employing a special version of filtered backprojection algorithm. In a phantom study, we compare binned and full resolution acquisition modes with respect to image quality. Under the condition of same dose, we investigate the impact of the number of views on artifacts. Finally, we show tomosynthesis images reconstructed from first clinical data.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.