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Paper can be freely accessed at PLoSONE website.
We recently elevated interior tomography from its origin in computed tomography (CT) to a general tomographic principle, and proved its validity for other tomographic modalities including SPECT, MRI, and others. Here we propose “omni-tomography”, a novel concept for the grand fusion of multiple tomographic modalities for simultaneous data acquisition in a region of interest (ROI). Omni-tomography can be instrumental when physiological processes under investigation are multi-dimensional, multi-scale, multi-temporal and multi-parametric. Both preclinical and clinical studies now depend on in vivo tomography, often requiring separate evaluations by different imaging modalities. Over the past decade, two approaches have been used for multimodality fusion: Software based image registration and hybrid scanners such as PET-CT, PET-MRI, and SPECT-CT among others. While there are intrinsic limitations with both approaches, the main obstacle to the seamless fusion of multiple imaging modalities has been the bulkiness of each individual imager and the conflict of their physical (especially spatial) requirements. To address this challenge, omni-tomography is now unveiled as an emerging direction for biomedical imaging and systems biomedicine.
Developments in X-Ray Tomography VIII (OP325)
Part of the SPIE International Symposium on SPIE Optical Engineering + Applications
12–16 August 2012 • San Diego Convention Center • San Diego, CA United States
Conference Chairs: Stuart R. Stock, Northwestern Univ. (United States)
Program Committee: Felix Beckmann, Helmholtz-Zentrum Geesthacht (Germany); Graham R. Davis, Queen
Mary, Univ. of London (United Kingdom); Atsushi Momose, The Univ. of Tokyo (Japan); Bert Müller, Univ.
Basel (Switzerland); Andrew G. Peele, Australian Synchrotron (Australia) and La Trobe Univ. (Australia); Erik
L. Ritman, Mayo Clinic (United States); Mark L. Rivers, The Univ. of Chicago (United States); Ge Wang,
Virginia Polytechnic Institute and State Univ. (United States)
We are pleased to announce a 2012 NSF CAREER Award Winner: Dr. Hengyong Yu
While classic computed tomography (CT) theory targets exact reconstruction of a whole cross-section or entire volume from complete projections, biomedical applications often focus on relatively small internal region-of-interests (ROIs). However, traditional CT theory cannot exactly reconstruct an internal ROI only from truncated projections associated with x-rays through the ROI because this interior problem does not have a unique solution in an unconstrained setting. In 2007, the PI and his collaborators proved that the interior problem can be exactly and stably solved if a sub-region is known inside the ROI. Inspired by the compressive sensing (CS) theory, in 2009 the PI proposed the concept of CS-based interior tomography and proved that exact interior reconstruction is achievable with an interior scan if the ROI is piecewise constant, which is subsequently extended to the case of piecewise polynomial ROI.
The goal of this CAREER proposal is to advance the CS-based interior tomography theory and algorithms, and make a paradigm shift from traditional global filtered back-projection (FBP) to contemporary interior reconstruction.
The three objectives are to 1) perform mathematical analysis on a general scarcity constraint model to establish uniqueness, exactness and stability, as well as the properties of the corresponding discrete scheme; 2) develop and optimize novel interior reconstruction algorithms in a general POCS framework incorporating the split-Bregman and statistical reconstruction methods; 3) verify the theoretical findings and validate the proposed algorithms via numerical simulation, and demonstrate its utility by solving the big patient problem.
The research will be closely integrated with educational and outreach activities including creating a Medical Image Reconstruction course at both graduate and undergraduate levels at the Virginia Tech-Wake Forest University School of Biomedical Engineering and Sciences (SBES).
Yang J, Vannier M, Wang F, Deng Y, Ou F, Bennett J, Liu Y, Wang G: Scientific Productivity, Research Funding, Race and Ethnicity. arXiv:1112.3944, 20110
In a recent study by Ginther et al., the probability of receiving a U.S. National Institutes of Health (NIH) RO1 award
was related to the applicant’s race/ethnicity. The results indicate black/African-American applicants were 10% less
likely than white peers to receive an award, after controlling for background and qualifications. It has generated a
widespread debate regarding the unfairness of the NIH grant review process and its correction. In this paper, the
work by Ginther et al. was augmented by pairing analysis, axiomatically-individualized productivity and normalized
funding success measurement. Although there are racial differences in R01 grant success rates, normalized figures
of merit for funding success explain the discrepancy. The suggested “leverage points for policy intervention” are in
question and require deeper and more thorough investigations. Further adjustments in policies to remove racial
disparity should be made more systematically for equal opportunity, rather than being limited to the NIH review
process. Click here for full article…
The number of publications and the number of co-authors become increasingly larger, and the competition for academic resources has intensified over the past years. To optimize the resource allocation, fair, sensitive and quick assessment of individual research productivity is highly desirable and being actively studied. However, the current indices, such as the number of papers, the number of citations, the h-factor and its variants have serious limitations. The primary shortcoming of these indices is their inability to quantify co-authors’ credits. Recently, we established an axiomatic system and derived the measure that is referred to as the a-index for quantification of co-authors’ credits. We believe that our methodology could play a significant role in the recruitment, promotion, funding and other evaluative processes. The a-index technology is patent-pending. Click here for full presentation….
Current collaborators include Dr. Jiansheng Yang, Mr. Ivan Ye, and Dr. Michael Vannier.
In the NY Times best seller, “The Black Swan”, the author (Nassim Nicholas Taleb) defines a Black Swan as an event that has three characteristics: it is an outlier; it carries an extreme impact; it has retrospective predictability. He further makes a claim that our world is dominated by Black Swans. This seminar series will provide an environment in which engineers, scientists and humanists from different disciplines can come together to move beyond the predictable and incremental advances in the current technologies to the disruptive technologies of the future – a breeding ground for future Black Swans.
Lu Y, Zhu B, Shen H, Rasmussen J, Wang G, Sevick-Muraca E: A parallel adaptive finite element simplified spherical harmonics approximation solver for frequency domain fluorescence molecular imaging. Phy. Med. Bio., 55, 4625-4645, 20100
Fluorescence molecular imaging/tomography may play an important future role in preclinical research and clinical diagnostics. Time- and frequency-domain fluorescence imaging can acquire more measurement information than the continuous wave (CW) counterpart, improving the image quality of fluorescence molecular tomography. Although diffusion approximation (DA) theory has been extensively applied in optical molecular imaging, high-order photon migration models need to be further investigated to match quantitation provided by nuclear imaging. In this paper, a frequency-domain parallel adaptive finite element solver is developed with simplified spherical harmonics (SPN) approximations. To fully evaluate the performance of the SPN approximations, a fast time-resolved tetrahedron-based Monte Carlo fluorescence simulator suitable for complex heterogeneous geometries is developed using a convolution strategy to realize the simulation of the fluorescence excitation and emission. The validation results show that high-order SPN can effectively correct the modeling errors of the diffusion equation, especially when the tissues have high absorption characteristics or when high modulation frequency measurements are used. Furthermore, the parallel adaptive mesh evolution strategy improves the modeling precision and the simulation speed significantly on a realistic digital mouse phantom. This solver is a promising platform for fluorescence molecular tomography using high-order approximations to the radiative transfer equation.
This book brings together 27 state-of-the-art, refereed and subsequently revised, research and review papers, by leading experts and practitioners in mathematical methods in biomedical imaging, in intensity-modulated radiation therapy (IMRT) and in optimization and inverse problems. The emphasis is on trying to discover relations and connections between these fields that will enhance progress in each of them. As this volume shows, applicable mathematical work in these fields goes hand-in-hand with real-world applications and the mutual “technology transfers” between them leads to further progress.
Li L, Chen Z, Jin X, Yu H, Wang G, Experimental measurement of human head motion for high-resolution computed tomography system design, Optical Engineering, vol. 49, n. 6, 20100
Human head motion has been experimentally measured for high-resolution computed tomography (CT) design using a Canon digital camera. Our goal is to identify the minimal movements of the human head under ideal conditions without rigid fixation. In our experiments, all the 19 healthy volunteers were lying down with strict self-control. All of them were asked to be calm without pressures. Our results showed that the mean absolute value of the measured translation excursion was about 0.35 mm, which was much less than the measurements on real patients. Furthermore, the head motions in different directions were correlated. These results are useful for the design of the new instant CT system for in vivo high-resolution imaging (about 40 µm). Click here for full article….
Whereas classic computed tomography (CT) theory targets the exact reconstruction of a whole cross-section or entire volume from complete projections, a real-world application often focuses on a region of interest (ROI). It has been a long-standing challenge to reconstruct an internal ROI only from truncated projections collected with a radiative beam through the ROI because this “interior problem” does not have a unique solution (1). When a traditional CT algorithm such as “filtered backprojection” is applied for an interior reconstruction from truncated projections, features outside the ROI may create artifacts overlapping inside features, rendering the images inaccurate or useless. On the other hand, over past decades, lambda tomography has been developed as a branch of applied mathematics that recovers gradient-like features within an ROI from truncated projections. With lambda tomography, the outcomes are not always the most appealing because of their non-quantitative nature. Recently, Quinto et al. (2) demonstrated the utility and limitation of electron lambda tomography and pointed out that “unless prior knowledge is being used…structures in the specimen cannot be exactly recovered even if we have access to noise-free continuum data….” Click here for full article….
Interior Tomography and Instant Tomography by Reconstruction from Truncated Limited-angle Projection Data by Dr. Ge Wang, Yangbo Ye, and Hengyong Yu.
A system and method for tomographic image reconstruction using truncated limited-angle projection data that allows exact interior reconstruction (interior tomography) of a region of interest (ROI) based on linear attenuation coefficient distribution of a subregion within the ROI, thereby improving image quality while reducing radiation dosage. In addition, the method includes parallel interior tomography using multiple sources beamed at multiple angles through an ROI and that enables higher temporal resolution. Click here for full text…
Yang L, Lu Y, Wang G, Compressed sensing inspired image reconstruction from overlapped projections, International Journal of Biomedical Imaging, vol. 2010, Article ID 284073, 20100
The key idea discussed in this paper is to reconstruct an image from overlapped projections so that the data acquisition process can be shortened while the image quality remains essentially uncompromised. To perform image reconstruction from overlapped projections, the conventional reconstruction approach (e.g., filtered backprojection (FBP) algorithms) cannot be directly used because of two problems. First, overlapped projections represent an imaging system in terms of summed exponentials, which cannot be transformed into a linear form. Second, the overlapped measurement carries less information than the traditional line integrals. To meet these challenges, we propose a compressive sensing-(CS-) based iterative algorithm for reconstruction from overlapped data. This algorithm starts with a good initial guess, relies on adaptive linearization, and minimizes the total variation (TV). Then, we demonstrated the feasibility of this algorithm in numerical tests. Click here for full article….
Gong R, Wang G, Cheng X, Han WM: A novel approach for studies of multispectral bioluminescence tomography. Numer. Math. 115, 553-583, 20100
Bioluminescence tomography (BLT) is a promising new area in biomedical imaging. The goal of BLT is to provide quantitative reconstruction of bioluminescent source distribution within a small animal from optical signals on the animal’s body surface. The multispectral version of BLT takes advantage of the measurement information in different spectrum bands. In this paper, we propose a novel approach for the multispectral BLT. The new feature of the mathematical framework is to use numerical prediction results based on two related but distinct boundary value problems. This mathematical framework includes the conventional framework in the study of multispectral BLT. For the new framework introduced here, we establish the solution existence, uniqueness and continuous dependence on data, and characterize the limiting behaviors when the regularization parameter approaches zero or when the penalty parameter approaches infinity. We study two kinds of numerical schemes for multispectral BLT and derive error estimates for the numerical solutions. We also present numerical examples to show the performance of the numerical methods.Click here for full article….
Lu Y, Katsevich A, Zhao J, Yu H, Wang G: Fast exact/quasi-exact FBP algorithms for triple-source helical cone-beam CT. IEEE Trans. Medical Imaging 29:756-770, 20100
Cardiac computed tomography (CT) has been improved over past years, but it still needs improvement for higher temporal resolution in the cases of high or irregular cardiac rates. Given successful applications of dual-source cardiac CT scanners, triple-source cone-beam CT seems a promising mode for cardiac CT. In this paper, we propose two filtered-backprojection algorithms for triple-source helical cone-beam CT. The first algorithm utilizes two families of filtering lines. These lines are parallel to the tangent of the scanning trajectory and the so-called L lines. The second algorithm utilizes two families of filtering lines tangent to the boundaries of the Zhao window and L lines, respectively, but it eliminates the filtering paths along the tangent of the scanning trajectory, thus reducing the required detector size greatly. The first algorithm is theoretically exact for r < 0.265 R and quasi-exact for 0.265 R ≤ r < 0.495 R, and the second algorithm is quasi-exact for r < 0.495 R, where and denote the object radius and the trajectory radius, respectively. Both algorithms are computationally efficient. Numerical results are presented to verify and showcase the proposed algorithms. Click here for full article….
Medical Imagers Lower the Dose
Radiation-lowering techniques were in the works even before studies showed a danger
By Neil Savage / March 2010
Recent research documenting that CT scans increase the risk of cancer has biomedical engineers looking for new ways to reduce patients’ exposure to ionizing radiation. Click here for full article…
Yang JS, Yu HY, Jiang M, Wang G: High-order total variation minimization for interior tomography. Inverse Problems 26:1-29, 20100
Recently, an accurate solution to the interior problem was proposed based on the total variation (TV) minimization, assuming that a region of interest (ROI) is piecewise constant. In this paper, we generalize that assumption to allow a piecewise polynomial ROI, introduce the high-order TV (HOT), and prove that an ROI can be accurately reconstructed from projection data associated with x-rays through the ROI via the HOT minimization if the ROI is piecewise polynomial. Then, we verify our theoretical results in numerical simulation. Click here for full article….