Dr. Ge Wang was interviewed by The American Association for the Advancement of Science (AAAS) regarding Omni-Tomography. The article can be found at the following link.
Dr. Ge Wang’s research on has been featured by Virginia Tech’s Engineering Department website.
“Towards Omni-Tomography—Grand Fusion of Multiple Modalities for Simultaneous Interior Tomography” has been featured by MedicalPhysicsWeb.
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).
Dr. Ge Wang was recently issued US Patent No. 8.090,431 on 1/3/2012. Click here for full PDF.
Click here to see the 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.
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.
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…
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…