Biomedical Imaging

The X-ray Systems Lab aims at developing novel medical imaging technologies for biomedical and bioscientific discovery, radiological diagnosis, and medical intervention. Directed by Dr. Guohua Cao, the lab focuses on unique x-ray sources, detectors, and systems engineering. The research activities are interdisciplinary and translational, and interface between basic sciences, translational development, and clinical applications.

Software-based scatter correction

The 10-Gbps connection provided from the VT-Rnet greatly facilitated the biomedical imaging service provided to the users of the biomedical imaging facility. The high speed connection allows uploading the imaging data to the server at high speed and enables the imaging users to retrieve their imaging results from the server at high speed as well. Because imaging data easily consumes a few gigabytes per CT scan, the high-speed connection boosts the efficiency and productivity significantly.

The fast connection has helped tremendously in imaging: (1) new aerospace materials for Professor Gary Seidel of Department of Aerospace and Ocean Engineering, (2) new smart structure materials for Professor Hang Yu of Department of Material Science and Engineering, (3) mosquitoes for Professor Jake Tu of Department of Biochemistry at Virginia Tech, and (4) meteorite for Dr. Andrew Needham of Carnegie Science Institute.

Grants

The high-speed network was used in work which contributed to the following grant awards:

  1. Modelling Pathogen And Surrogate Reduction Using Vacuum Assisted Steam On Low Water Activity Foods As Effected By In-Package Interactions. USDA, 1/1/18-12/31/22, $488,691. PI: M. PonderRole, Co-PI: Guohua Cao.
  2. Early solar system processes recorded by the most refractory materials. NASA, 12/1/17-11/30/20, $366,251. PI: A. Needham, Subcontract PI: Guohua Cao.
  3. CAREER: Interior 5D Micro-CT to Analyze Atherosclerotic Plaques In Vivo. NSF, 8/1/14-7/31/19, $400,000. PI. G. Cao.
  4. Computed Tomography Without Moving Parts. Center for Innovative Technology Commonwealth of Virginia, 7/1/17-6/30/18, $100,000, PI: G. Cao.
  5. A Smart Device for Mine Dust Characterization and Diagnosis.
    Alpha Foundation, 8/15/17-2/14/19, $175,000. PI: C. Chen and Co-PI: G. Cao.

Publications

The following publications contain research which utilized the high-speed connection to VT-Rnet:

  1. Zhicheng Zhang*, Xiaokun Liang, Xu Dong*, Yaoqin Xie, and Guohua Cao, “A Novel Sparse-View CT Reconstruction Method Based on Combination of DenseNet and Deconvolution”, IEEE Trans. on Medical Imaging 37(6), 1407-1417 (2018).
  2. Shunli Zhang, Guohua Geng, Guohua Cao, Yuhe Zhang, Baodong Liu, and Xu Dong*, “Fast projection algorithm for LIM-based simultaneous algebraic reconstruction technique and its parallel implementation on GPU”, IEEE Access 6, 23007-23018 (2018). DOI: 10.1109/ACCESS.2018.2829861.
  3. Xiaodong Yu, Hao Wang, Wu-chun Feng, Hao Gong*, and Guohua Cao, “GPU-Based Iterative Medical CT Image Reconstructions”, Journal of Signal Processing Systems: p. 1-18 (2018).
  4. Hao Gong*, Bin Li, Xun Jia, and Guohua Cao, “Physics Model Based Scatter Correction in Multi-Source Interior Computed Tomography”. IEEE Trans. Medical Imaging, 37(20): p. 349-360 (2018).
  5. Xiaodong Yu, Hao Wang, Wu-Chun Feng, Hao Gong, and Guohua Cao. “An Enhanced Image Reconstruction Tool for Computed Tomography on CPUs”. Proceedings of the Computing Frontiers Conference: p. 97-106 ACM (2017).
  6. Xiaodong Yu, Hao Wang, Wu-Chun Feng, Hao Gong, and=
    Guohua Cao. “cuART: Fine-Grained Algebraic Reconstruction Technique for Computed Tomography Images on GPUs”. Proceedings of the 2016 IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, CCGrid, 16 (2016).
  7. Lijuan Kan, Patrick Thayer, Huimin Fan, Benjamin L=
    edford, Miao Chen, Aaron Goldstein, Guohua Cao, and Jia-Qiang He, “Polymer microfiber meshes facilitate cardiac differentiation of c-kit+ human cardiac stem cells”. Experimental cell research 347(1): p. 143-152 (2016).
  8. Hao Gong, Hao Yan, Xun Jia, Bin Li, Ge Wang, and Guohua Cao, “X-ray scatter correction for multi-source interior computed tomography”. Medical Physics 44(1): p. 71-83 (2017).