Research

Medical Image Processing and Analysis

Our group is dedicated in developing advanced image processing and analysis techniques, including the emerging deep-learning methods, for radiotherapy. Over the years, we have developed novel algorithms for high-quality low-dose computed tomography (CT), cone beam CT (CBCT), and 4-D CBCT reconstruction, pioneering the applications of graphical processing unit (GPU) in medical image processing.

Recently, we have successfully realized multi-energy CBCT (ME-CBCT) on a standard on-board imaging system, based on which an element-resolved ME-CBCT reconstruction framework has been put forward to directly derive elemental compositions and electron density in addition to the high-quality ME-CBCT images. We are in the process of applying ME-CBCT for advanced radiotherapy purposes, such as low-concentration contrast enhancement and stopping power ratio estimation for proton therapy.

Furthermore, we are actively integrating these imaging approaches to contribute to the development of next generation radiotherapy hardware in our Lab.

 

 
 

Recent publications:

  1. Chenyang Shen, Bin Li, Liyuan Chen, Ming Yang, Yifei Lou, Xun Jia, "Material elemental decomposition in dual and multi-energy CT via a sparsity-dictionary approach for proton stopping power ratio calculation," Medical Physics, 45(4), 1491-1503 (2018).
  2. Chenyang Shen, Bin Li, Yifei Lou, Ming Yang, Linghong Zhou, Xun Jia, "Multienergy element-resolved cone beam CT (MEER-CBCT) realized on a conventional CBCT platform," Medical Physics, 45(10), 4461-4470 (2018).
  3. Bin Li, Chenyang Shen Yujie Chi, Ming Yang, Yifei Lou, Linghong Zhou, Xun Jia, "Multienergy Cone-Beam Computed Tomography Reconstruction with a Spatial Spectral Nonlocal Means Algorithm," SIAM journal on imaging sciences, 11(2), 1205-1229 (2018).
  4. Xun Jia, Zhen Tian, Yifei Lou, Jan-Jakob Sonke, Steve Jiang, "Four-dimensional cone beam CT reconstruction and enhancement using a temporal nonlocal means method," Medical Physics, 39(9), 5592-5602 (2012).
  5. Xun Jia, Bin Dong, Yifei Lou, Steve Jiang, "GPU-based iterative cone-beam CT reconstruction using tight frame regularization," Physics in Medicine and Biology, 56(13), 3787 (2011).
  6. Xun Jia, Yifei Lou, Ruijiang Li, William Song, Steve Jiang, "GPU-based fast cone beam CT reconstruction from undersampled and noisy projection data via total variation," Medical Physics, 37(4), 1757 (2010).

Funding support:

  1. “Precise image guidance for liver cancer stereotactic body radiotherapy using element-resolved motion-compensated cone beam CT,” NIH/NCI 1R01CA22728901, 03/2018 - 02/2023.
  2. “Explore random sampling for dose reduction and scatter removal in cone beam CT,” NIH/NIBIB 1R21EB021545-01A1, 06/2016 - 05/2019.
  3. “4D cone beam CT reconstruction for radiotherapy via motion vector optimization,” NIH/NIBIB 1R21EB017978-01A1, 09/2014 - 08/2016.
  4. “A progressive cone-beam CT dose control scheme for image-guided radiation therapy,” NIH/NCI 1R21CA178787-01A1, 07/2014 - 06/2016.