Journal

  1. Y. Long, J. A. Fessler, and J. M. Balter.Accuracy estimation for projection-to-volume targeting during rotational therapy: A feasibility study.Med. Phys., 37(6):2480–90, Jun. 2010.
  2. Y. Long, J. A. Fessler, and J. M. Balter.3D forward and back-projection for X-ray CT using separable footprints.IEEE Trans. Med. Imag., 29(11):1839–50, Nov. 2010.
  3. Y. Long and J. A. Fessler.Multi-material decomposition using statistical image reconstruction.IEEE Trans. Med. Image., 33(8):1–13, Aug. 2014.
  4. X. Rui, L. Cheng, Y. Long, L. Fu, A. M. Alessio, E. Asma, P. E. Kinahan and B. De Man.Ultra-low dose CT attenuation correction for PET/CT: analysis of sparse view data acquisition and reconstruction algorithms.Phys. Med. Biol., 60 (19): 7439-7462, Sep. 2015.
  5. Y. Xue, R. Ruan, X. Hu, Y. Kuang, J. Wang, Y. Long, and T. Niu. Statistical image-domain multi-material decomposition for dual-energy CT.Med. Phys.,44(3): 886–901, doi:10.1002/mp.12096, Mar. 2017.
  6. Y. Zan, Y. Long, K. Chen, B. Li, Q. Huang and G. T. Gullberg. “Design of a short non-uniform acquisition protocol for quantitative analysis in dynamic cardiac SPECT imaging – a retrospective animal study.“Med. Phys., 44(7):3639-3649, July 2017.
  7. X. Zheng, S. Ravishankar, Y. Long and J. Fessler. “PWLS-ULTRA: An Efficient Clustering and Learning-Based Approach for Low-Dose 3D CT Image Reconstruction.” IEEE Trans. Med. Image., 37(6):1498-510, June 2018.
  8. Q. Ding, T. Niu, X. Zhang and Y. Long. “Image-domain multi-material decomposition for dual-energy CT based on prior information of material images.” Medical Physics, 45(8):3614-3626, August 2018.

Conference Proceedings Papers

  1. Y. Long, J. A. Fessler, and J. M. Balter. “A 3D forward and back-projection method for X-ray CT using separable footprint”.In Proc. Intl. Mtg. on Fully 3D Image Recon. in Rad. and Nuc. Med, pp. 146–9, 2009. Winner of poster award.pdf
  2. Y. Long, J. A. Fessler, and J. M. Balter. “3D forward and back-projection for X-ray CT using separable footprints with trapezoid functions”.In Proc. First Intl. Mtg. on image formation in X-ray CT, pp. 216–9, 2010.pdf
  3. Y. Long and J. A. Fessler. “Multi-material decomposition using statistical image reconstruction in X-ray CT”.In Proc. 2nd Intl. Mtg. on image formation in X-ray CT, pp. 413–6, 2012. pdf
  4. Y. Long, L. Cheng, X. Rui, B. De Man, A. Alessio, E. Asma and P. Kinahan. “Analysis of Ultra-Low Dose CT Acquisition Protocol and Reconstruction Algorithm Combinations for PET Attenuation Correction”.In Proc. Intl. Mtg. on Fully 3D Image Recon. in Rad. and Nuc. Med., pp. 400-3, 2013.pdf
  5. X. Rui, Y. Long, A. Alessio, E. Asma, P. Kinahan and B. De Man. “Theoretical Analysis of Optimal CT Spectrum for PET Attenuation Correction“.In Proc. IEEE Nuc. Sci. Symp. Med. Im. Conf., pp1-6,2013.
  6. Y. Long, H. Gao, M. Wu, J. D. Pack, H. Xu, K. Tao, P. F. Fitzgerald and B. De Man. “Physics- based modeling of X-Ray CT measurements with energy-integrating detectors“.Proc. SPIE 9033 Medical Imaging 2014: Phys. Med. Im.,pp.90334S, 2014.
  7. J. Wang, Y. Long, L. Fu, X. Rui and B. De Man. “Sinogram rebinning and frequency boosting for high resolution iterative CT reconstruction with focal spot wobbling“.Proc. SPIE 9033 Medical Imaging 2014: Phys. Med. Im.,pp. 903333, 2014.
  8. H. Xu, K. Tao, P. GK, M. Wu, X. Cao, Y. Long, M. Yan, Y. Yao and B. De Man. “Hybrid model for computed tomography simulations and post-patient collimator design“.Proc. SPIE 9033 Medical Imaging 2014: Phys. Med. Im.,pp. 90334R, 2014.
  9. X. Zheng, Z. Lu, S. Ravishankar, Y. Long, J. A. Fessler. “Low dose CT image reconstruction with trained sparsifying transform“.Proc. IEEE Wkshp. on Image, Video, Multidim. Signal Proc., pp. 1-5, July 11-12 2016, Bordeaux, France.
  10. M. Yang, Y. Long and T. Niu. “Statistical Image-Domain Multi-Material Decomposition for Dual-Energy CT”.In Proc. 4th Intl. Mtg. on image formation in X-ray CT, pp. 65-8, July 18-22, 2016, Bamberg, Germany. pdf
  11. Q. Ding, Y. Long, X. Zhang and J. A. Fessler. “Modeling Mixed Poisson-Gaussian Noise in Statistical Image Reconstruction for X-Ray CT”.In Proc. 4th Intl. Mtg. on image formation in X-ray CT, pp. 399-402, July 18-22, 2016, Bamberg, Germany.pdf
  12. X. Xie, M. G. McGaffin, Y. Long, J. A. Fessler, M. Wen, J. Lin. “Accelerating separable footprint (SF) forward and back projection on GPU“.Proc. SPIE 10132 Medical Imaging 2017: Phys. Med. Im., 101322S, Feb. 11-16, 2017, Orlando, Florida, USA.
  13. X. Zheng, S. Ravishankar, Y. Long and J. A. Fessler. “Union of Learned Sparsifying Transforms Based Low-Dose 3D CT Image Reconstruction.” Proc. Intl. Mtg. on Fully 3D Image Recon. in Rad. and Nuc. Med., page 69-72, June 18-23, 2017, Xi’an, China.pdf
  14. I. Y. Chun, X. Zheng, Y. Long, and J. A. Fessler. “Efficient Sparse-View X-Ray CT Reconstruction Using L1 Regularization with Learned Sparsifying Transform.” Proc. Intl. Mtg. on Fully 3D Image Recon. in Rad. and Nuc. Med., page 115-119, June 18-23, 2017. Xi’an, China.pdf
  15. Q. Ding, T. Niu, X. Zhang and Y. Long. “Image-domain multile-material decomposition for dual-energy CT via total nuclear norm and L0 norm.” Proc. Intl. Mtg. on Fully 3D Image Recon. in Rad. and Nuc. Med., page 154-159, June 18-23, 2017. Xi’an, China.pdf
  16. S. Ye, S. Ravishankar, Y. Long, and J. A. Fessler. “Adaptive sparse modeling and shifted-Poisson likelihood based approach for low-dose CT image reconstruction.” In Proc. IEEE Wkshp. Machine Learning for Signal Proc., pages 154-159, September 25-28, 2017, Roppongi, Tokyo, Japan.
  17. Z. Li, S. Ravishankar, Y. Long, and J. A. Fessler. “Image-Domain Material Decomposition Using Data-Driven Sparsity Models for Dual-Energy CT.” In Proc. IEEE Intl. Symp. Biomed. Image., pages 52-6, April 4-7, 2018, Washington D.C., USA. Award for best student paper.
  18. Z. Li, S. Ravishankar, Y. Long, and J. A. Fessler. “Learned missed material models for efficient clustering based dual-energy CT image decomposition.” In Proc. IEEE GlobalSIP, November 26-29, 2018, Anaheim, California, USA.

Conference Abstracts

  1. Y. Long, J. A. Fessler, and J. M. Balter. “Accuracy limits for projection-to-volume targeting during arc therapy”.Proc. Amer. Assoc. Phys. Med., pp. 3154, 2010.
  2. Y. Long, J. A. Fessler, and J. M. Balter. “Two-material decomposition from a single CT scan using statistical image reconstruction”.Proc. Amer. Assoc. Phys. Med., pp. 3810, 2011.
  3. J. M. Balter, Y. Long, M. M. Folkerts, G. C. Sharp, T. R. Bortfeld and J. A. Fessler. “An open platform for 2D-3D image registration experiments”.Proc. Amer. Assoc. Phys. Med., pp. 3450, 2011.
  4. X. Zheng, S. Ravishankar, Z. Lu, Y. Long, J. A. Fessler. “Image reconstruction for low dose X-ray CT using learned overcomplete sparsifying transforms”. Gordon Res. Conf. on Imaging Science, 2016.