Publications

[2019] [2018] [2017] [2016] [2015] [2011-2014] [2006-2010] [2000-2005]

2019

  • D. Wu, K. Kim, and Q. Li, "Computationally Efficient Deep Neural Network for Computed Tomography Image Reconstruction," Medical physics, 2019.

       View in: link

  • D. Wu, K. Kim, M. K. Kalra, B. De Man, and Q. Li, "Learned primal-dual reconstruction for dual energy computed tomography with reduced dose," in 15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, 2019, p. 1107206.

       ​View in: link

  •  D. Wu, K. Kim, G. El Fakhri, and Q. Li, "Computational-efficient cascaded neural network for CT image reconstruction," Physics of Medical Imaging, 2019, p. 109485Z.

       View in: PubMed

  • T.-A. Song, F. Yang, S. R. Chowdhury, K. Kim, K. A. Johnson, G. El Fakhri, et al., "PET Image Deblurring and Super-Resolution with an MR-Based Joint Entropy Prior," IEEE Transactions on Computational Imaging, 2019.

  • T.-A. Song, S. R. Chowdhury, G. El Fakhri, Q. Li, and J. Dutta, "Super-resolution PET imaging using a generative adversarial network," Journal of Nuclear Medicine, vol. 60, pp. 576-576, 2019.

  • K. Kim, Y. D. Son, J.-H. Kim, and Q. Li, "Parametric image estimation using Residual simplified reference tissue model," in 15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, 2019, p. 1107237.

  •  K. Kim, D. Kim, J. Yang, G. El Fakhri, Y. Seo, J. A. Fessler, et al., "Time of flight PET reconstruction using nonuniform update for regional recovery uniformity," Medical physics, vol. 46, pp. 649-664, 2019.

  • R. Ju, C. Hu, P. Zhou, and Q. Li, "Early diagnosis of Alzheimer's disease based on resting-state brain networks and deep learning," IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB), vol. 16, pp. 244-257, 2019.

  •  Z. Guo, X. Li, H. Huang, N. Guo, and Q. Li, "Deep Learning-Based Image Segmentation on Multimodal Medical Imaging," IEEE Transactions on Radiation and Plasma Medical Sciences, vol. 3, pp. 162-169, 2019.

  • Z. Guo, N. Guo, K. Gong, and Q. Li, "Automatic multi-modality segmentation of gross tumor volume for head and neck cancer radiotherapy using 3D U-Net," in Medical Imaging, 2019, p. 1095009.

  • N. Guo, C. Wu, Z. Guo, and Q. Li, "Intratumoral heterogeneity predicts recurrence after radiofrequency ablation therapy using early post-treatment 18F-FDG PET in lung cancer," Journal of Nuclear Medicine, vol. 60, pp. 1588-1588, 2019.

  • K. Gong, D. Wu, K. Kim, J. Yang, T. Sun, G. El Fakhri, et al., "MAPEM-Net: an unrolled neural network for Fully 3D PET image reconstruction," in 15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, 2019, p. 110720O.

  • K. Gong, D. Wu, K. Kim, J. Yang, G. El Fakhri, Y. Seo, et al., "EMnet: an unrolled deep neural network for PET image reconstruction," in Medical Imaging, p. 1094853.

  • K. Gong, C. Catana, J. Qi, and Q. Li, "Direct patlak reconstruction from dynamic PET using unsupervised deep learning," in 15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, 2019, p. 110720R.

  • K. Gong, C. Catana, J. Qi, and Q. Li, "Direct Patlak Reconstruction for Low-Dose Dynamic PET Using Unsupervised Deep Learning," Journal of Nuclear Medicine, vol. 60, pp. 575-575, 2019.

  • J. Cui, K. Gong, N. Guo, C. Wu, K. Kim, H. Liu, et al., "Population and individual information guided PET image denoising using deep neural network," in 15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, 2019, p. 110721E.

  • J. Cui, K. Gong, N. Guo, K. Kim, H. Liu, and Q. Li, "CT-guided PET parametric image reconstruction using deep neural network without prior training data," in Medical Imaging 2019, p. 109480Z.

2018

  • Y. Zhao, X. Li, W. Zhang, S. Zhao, M. Makkie, M. Zhang, et al., "Modeling 4D fMRI Data via Spatio-Temporal Convolutional Neural Networks (ST-CNN)," in International Conference on Medical Image Computing and Computer-Assisted Intervention, 2018, pp. 181-189.

  •  M. Zhang, X. Li, M. Xu, and Q. Li, "RBC semantic segmentation for sickle cell disease based on deformable U-Net," in International Conference on Medical Image Computing and Computer-Assisted Intervention, 2018, pp. 695-702.

  • L. Zhang, H. Wang, Q. Li, M.-H. Zhao, and Q.-M. Zhan, "Big data and medical research in China," bmj, vol. 360, p. j5910, 2018.

  • F. Yang, R. Tabassum, J. Sanchez, A. Becker, G. El Fakhri, Q. Li, et al., "Association between partial volume corrected longitudinal tau measures and cognitive decline," Journal of Nuclear Medicine, vol. 59, pp. 411-411, 2018.

  • F. Yang, R. Tabassum, A. Becker, J. S. Sanchez, G. El Fakhri, Q. Li, et al., "JOINT DEBLURRING OF LONGITUDINAL DIFFERENTIAL PET IMAGES OF TAU," Alzheimer's & Dementia: The Journal of the Alzheimer's Association, vol. 14, p. P167, 2018.

  • D. Wu, K. Kim, and Q. Li, "Computationally Efficient Cascaded Training for Deep Unrolled Network in CT Imaging," arXiv preprint arXiv:1810.03999, 2018.

  • D. Wu, K. Kim, B. Dong, G. El Fakhri, and Q. Li, "End-to-End Lung Nodule Detection in Computed Tomography," in International Workshop on Machine Learning in Medical Imaging, 2018, pp. 37-45.

  • X. Wang, X. Zhen, Q. Li, D. Shen, and H. Huang, "Cognitive assessment prediction in Alzheimer’s disease by multi-layer multi-target regression," Neuroinformatics, vol. 16, pp. 285-294, 2018.

  • J. H. Thrall, X. Li, Q. Li, C. Cruz, S. Do, K. Dreyer, et al., "Artificial intelligence and machine learning in radiology: opportunities, challenges, pitfalls, and criteria for success," Journal of the American College of Radiology, vol. 15, pp. 504-508, 2018.

  • J. Sepulcre, M. J. Grothe, F. d. O. Uquillas, L. Ortiz-Terán, I. Diez, H.-S. Yang, et al., "Neurogenetic contributions to amyloid beta and tau spreading in the human cortex," Nature medicine, vol. 24, p. 1910, 2018.

  • D. Pantazis, M. Fang, S. Qin, Y. Mohsenzadeh, Q. Li, and R. M. Cichy, "Decoding the orientation of contrast edges from MEG evoked and induced responses," NeuroImage, vol. 180, pp. 267-279, 2018.

  • X. Li, Q. Chen, X. Wang, N. Guo, N. Wu, and Q. Li, "Network Modeling and Pathway Inference from Incomplete Data (" PathInf")," arXiv preprint arXiv:1810.00839, 2018.

  • K. Kim, D. Wu, K. Gong, J. Dutta, J. H. Kim, Y. D. Son, et al., "Penalized PET reconstruction using deep learning prior and local linear fitting," IEEE transactions on medical imaging, vol. 37, pp. 1478-1487, 2018.

  • K. Kim, J. Dutta, A. Groll, G. El Fakhri, L.-J. Meng, and Q. Li, "A novel depth-of-interaction rebinning strategy for ultrahigh resolution PET," Physics in Medicine & Biology, vol. 63, p. 165011, 2018.

  • Z. Guo, X. Li, H. Huang, N. Guo, and Q. Li, "Medical image segmentation based on multi-modal convolutional neural network: study on image fusion schemes," in 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018), 2018, pp. 903-907.

  • K. Gong, J. Yang, K. Kim, G. El Fakhri, Y. Seo, and Q. Li, "Attenuation Correction of PET/MR Using Deep Neural Network Based on Dixon and ZTE MR Images," Journal of Nuclear Medicine, vol. 59, pp. 650-650, 2018.

  • K. Gong, J. Yang, K. Kim, G. El Fakhri, Y. Seo, and Q. Li, "Attenuation correction for brain PET imaging using deep neural network based on Dixon and ZTE MR images," Physics in Medicine & Biology, vol. 63, p. 125011, 2018.

  • K. Gong, K. Kim, J. Cui, N. Guo, C. Catana, J. Qi, et al., "Learning personalized representation for inverse problems in medical imaging using deep neural network," arXiv preprint arXiv:1807.01759, 2018.

  • K. Gong, J. Guan, K. Kim, X. Zhang, J. Yang, Y. Seo, et al., "Iterative PET image reconstruction using convolutional neural network representation," IEEE transactions on medical imaging, vol. 38, pp. 675-685, 2018.

  • K. Gong, C. Catana, J. Qi, and Q. Li, "PET Image Reconstruction Using Deep Image Prior," IEEE transactions on medical imaging, 2018.

  • Y. Chang, G. C. Sharp, Q. Li, H. A. Shih, G. El Fakhri, J. B. Ra, et al., "Subject-specific brain tumor growth modelling via an efficient Bayesian inference framework," in Medical Imaging 2018: Image Processing, 2018, p. 105742I.

  • P. Bandi, O. Geessink, Q. Manson, M. Van Dijk, M. Balkenhol, M. Hermsen, et al., "From detection of individual metastases to classification of lymph node status at the patient level: the CAMELYON17 challenge," IEEE transactions on medical imaging, vol. 38, pp. 550-560, 2018.

2017

  • B. Ehteshami Bejnordi, M. Veta, P. Johannes van Diest, B. van Ginneken, N. Karssemeijer, G. Litjens, JAWM. van der Laak; the CAMELYON16 Consortium, M. Hermsen, QF. Manson, M. Balkenhol, O. Geessink, N. Stathonikos, MC. van Dijk, P. Bult, F. Beca, AH. Beck, D. Wang, A. Khosla, R. Gargeya, H. Irshad, A. Zhong, Q. Dou, Q. Li, et., Diagnostic Assessment of Deep Learning Algorithms for Detection of Lymph Node Metastases in Women With Breast Cancer, JAMA,vol 318, no 22, pp:2199-2210,  2017.

View in: PubMed

  • R. Ju, C. Hu, P. Zhou, Q. Li, Early Diagnosis of Alzheimer's Disease Based on Resting-State Brain Networks and Deep Learning, IEEE/ACM Transactions on Computational Biology and Bioinformatics, Volume: PP, Issue: 99, 2017​

  • K. Kim, G. El Fakhri, Q. Li, Low-dose CT reconstruction using spatially encoded nonlocal penalty. Med Phys, vol 44, no 10, pp:e376-e390,  2017.

View in: PubMed

  • J. Yang, C. Hu, N. Guo, J. Dutta, LM. Vaina, KA. Johnson, J. Sepulcre, GE. Fakhri, Q. Li, Partial volume correction for PET quantification and its impact on brain network in Alzheimer's disease, Sci Rep, vol 7, no 1, pp:13035,  2017.

View in: PubMed

  • D. Wu, K. Kim, G. El Fakhri, Q. Li, Iterative Low-Dose CT Reconstruction With Priors Trained by Artificial Neural Network, IEEE Trans Med Imaging, vol 36, no 12, pp:2479-2486, 2017.

View in: PubMed

  • S. Jeong, X. Li, J. Yang, Q. Li, V. Tarokh, Dictionary Learning and Sparse Coding-Based Denoising for High-Resolution Task Functional Connectivity MRI Analysis, International Workshop on Machine Learning in Medical Imaging MLMI 2017: Machine Learning in Medical Imaging pp 45-52

  • X. Li, A. Zhong, M. Lin, N. Guo, M. Sun, A. Sitek, J.  Ye, J.  Thrall, Q.  Li, Self-paced Convolutional Neural Network for Computer Aided Detection in Medical Imaging Analysis, International Workshop on Machine Learning in Medical Imaging MLMI 2017: Machine Learning in Medical Imaging pp 212-219

  • S. Roy Chowdhury, J. Yang, G. El Fakhri, Q. Li, J. Dutta, Joint Segmentation of Multi-Channel Images Using Multigraph Cuts, J Nucl Med May 1, 2017 vol. 58no. supplement 1 1308

  • D. Pantazis, M. Fang, S. Qin, Y. Mohsenzadeh, Q. Li, RM. Cichy, Decoding the orientation of contrast edges from MEG evoked and induced responses, Neuroimage, pii: S1053-8119(17)30590-6, 2017.

View in: PubMed

  • K. Kim, Y. Don Son, G. El Fakhri, Q. Li, Penalized direct estimation using joint similarity of kinetic images with partial dynamic data, J Nucl Med May 1, 2017 vol. 58no. supplement 1 1304

  • H. Farhadi, Y. Xiang, S. Jeong, X. Li, N. Guo, J. Sepulcre, V. Tarokh, Q. Li, Inferring the causality network of Abeta and Tau accumulation in the aging brain: a statistical inference approach, J Nucl Med May 1, 2017 vol. 58no. supplement 1 803

  • K. Gong, J. Guan, K. Kim, X. Zhang, G. El Fakhri, J. Qi, Q. Li, Iterative PET Image Reconstruction Using Convolutional Neural Network Representation, arXiv:1710.03344 [cs.CV]

View in: PDF

  • Y. Lu, A. Zhong, Q. Li, B. Dong, Beyond Finite Layer Neural Networks: Bridging Deep Architectures and Numerical Differential Equations, arXiv:1710.10121 [cs.CV]

View in: PDF

  • D. Wu, K. Kim, G. El Fakhri, Q. Li, A Cascaded Convolutional Neural Network for X-ray Low-dose CT Image Denoising,
    arXiv:1705.04267 [cs.CV]

View in: PDF

  • A. Groll, K. Kim, Q. Li, L. Meng, Ultrahigh Resolution Coplanar PET Imaging of Microfluidic Devices for Synthesizing PET Radiopharmaceuticals, J Nucl Med May 1, 2017 vol. 58 no. supplement 1 90

  • M. Zhang, X. Li, M. Xu, Q. Li, Image Segmentation and Classification for Sickle Cell Disease using Deformable U-Net, arXiv:1710.08149 [q-bio.CB]

View in: PDF

  • N. Guo, Z. Guo, N. Shusharina, Z. Liao, G. El Fakhri, Q. Li, SVM based Radiomics Analysis using Pre-radiotherapy PET/CT Increases the Prediction Accuracy of Radiation Pneumonitis, J Nucl Med May 1, 2017 vol. 58 no. supplement 1 501

  • C. Su, J. Dutta, H. Zhang, G. El Fakhri, Q. Li, Image deblurring using a joint entropy prior in x-ray luminescence computed tomography, Proc. SPIE 10137, Medical Imaging 2017: Biomedical Applications in Molecular, Structural, and Functional Imaging, 1013706 (13 March  2017)

  • D. Wu, K. Kim, B. Dong, Q. Li, End-to-End Abnormality Detection in Medical Imaging, arXiv:1711.02074 [cs.CV]

View in: PDF

  • Z. Guo, X. Li, H. Huang, N. Guo, Q. Li, Medical Image Segmentation Based on Multi-Modal Convolutional Neural Network: Study on Image Fusion Schemes, arXiv:1711.00049 [cs.CV]

View in: PDF

  • S. Shi, X. Li, A. Sitek, Q. Li, Learning the Sparse and Low Rank PARAFAC Decomposition via the Elastic Net,
    arXiv:1705.10015 [math.NA]

View in: PDF

  • Q. Li, H. Li, K. Kim, G. El Fakhri, Joint estimation of activity image and attenuation sinogram using time-of-flight positron emission tomography data consistency condition filtering, J Med Imaging (Bellingham), vol 4, no 2, pp:023502, 2017.

View in: PubMed

  • J. Sepulcre, MR. Sabuncu, Q. Li, G. El Fakhri, R. Sperling, KA. Johnson, Tau and amyloid β proteins distinctively associate to functional network changes in the aging brain, Alzheimers Dement, vol 13, no 11, pp:1261-1269, 2017.

View in: PubMed

2016

  • C. Hu, X. Hua, J. Ying, PM. Thompson, GE. Fakhri, Q. Li, Localizing Sources of Brain Disease Progression with Network Diffusion Model, IEEE J Sel Top Signal Process. vol 10, no 7, pp:1214-1225, 2016.

View in: PubMed

  • C. Hu**, X. Hua, P. M. Thompson, J. Ying, G. E. Fakhri, and Q. Li, Inferring Sources of Dementia Progression with Network Diffusion Model, IEEE Journal of Selected Topics in Signal Process, Accepted, 2016

         view in: PubMed

  • A. Sitek, Q. Li, G. El Fakhri and N. Alpert, Validation of Bayesian Analysis of Compartmental Kinetic Models in Medical Imaging, Physica Medica, accepted

         view in: PubMed

  • A. Groll, K. Kim, H. Bhatia, J. C. Zhang, J. H. Wang, Z. M. Shen, L. Cai, J. Dutta, Q. Li, and L. J. Meng, Hybrid Pixel-Waveform (HPWF) Enabled CdTe Detectors for Small Animal Gamma-Ray Imaging Applications, IEEE Transaction on Nuclear Sciences, accepted

         view in: PubMed

  • C. Hu**, R. Ju, Y. Shen, P. Zhou and Q. Li, Clinical Decision Support and Disease Prediction from E-Health Systems, ICC, 2016                                 Media Coverage -- IEEE Sprectrum

  • Q. Li, E. Asma, J. Qi, J. R. Bading and R. M. Leahy, Accurate Estimation of the Fisher Information Matrix for the PET Image Reconstruction Problem, in proceedings of IEEE Nuclear Science Symposium and Medical Imaging Conf., 2003, Portland, OR, vol.3, pp:2012- 2016

         view in: PubMed

  • A. Groll, K. Kim, J. Smith, J. Kroeger, H. Bhatia, J. Dutta, Q. Li and L. J. Meng, An Experimental Evaluation of a Hybrid Pixel-Waveform CdTe Based Prototype PET Detector Against Commercial MicroPET for Imaging Tau Protein Pathology in Transgenic Mouse Brain Tissue, in proceedings of IEEE Nuclear Science Symposium Medical Imaging Conf., 2016, accepted

  • J. Dutta, G. El Fakhri and Q. Li, PET Image Denoising Using Anatomically Guided Non-Local Euclidean Medians, in proceedings of IEEE Nuclear Science Symposium Medical Imaging Conf., 2016, accepted

  • K. Kim, G. El Fakhri and Q. Li, Penalized joint direct estimation using partial dynamic data for parametric imaging in PET, in proceedings of IEEE Nuclear Science Symposium Medical Imaging Conf., 2016, accepted

  • K. Kim, J. Yang, G. El Fakhri, Y. Seo and Q. Li, Penalized MLAA using a MR-based Spatially-encoded Anatomic Prior in TOF PET/MR, in proceedings of IEEE Nuclear Science Symposium Medical Imaging Conf., 2016, accepted

  • H. Yang, K. Kim, G. El Fakhri, K. Kang, Y. Xing and Q. Li, Dual-energy CT reconstruction using guided image filtering, in proceedings of IEEE Nuclear Science Symposium Medical Imaging Conf., 2016, accepted

2015

  • K. Kim**, J. C. Ye, W. Worstell, J. Ouyang, Y. Rakvongthaia, G. El Fakhria and Q. Li. Sparse-view Multi-energy CT Reconstruction using Spectral Patch-based Low-rank Penalty, IEEE Transactions on Medical Imaging, vol. 34, no. 3, pp:748-760, 2015

         view in: PubMed

  • N. Guo**, F. Zhang, X. Zhang, J. Guo, L. Lang, D. O. Kiesewetter, G. Niu, Q. Li* and Chen, X. Quantitative Evaluation of Tumor Early Response to a Vascular-Disrupting Agent with Dynamic PET. Molecular Imaging and Biology, in press, 2015.

         view in: PubMed

  • C. Hu**, L. Cheng, J. Sepulcre, K. Johnson, G. El Fakhri, Y. M. Lu and Q. Li, A Spectral Graph Regression Model for Learning Brain Connectivity of Alzheimer's Disease. Plos One, in press, 2015

         view in: PubMed

  • J. Dutta**, C. Huang, Q. Li* and G. El Fakhri, Pulmonary Imaging Using Respiratory Motion Compensated Simultaneous PET/MR. Medical Physics, vol. 42, no. 7, pp:4227-4240, 2015

        Cover Paper of vol. 42, no. 7 at Physics in Medical Physics, 2015

         view in: PubMed

  • M. Wang**, N. Guo, G. Hu, G. El Fakhri, H. Zhang and Q, Li, A novel approach to assess the treatment response using Gaussian random field in PET. Medical Physics, accepted, 2015

         view in: PubMed

  • C. Hu**, J. Sepulcre, K. Johnson, G. El Fakhri, Y. M. Lu and Q. Li, Matched Signal Detection on Graphs: Theory and Application to Brain Imaging Data Classification. Neuroimage, accepted, 2015

         view in: PubMed

  • K. S. Grogg, T. Toole, J. Ouyang, X. Zhu, M. D. Normandin, Q. Li, K. Johnson, N. M. Alpert, and G. El Fakhri, National Electrical Manufacturers Association and Clinical Evaluation of a Novel Brain PET/CT Scanner, J Nucl Med, 2016 57:646-652

         view in: PubMed

  • W. Zhu**, N. Guo, B. Bai, P. Conti, R. M. Leahy and Q. Li, Direct Estimation from List-Mode Data for Reversible Tracers using Graphical Modeling, IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2015, accepted

  • J. Dutta**, G. El Fakhri, X. Zhu and Q. Li, PET Point Spread Function Modeling and Image Deblurring using a PET/MRI Joint Entropy Prior. IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2015, accepted

  • K. Kim**, J. Dutta, A. Groll, L. Meng, G. EI Fakhri and Q. Li, Penalized Maximum Likelihood Reconstruction of Ultrahigh Resolution PET with Depth of Interaction, in proceedings of Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, 2015, accepted

  • M. Wang**, G. Hu, G. EI Fakhri, H. Zhang and Q. Li, Improvement of Variance in TOF-PET using Iterative Image Reconstruction, in proceedings of Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, 2015, accepted

  • J. Dutta**, G. El Fakhri and Q. Li, A Data-Driven Framework to Optimize External Marker Positioning for Internal Motion Tracking, in proceedings of Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, 2015, accepted

  • K. Kim**, G. El Fakhri and Q. Li, Penalized Direct Estimation of Parametric Images in PET, in proceedings of IEEE Nuclear Science Symposium Medical Imaging Conf., 2015, accepted

         view in: PubMed

  • K. Kim**, G. El Fakhri and Q. Li, Non-local and Motion-based Low-rank Regularizations for Gated CT, in proceedings of IEEE Nuclear Science Symposium Medical Imaging Conf., 2015, accepted

  • N. Guo**, R-F. Yen, G. El Fakhri and Q. Li, SVM Based Staging for Lung Cancer Patients using Multiple Image Features in PET/CT, in proceedings of IEEE Nuclear Science Symposium Medical Imaging Conf., 2015, accepted

  • G. Gao, X. Lai, H. Li, Q. Li and L. Meng, Experimental Evaluation of Prototype Compound Eye Camera for Use in the Second Generation of MRI Compatible SPECT Imaging, in proceedings of IEEE Nuclear Science Symposium Medical Imaging Conf., 2015, accepted

  • M. Q. Wilks**, G. El Fakhri, N.M. Alpert and Q. Li, A Joint Estimation Method for Kinetic Modeling of Simultaneously Acquired PET/MRI Signals, in proceedings of IEEE Nuclear Science Symposium Medical Imaging Conf., 2015, accepted

  • M. Wang**, G. Hu, G. El Fakhri, H. Zhang and Q. Li, Fast Estimation of Image Variance for Time-of-Flight PET Reconstruction, in proceedings of IEEE Nuclear Science Symposium Medical Imaging Conf., 2015, accepted

  • J. Dutta, G. El Fakhri and Q. Li, Spatially Encoded Joint Entropy Prior for PET Image Deblurring, in proceedings of IEEE Nuclear Science Symposium Medical Imaging Conf., 2015, accepted

2014

  • J. Guo**, N. Guo, L. Lang, D. O. Kiesewetter, Q. Xie, Q. Li, H. S. Eden, G. Niu, X. Chen, 18F-Alfatide II and 18F-FDG Dual Tracer Dynamic PET for Parametric, Early Prediction of Tumor Response to Therapy, Journal of Nuclear Medicine, vol 55, no 1, pp:154-160, 2014

  • Y. Lin**, J. P. Haldar, Q. Li and R. M. Leahy. Sparse Constrained Mixture Modeling for the Estimation of Kinetic Parameters in Dynamic PET, IEEE Transactions on Medical Imaging, vol 33, no 1, pp:173-185, 2014.

  • B Bai, Y Lin, W Zhu, R Ren, Q. Li, M Dahlbom, F Di Filippo, RM Leahy, MAP Reconstruction for Fourier Rebinned TOF-PET Data, Physics in Medicine and Biology, vol 59, no 4, pp:925-949, 2014

  • W. Zhu**, Q. Li, B Bai, PS Conti, RM Leahy, Patlak Image Estimation from Dual Time-point List-mode PET Data, IEEE Transactions on Medical Imaging, vol 33, no4, pp:913-924, 2014

  • Y. Petibon, C. Huang, J. Ouyang, T. G Reese, Q. Li, S. Syrkina, Y-L Chen and G. El Fakhri, Relative Role of Motion and PSF Compensation in Whole-body Oncologic PET-MR Imaging, Medical Physics, vol 41, no 4, 042503, 2014

  • C. Hu**, G. El Fakhri and Q. Li, Evaluating Structural Symmetry of Weighted Brain Networks via Graph Matching, In Medical Image Computing and Computer-Assisted Intervention–MICCAI 2014, pp. 733-740. Springer International Publishing, 2014

  • A. Lorsakul**, Q. Li*, C. M. Trott, C. Hoog, Y. Petibon, J. Ouyang, A. F. Laine, and G. El Fakhri. Four-Dimensional Numerical Observer for Lesion Detection in Respiratory-Gated PET, Medical Physics, vol. 41, no. 10 (2014): 102504.

  • C. Hu**, X. Hua, P. M. Thompson, G. El Fakhri and Q. Li, Inferring Sources of Dementia Progression with Network Diffusion Model, In Machine Learning in Medical Imaging, pp. 42-49. Springer International Publishing, 2014

  • K. Kim**, J. C. Ye, L. Cheng, K. Ying, G. El Fakhri and Q. Li, TOF-PET Ordered Subset Reconstruction using Non-Uniform Separable Quadratic Surrogates Algorithm, IEEE International Symposium on Biomedical Imaging: From Nano to Macro, pp.393-396, 2014

  • K. Kim**, J. C. Ye, G. El Fakhri and Q. Li, Metal Artifact Reduction using l1 norm and Non-Local Penalties with Iterative Sinogram Correction, in proceedings of the third international conference on image formation in X-ray computed tomography, pp.393-396, Salt Lake City, 2014

  • X.-C. Lai, J. George, H. Li, Q. Li, L.-J. Meng, Microscopic SPECT Imaging with Inverted Compound Eye Cameras, in proceedings of IEEE Nuclear Science Symposium Medical Imaging Conf., 2014.

  • J. Dutta**, M. Chelala, X. Shao, A. Lorsakul, Q. Li, G. El Fakhri, Accuracy of Respiratory Motion Compensated Image Reconstruction Using 4DPET-Derived Deformation Fields, in proceedings of IEEE Nuclear Science Symposium Medical Imaging Conf., 2014.

  • H. Li**, G. El Fakhri, A. A. Joshi, Q. Li, An ADMM Reconstruction Algorithm for Joint Registration and Attenuation Correction in Transmission-Less Gated TOF PET, in proceedings of IEEE Nuclear Science Symposium Medical Imaging Conf., 2014.

  • M. Wang**, H. Zhang, G. El Fakhri, Q. Li, The Evaluation of Treatment Response Using Gaussian Random Field Theory, in proceedings of IEEE Nuclear Science Symposium Medical Imaging Conf., 2014.

  • A. Lorsakul**, G. El Fakhri, J. Ouyang, W. Worstell, Y. Rakvongthai, A. F. Laine, Q. Li, Numerical Observer for Objective Assessment on Carotid Plaque Using Spectral CT, in proceedings of IEEE Nuclear Science Symposium Medical Imaging Conf., 2014.

2013

  • B. Bai, Q. Li and R. M. Leahy, Magnetic Resonance-Guided Positron Emission Tomography Image Reconstruction, Seminars in Nuclear Medicine, vol 43, no 1, pp:30-44, 2013

  • J. Ouyang, Q. Li and G. El Fakhri, Magnetic Resonance-Based Motion Correction for Positron Emission Tomography Imaging, Seminars in Nuclear Medicine, vol 43, no 1, pp:60-67, 2013

  • Y. Rakvongthai**, J. Ouyang, B. Guerin, Q. Li, N. M. Alpert, and G. El Fakhri, Reconstruction of Cardiac PET Kinetic Parametric Images Using a Preconditioned Conjugate Gradient Approach, Medical Physics, vol 40, no 10, 102501, doi: 10.1118/1.4819821, 2013

  • Y. Petibon, J. Ouyang, T. G. Reese, C. Huang, X. Zhu, S. Y. Chun, Q. Li and G El Fakhri, Cardiac Motion Compensation and Resolution Modeling in Simultaneous PET-MR: a cardiac lesion detection study, Physics in Medicine and Biology, vol 58, no 7, pp: 2085-2102, 2013

  • C. Hu**, L. Cheng, J. Sepulcre, G. El Fakhri, Y. M. Lu and Q. Li, Matched Signal Detection on Graphs: Theory and Application to Brain Network Classification, Information Processing in Medical Imaging, Lecture Notes in Computer Science, vol 7917, pp 1-12, 2013                   Most downloaded paper in this issue

  • B. E. Fisher, Q. Li, Angelo Nacca, G. J. Salem, J. Song, J. Yip, J. S. Hui, M. W. Jakowec, and G. M. Petzinger. Treadmill Exercise Elevates Striatal Dopamine D2 Receptor Binding Potential in Patients with Early Parkinson’s Disease, Neuro Report, vol. 24, no. 10, pp: 509-514, 2013.

  • J. Dutta**, S. Ahn and Q. Li, Quantitative Statistical Methods for Image Quality Assessment, Theranostics, vol 3, no 10, pp:741-756, 2013.

  • J. Dutta**, R. M. Leahy and Q. Li, Non-Local Means Denoising of Dynamic PET Images, Plos One, vol.8, no 12, e81390, 2013

  • C. Hu**, L. Cheng, J. Sepulcre, G. El Fakhri, Y. M. Lu and Q. Li, A Graph Theoretical Regression Model for Brain Connectivity Learning of Alzheimer's Disease, IEEE International Symposium on Biomedical Imaging: From Nano to Macro, pp.616-619, 2013

  • J. Dutta**, G. El Fakhri, C. Huang, Y. Petibon, T. G. Reese, and Q Li. Respiratory Motion Compensation in Simultaneous PET/MR Using a Maximum a Posteriori Approach, IEEE International Symposium on Biomedical Imaging: From Nano to Macro, pp.800-803, 2013

  • W. Zhu**, B. Bai, P. S. Conti, Q. Li, and R. M. Leahy, Data Correction Methods for Wholebody Patlak Imaging from List-mode PET Data, in proceedings of Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, pp:213-217, 2013

  • Y. Lin**, B. Bai, W. Zhu, R. Ren, Q. Li, and R. M. Leahy, Optimized MAP Reconstruction of H2-weighted Fourier Rebinned TOF PET, in proceedings of Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, pp:292-296, 2013

  • H. Li**, G. EI Fakhri, and Q. Li, Direct MAP Estimation of Attenuation Sinogram using TOF PET Data and Anatomical Image, in proceedings of Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, pp:404-408, 2013

  • Q. Li. Quantitative Methods for Molecular Diagnostic and Therapeutic Imaging. Theronostics, vol. 3, no.10, pp: 729–730, 2013

2012

  • L. Zhu, N. Guo, Y. Ma, O. Jacboson, S. Lee, H. S. Choi, Q. Li, G. Niu and X. Chen, Dynamic PET and Optical Imaging and Compartment Modeling using a Dual-labeled Cyclic RGDyK Peptidic Probe, Theranostics, vol.2, no. 8, pp:746-756, 2012

  • W. Zhu**, Q. Li and R. Leahy, Dual-time-point Patlak Estimation from List Mode PET Data, in proceedings of IEEE International Symposium on Biomedical Imaging: From Nano to Macro, pp.486-489, 2012.

  • Y. Lin**, Q. Li, Justin Haldar and R. Leahy, Constrained Mixture Modeling For the Estimation of Kinetic Parameters in Dynamic PET, in proceedings of IEEE International Symposium on Biomedical Imaging: From Nano to Macro, pp.1004-1007, 2012

  • J. Dutta**, G. El Fakhri, Y. Lin, R. M. Leahy and Q. Li, Spatially Varying Regularization for Motion Compensated PET Reconstruction, in proceedings of IEEE Nuclear Science Symposium Medical Imaging Conf., pp.2156-2160, 2012

  • Y. Lin**, J. P. Haldar, Q. Li and R. M. Leahy, Kinetic Parameter Estimation in Dynamic PET with a Sparsity-Regularized Mixture Model, in proceedings of IEEE Nuclear Science Symposium Medical Imaging Conf., 2012

  • R. Ren**, B. Bai, Q. Li and R. M. Leahy, Optimizing MAP reconstruction of 3D TOF PET, in proceedings of IEEE Nuclear Science Symposium Medical Imaging Conf., 2012

  • W. Zhu**, B. Bai, P. S. Conti, Q. Li and R. M. Leahy, Dynamic PET With Partial Data for Application to Whole Body Studies, in proceedings of IEEE Nuclear Science Symposium Medical Imaging Conf., 2012

2011

  • S. Somayajula**, C. Panagiotou, A. Rangarajan, Q. Li, S.R. Arridge and R.M. Leahy, PET Image Reconstruction Using Information Theoretic Anatomical Priors, IEEE Transactions on Medical Imaging, vol 30, no 3, pp:537-549, 2011

  • S. Ahn, S. Cho, Q. Li and R.M. Leahy, Optimal Rebinning of Time-of-Flight PET Data, IEEE Transactions on Medical Imaging, vol. 30, no. 10, pp:1808-1818, 2011

2010

  • M. G. Vuckovic, Q. Li, B Fisher, A Nacca, R. M. Leahy, J. P. Walsh, M. W. Jakowec and G. M. Petzinger, Exercise Elevates Dopamine D2 Receptor in a Mouse Model of Parkinson's Disease: in vivo Imaging with [18F]fallypride, Movement Disorders, vol 25, no 16, pp:2777-2784, 2010     Cover paper of Movement Disorder, vol. 25, no. 16

  • A. Joshi, D. Pantazis, Q. Li, D.W. Shattuck, L.E. Bernstein and R.M. Leahy, Sulcal Set Optimization for Cortical Surface Registration, NeuroImage, vol. 50, no. 3, pp:950-959, 2010

  • R. Ren**, Q. Li, S. Ahn, S. Cho and R. M. Leahy, Estimation of Gap Data Using Bow-Tie Filters for 3D Time-of-Flight PET, in proceedings of IEEE Nuclear Science Symposium Medical Imaging Conf., pp.2691-2694, 2010

  • Y. Lin**, Q. Li and R. M. Leahy, Fast GPU-based forward and back projection in MAP Reconstruction with a factored system matrix, in proceedings of IEEE Nuclear Science Symposium Medical Imaging Conf., 2010

  • W. Zhu**, R. M. Leahy, P.S. Conti and Q. Li, Longitudinal Registration of Liver PET Scans Using Four Phase CT, in proceedings of IEEE Nuclear Science Symposium Medical Imaging Conf., pp.2366-2369, 2010

  • Q. Li and R. M. Leahy. A Practical Approximation of Variance of OSEM Reconstruction, in proceedings of IEEE Nuclear Science Symposium Medical Imaging Conf., 2010

2009

  • Z. Li**, Q. Li, X. Yu, P.S. Conti and R.M. Leahy, Lesion Detection in Dynamic FDG-PET Using Matched Subspace Detection, IEEE Transactions on Medical Imaging, vol. 28, no. 2, pp:230–240, 2009

  • S. Scho**, S. Ahn, Q. Li and R.M. Leahy, Exact and Approximate Fourier Rebinning of PET Data from Time-of Flight to Non Time-of-Flight, Physics in Medicine and Biology, vol 54, no. 3, pp: 467-484, 2009.                                                                                                                             Featured Paper of vol. 54, no. 3 at Physics in Medicine and Biology, 2009                                                                                                                Selected Paper, among all papers published at Institute of Physics journals in 2009                                                                                                Finalist of the Roberts best paper prize, second place, among all the papers in 2009

  • Z. Li**, Q. Li, D. Pantazis, X. Yu and R. M. Leahy, Controlling Familywise Error Rate for Matched Subspace Detection in Dynamic FDG PET, IEEE Transactions on Medical Imaging, vol 28, no. 10, pp: 1623-1631, 2009

  • A. A. Joshi, D. Pantazis, H. Damasio, Q. Li, D. W. Shattuck, L. E. Bernstein and R. M. Leahy, Optimization of Landmark Selection for Cortical Surface Registration, Computer Vision and Pattern Recognition IEEE conference in CVPR, pp:699-706, 2009

  • S. Somayajula**, B. Bai, Q. Li, and R. M. Leahy, Positron Range Correction Using Information Theoretic Anatomical Priors, in Proc. IEEE Nuclear Science Symposium Medical Imaging Conf., 2009

  • Y. Lin**, Q. Li, and R. M. Leahy, Kinetic Parameters Estimation for Heterogeneous Tumor Model, in proceedings of IEEE Nuclear Science Symposium Medical Imaging Conf., pp.3069-3073, 2009

  • S. Ahn, S. Cho, Q. Li, and R. M. Leahy, Optimal Weighting for Fourier Rebinning of Three-Dimensional Time-of-Flight PET Data to Non-Time-of-Flight, in proceedings of IEEE Nuclear Science Symposium Medical Imaging Conf., pp.2989-2996, 2009 

  • Q. Li, B. Bai, A. Simth and R.M. Leahy, Count Independent Resolution and Its Calibration, in proceedings of The Tenth International Meeting on Three Dimensional Image Reconstruction in Radiology and Medicine, pp.223-224, 2009

  • Q. Li, R. M. Leahy, Direct Estimation of Patlak Parameters from List Mode PET Data, in proceedings of IEEE International Symposium on Biomedical Imaging: From Nano to Macro, pp.390-393, 2009.

  • M G. Vuckovic, G. M. Petzinger, J. VanLeeuwen, A. Nacca, Q. Li, R.M. Leahy, G. Akopian, J. P. Walsh, and M. W. Jakowec. Molecular Mechanisms of Normalized Dopamine and Glutamate Neurotransmission After High Intensity Exercise in the MPTP Mouse Model of Basal Ganglia Injury, in the Workshop of Plasticity and Repair in Neurodegenerative Disorders, 2009

2008

  • S. Scho**, S. Ahn, Q. Li and R.M. Leahy, Analytical Properties of TOF PET data, Physics in Medicine and Biology, vol 53, no. 11, pp:2809–2821, 2008.                                                                                                                                                                                                                Featured Paper of vol. 53, no. 11 at Physics in Medicine and Biology, 2008                                                                                                            Finalist of the Roberts best paper prize, second place, for all the papers in 2008

  • S. Cho**, S. Ahn, Q. Li, and R. M. Leahy, Fourier Rebinnings from Time-of-Flight PET Data to Non Time-of-Flight Data, in proceedings of IEEE Nuclear Science Symposium Medical Imaging Conf., 2008

2007

  • Q. Li, E. Asma, S. Ahn and R.M. Leahy. A Fast Fully 4D Incremental Gradient Reconstruction Algorithm for List Mode PET Data, IEEE Transactions on Medical Imaging, vol 26, no. 1, pp:58-67, 2007

  • S.Cho**, Q. Li, S. Ahn and R.M. Leahy. Fast Projectors for Iterative 3D PET Reconstruction, IEEE Transactions on Medical Imaging, vol 26, no. 3, pp: 347–358, 2007     

  • Q. Li and R. M. Leahy, Variance Approximation for Exponential Family Penalized Mzximum Likelihood Estimation: Application to Kinetic Parametric Estimation, in proceedings of 2007 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, pp.916-919, 2007

  • Q. Bao, B. Bai, Q. Li, A. Smith and A. Chatziioannou. Evaluation of Maximum a Posteriori (MAP) Reconstruction on MicroPET Scanner, in proceedings of IEEE Nuclear Science Symposium Medical Imaging Conf., 2007

  • S. Cho**, Q. Li, S. Ahn and R. M. Leahy, A New Exact Fourier Rebinning Method for Time-of-Flight PET, in proceedings of IEEE Nuclear Science Symposium Medical Imaging Conf., 2007

  • Z. Li**, Q. Li, D. Pantazis, X. Yu and R. M. Leahy, Controlling Familywise Error Rate for Matched Subspace Detection in Dynamic FDG PET, in proceedings of by IEEE Nuclear Science Symposium Medical Imaging Conf., 2007

2006

  • Q. Li and R.M. Leahy, Statistical Modeling and Reconstruction of Randoms Precorrected PET Data, IEEE Transactions on Medical Imaging, vol 25, no. 12, pp: 1565-1572, 2006

  • Z. Li**, Q. Li, X. Yu, P. S. Conti and R. M. Leahy, Matched Subspace Detection for Dynamic PET: An ROC Phantom Study for MAP Reconstruction, in proceedings of 2006 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, pp.1332-1335, 2006

  • Q. Li and R. M. Leahy, Statistical Modeling and Reconstruction of Randoms Pre-corrected PET Data, in proceedings of 2006 IEEE International Symposium on Biomedical Imaging: From Nano to Macro

  • Z. Li**, Q. Li, X. Yu, P. S. Conti, and R. M. Leahy, Performance of Matched Subspace Detectors for Dynamic FDG PET, in proceedings of IEEE Nuclear Science Symposium Medical Imaging Conf., 2006

  • S. Cho**, Q. Li, S. Ahn, and R. M. Leahy. On the Impact of Arc Correction and Axial Resampling in Inverse Fourier Rebinning, in proceedings of IEEE Nuclear Science Symposium Medical Imaging Conf., 2006

2005

  • S. Cho**, Q. Li, S. Ahn and R. M. Leahy, Fast Projectors for Iterative 3D PET reconstruction, in proceedings of IEEE Nuclear Science Symposium and Medical Imaging Conf., vol. 4, 2005

  • Q. Li, S. Ahn and R. M. Leahy, Fast Hybrid Algorithms for PET Image Reconstruction, in proceedings of IEEE Nuclear Science Symposium and Medical Imaging Conf., pp.5-8, 2005

2004

  • Y. Yang, Y.C. Tai, S. Siege, D.F. Newport, B. Bai, Q. Li, R.M. Leahy and S.R. Cherry, Optimization and Performance Evaluation of the MicroPET II Scanner for In Vivo Small-Animal Imaging, Physics in Medicine and Biology, vol. 49, no. 12, pp:2527–2545, 2004                                             Highlight Paper of vol. 49, no. 12 at Physics in Medicine and Biology, 2004

  • Q. Li, E. Asma, J. Qi, J. R. Bading and R. M. Leahy, Accurate Estimation of the Fisher Information Matrix for the PET Image Reconstruction Problem, IEEE Transactions on Medical Imaging, vol 23, no. 9, pp:1057-1064, 2004

  • Q. Li, E. Asma and R. M. Leahy, A Fast Fully 4D Incremental Gradient Reconstruction Algorithm for List Mode PET Data, in proceedings of 2004 IEEE International Symposium on Biomedical Imaging: from Nano to Macro,  Arlington, VA,  pp:555 -558,  2004

  • Q. Li, E. Asma and R. M. Leahy, Fast Fully 4D Dynamic PET Image Reconstruction Based on List Mode Data, in proceedings of IEEE Nuclear Science Symposium and Medical Imaging Conf., 2004, Roma, Italy

2002

  • B. Bai, Q. Li, C. H. Holdsworth, E. Asma, Y. C. Tai, A. Chatziioannou and R. M. Leahy, Model Based Normalization for Iterative 3D PET Reconstruction, Physics in Medicine and Biology, vol. 47, no. 15, pp:2785–2797, 2002.

2000

  • Q. Li, X. Gao, J. Ouyang. Methods for Removing Respiratory Interference from Thoracic Electrical Bioimpedance, Journal of Tsinghua University (Sci. & Tech.), vol.9, pp:003, 2000.

  • R. Li, P. Wang, Q. Zhang and Q. Li, The Study on a Novel Biochemical Image Sensor, Journal of Chinese Biomedical Engineering, vol.19, no.4, pp:382-386, 2000