PUBLICATIONS

2019

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2018

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Journal paper

1.Y. Lu, L. Shenand Y. Xu. Shadow Block Iteration for Solving Linear Systems Obtained from Wavelet Transforms. Applied and Computational Harmonic Analysis, 19(3), 2005, 359-385.

2. Y. Lu, L. Shenand Y. Xu. Multi-Parameter Regularization Methods for High-Resolution Image Reconstruction with Displacement Errors. IEEE Transactions on Circuits and Systems I: Regular Papers, 54(8), 2007, 1788-1799.

3. Z. Chen, Y. Lu, Y. Xu and H. Yang. Multi-Parameter Tikhonov Regularization for Linear Ill-posed Operator Equations. Journal of computational mathematics, 26(1), 2008, 37-55.

4. Y. Lu, L. Shenand Y. Xu. Integral Equation Models for Image Restoration: High Accuracy Methods and Fast Algorithms. Inverse Problems, 26(4), 2010, 045006, 32pp.(Inverse Problems Highlights collection in 2010)

5. Y. Lu, H.-P. Chan, J. Wei and L.M. Hadjiiski. Selective-diffusion Regularization for Enhancement of Microcalcifications in Digital Breast Tomosynthesis Reconstruction. Medical Physics, 37(11), 2010, 6003-14.

6. Y. Lu, H.-P. Chan, J. Wei, M. Goodsitt, P.L. Carson, L. Hadjiiski, A. Schmitz, J.W. Eberhard and B.E.H. Claus. Image Quality of Microcalcifications in Digital Breast Tomosynthesis: Effects of Projection-View Distributions. Medical Physics, 38(10), 2011, 5703-12.

7. B. Sahiner, H.-P. Chan, L. Hadjiiski, M. Helvie, J. Wei, C. Zhou and Y. Lu. Computer-aided Detection of Clustered Microcalcifications in Digital Breast Tomosynthesis: A 3D Approach. Medical Physics, 39(1), 2012, 28-39.

8. Y. Lu, H.-P. Chan, J. Wei,L. Hadjiiski. Diffusion-based Truncated Projection Artifact Reduction Method for Iterative Digital Breast Tomosynthesis Reconstruction. Physics in Medicine and Biology, 58(3), 2013, 569-87.

9. R. Samala, H.-P. Chan, Y. Lu, L. Hadjiiski, J. Wei, B. Sahiner and M. Helvie, Computer-aided detection of clustered microcalcifications in multiscale bilateral filtering regularized reconstructed digital breast tomosynthesis volume.Medical Physics, 41(2), 2014.

10. J. Wei, H.-P. Chan, L. Hadjiiski, M. Helvie,Y. Lu, C. Zhou and R. Samala, Multichannel response analysis on 2D projection views for detection of clustered microcalcifications in digital breast tomosynthesis, Medical Physics, 41(4), 2014.

11. R. Samala, H.-P. Chan, Y. Lu, L. Hadjiiski, J. Wei and M. Helvie, Digital breast tomosynthesis: computer-aided detection of clustered microcalcifications on planar projection images.Physics in Medicine and Biology, 59(23), 2014, 7457-77.

12. H.-P. Chan, M. Goodsitt, M. Helvie, S. Zelakiewicz, A. Schmitz, M. Noroozian, C. Paramagul, M. Roubidous, A. Nees, C. Neal, P. Carson, Y. Lu, L. Hadjiiski and J. Wei, Digital breast tomosynthesis: observer performance of clustered microcalcification detection on breast phantom images acquired with an experimental system using variable scan angles, angular increments, and number of projection views. Radiology, 273(3), 2014, 675-85.

13. Y. Lu, H.-P. Chan, J. Wei, L. Hadjiiski and R. Samala. Multiscale bilateral filtering for improving image quality in digital breasttomosynthesis. Medical Physics, 42(1), 2015, 182-195.­

14. R. Samala, H-P Chan, Y. Lu, L. Hadjiiski, J. Wei and M. Helvie. Computer-aided detection system for clustered microcalcifications in digital breast tomosynthesis using joint information from volumetric and planar projection images. Physics in medicine and biology, 60(21), 2015, 8457-79.

15. Y. Lin, H. Lin, Q. Lin, J. Zhang, P. Zhu, Y. Lu, Z. Zhao, J. Lv, M. Lee and Y. Xu, A novel three-dimensional smile analysis based on dynamic evaluation of facial curve contour. Scientific Reports 6, Article number: 22103, 2016.
16. W. Long, Y. Lu, L. Shen, Y. Xu. High-resolution image reconstruction: an envℓ1/TV model and a fixed-point proximity algorithm. International journal of numerical analysis, 14(2), 2017, 255-282.

17. L. Yan, Y. Guo, J. Qi, Q. Zhu, L. Gu, C. Zheng, T. Lin, Y. Lu, Z. Zeng, S. Yu, S. Zhu, X. Zhou, X. Zhang, Y. Du, Z. Yao, Y. Lu∗, X. Liu. Iodine and Freeze-Drying Enhanced High-Resolution MicroCT Imaging for Reconstructing 3D Intraneural Topography of Human Peripheral Nerve Fascicles. Journal of Neuroscience Methods, 2017, 287:58-67.

18. S. Xu, L. Feng, Y. Chen, Y. Sun, Y. Lu, S. Huang, Y. Fu, R. Zheng, Y. Zhang, and R. Zhang. Consistency mapping of 16 lymph node stations in gastric cancer by CT-based vessel-guided delineation of 255 patients. Oncotarget. 2017, 8(25): 41465–41473.

19. Y. Lu, H-P. Chan, J. Wei, L. Hadjiiski, R. Samala. Improving image quality for digital breast tomosynthesis: automated detection and diffusion-based method for metal artifact reduction. Physics in Medicine and Biology, 2017,62(19).

20. L. Lin, Y. Lu, X. Wang, H. Chen, S. Yu, J. Tian, G. Zhou, L. Zhang, Z. Qi, J. Hu, J. Ma, Y. Sun. Delineation of neck clinical target volume specific to nasopharyngeal carcinoma based on lymph node distribution and the international consensus guidelines. International Journal of Radiation Oncology, Biology, Physics, 2017,100(4):891-902.

21. S. Li, J. Wei, HP Chan, M. Helvie, M. Roubidoux, Y. Lu, C. Zhou, L. Hadjiiski, R. Samala. Computer-aided assessment of breast density: Comparison of supervised deep learning and feature based statistical learning. Physics in Medicine and Biology, 63 (2018) 025005
22. S. Li, J. Wei, HP Chan, M. Helvie, M. Roubidoux, Y. Lu, C. Zhou, L. Hadjiiski, R. Samala. Computer-aided assessment of breast density: Comparison of supervised deep learning and feature based statistical learning. Physics in Medicine and Biology, 63 (2018) 025005

23. S. Yu, Y. Lu, Derek Molloy. A Dynamic-Shape-Prior Guided Snake Model with Application in Visually Tracking Dense Cell Populations. IEEE Trans. Image Processing 28(3): 1513-1527 (2019).

24. X. Ma,J. Wei,C. Zhou, Mark A. Helvie,Heang-Ping Chan,Lubomir M. Hadjiiski,and Y. Lu.Automated Pectoral Muscle Identification on MLO-view Mammograms: Comparison of Deep Neural Network to Conventional Computer Vision.Medical Physics,2019 Feb 16. doi: 10.1002/mp.13451.

25. X. Ma,Lubomir M. Hadjiiski,J. Wei,Heang-Ping Chan,Kenny H. Cha,Richard H. Cohan,Elaine M. Caoili,Ravi Samala,C. Zhou,and Y. Lu. U-Net-based Deep-Learning Bladder Segmentation in CT Urography. Medical Physics, 46(4):1752-1765, 2019.

26. W. Jun, Heang-PingChan, Helvie Mark. RoubidouxMarilyn, NealColleen, Y. Lu, HadjiiskiLubomir, and C. Zhou. Synthesizing Mammogram from Digital Breast Tomosynthesis. Physics in Medicine and Biology, 64(4):045011,2019.

27. Z. Zeng, W. Xie, Y.  Zhang and Y. Lu. RIC-Unet: An Improved Neural Network Based on Unet for Nuclei Segmentation in Histology Images.IEEE ACCESS, 2019, accepted.
M.Tang,Y. Lu and L.Yang. Temporal-spatial Patterns in dynamic FunctionalBrain Network for Self-paced Hand Movement. IEEE transactionsonneural systems&rehabilitation engineering, 2019, accepted.

28. S. Zhou, Y. Lu, N.Li, Y. Wang. Extension of the Virtual Electric Field Model Using Bilateral-like Filter for ActiveContours. Signal, Image, Video Processing, 2019, accepted.

29. S. Zhou, Y. Lu, N.Li, Y. Wang. Extension of the Virtual Electric Field Model Using Bilateral-like Filter for ActiveContours. Signal, Image, Video Processing, 2019, accepted.
L. Zhang, M. Huang, Y. Li, J. Liang, T. Gao, B. Deng, J. Yao, L. Lin, F. Chen, X. Huang, J. Kou, C. Li, C. Xie, Y. Lu*, Y. Sun. Pretreatment MRI Radiomics Analysis Allows for Reliable Prediction of Local Recurrence in Non-metastatic T4 Nasopharyngeal Carcinoma, Ebiomedicine, 2019, accepted.

30. X. Jiang, Y. Guo, H. Chen, Y. Zhang and Y. Lu. An Adaptive Region Growing based on Neutrosophic Set in Ultrasound Domain for Image Segmentation. IEEE ACCESS, 2019, accepted.

31. J. Jiang, Y. Zhang, Y. Lu, Y. Guo, H. Chen. A Radiomic-feature based Nipple Detection Algorithm on Digital Mammography. medical physics, 2019, accepted, doi:. 10.1002/mp.13684.
32. G. Cai, Y. Guo, H. Zeng, W. Chen, Y. Zhou, Y. Lu. Computer-aided detection and diagnosis of microcalcification clusters on full field digital mammograms based on deep learning method using neutrosophic boosting , Multimedia Tools and Applications, 2019, accepted, doi: 10.1007/s11042-019-7726-x.
33. Y. Lu, and etc. Three-dimensional reconstruction of internal fascicles and microvascular structures of human peripheral nerves, International Journal for Numerical Methods in Biomedical Engineering, 2019, accepted, doi: 10.1002/cnm.3245.

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Processing paper

1. H. Ye, A. Krol, D.H. Feiglin, E.D. Lipson, Y. Lu, Y. Xu, and W. Lee. Implementation of a Fully 3DSystem Model for Brain SPECT with Fan-Beam-Collimator OSEM Reconstruction with 3D TotalVariationRegularization.Proc. SPIE 6510, Medical Imaging 2007: Physics of Medical Imaging:65104T:1-6.

2. Y. Lu, H. Ye, Y. Xu, X. Hu, L. Shen, D. Feiglin, E. Lipson, and A.Krol. Expectation Maximization SPECT Reconstruction with a Content Adaptive Singularity-Based Mesh-Domain Image Model.Proc. SPIE 6913, Medical Imaging 2008: Physics of Medical Imaging:69132F:1-6.

3. L. Vogelsang, Y. Lu, B. Yu, A. Krol, Y. Xu, X. Hu, D. Feiglin and E. Lipson. Attenuation Compensation in Mesh-Domain OSEM SPECT Reconstruction.Proc. SPIE 7258, Medical Imaging 2009: Physics of Medical Imaging:72583G:1-7.

4. A. Krol, L. Vogelsang, Y. Lu, Y. Xu, X. Hu, L. Shen, D. Feiglin and E. Lipson. Implementation OSEM Mesh-Domain SPECT Reconstruction with Explicit Prior Information.Proc. SPIE 7258, Medical Imaging 2009: Physics of Medical Imaging:72585C:1-7.

5. Y. Lu, B. Yu, L. Vogelsang, A. Krol, Y. Xu, X. Hu, and D. Feiglin. Tomographic Mesh Generation forOSEM Reconstruction of SPECT Images.Proc. SPIE 7258, Medical Imaging 2009: Physics of Medical Imaging:725854:1-7.

6. A. Krol, Y. Lu, L. Vogelsang, B. Yu, Y. Xu, and D. Feiglin. Hyperparameter Selection for OSEM SPECT Reconstruction in Mesh Domain with Total Variation Regularization. Proc. SPIE 7622, Medical Imaging 2010: Physics of Medical Imaging:762254:1-6.

7. Y. LuH.-P. Chan, M. Goodsitt, J. WeiL. Hadjiiski, A. Schmitz, J.W. Eberhard and B.E.H. Claus. Effects of Projection-View Distributions on Image Quality of Calcifications in Digital Breast Tomosynthesis (DBT) Reconstruction. Proc. SPIE 7622, Medical Imaging 2010: Physics of Medical Imaging:76220D:1-8.

8. Y. Lu, H.-P. Chan, J. F. Fessler, L. Hadjiiski, J. Wei, and M. Goodsitt. Adaptive Diffusion Regularization for Enhancement of Microcalcifications in Digital Breast Tomosynthesis (DBT) Reconstruction. Proc. SPIE 7961, Medical Imaging 2011: Physics of Medical Imaging:796117:1-9.

9. J. Wei,H.-P. Chan, B. Sahiner, M. Helvie, L. Hadjiiski, C. Zhou and Y. Lu. Computer-aided Detection of Breast Masses in Digital Breast Tomosynthesis (DBT): Improvement of False Positive Reduction by Optimization of Object Segmentation.Proc. SPIE 7963, Medical Imaging 2011: Computer-Aided Diagnosis: 796311:1-6.

10. Y. Lu, H.-P. Chan, J. Wei, L. Hadjiiski, and C. Zhou. Multiscale Regularized Reconstruction for Enhancing Microcalcification in Digital Breast Tomosynthesis. Proc. SPIE 8313, Medical Imaging 2012: Physics of Medical Imaging:831322:1-9.

11. Y. Lu, H.-P. Chan, J. Wei, L. Hadjiiski, and C. Zhou.Improving Image Quality of Digital Breast Tomosynthesis by Artifact Reduction. Proc. 11th International Workshop on Breast Imaging.  IWDM-2012.  Philadelphia, PA.  July 8-11, 2012. Lecture Notes in Computer Science, 7361, 745-752, 2012.

12. J. Wei, H.-P. Chan, Y. Lu, L. Hadjiiski, C. Zhou, M. Helvie. Breast Parenchymal Pattern (BPP) Analysis: Comparison of Digital Mammograms and Breast Tomosynthesis.  Proc. 11th International Workshop on Breast Imaging.  IWDM-2012.  Philadelphia, PA.  July 8-11, 2012. Lecture Notes in Computer Science, 7361:  514-520, 2012.

13. Y. Lu, H.-P. Chan, J. Wei, L. Hadjiiski and R. Samala. Study of Image Quality in Digital Breast Tomosynthesis by Subpixel Reconstruction.Proc. of SPIE 8668, Medical Imaging 2013: Physics of Medical Imaging: 86680I: 1-6.

14. R. Samala, H.-P. Chan, Y. Lu, L. Hadjiiski, J. Wei, B. Sahiner and M Helvie. Detection of Microcalcifications in Digital Breast Tomosynthesis Reconstructed with Multiscale Bilateral Filtering Regularization.Proc. of SPIE 8670, Medical Imaging 2013: Computer-Aided Diagnosis: 86701L: 1-8.

15. R. Samala, H.-P. Chan, Y. Lu, L. Hadjiiski, J. Wei, and M Helvie. Digital breast tomosynthesis: effects of projection-view distribution on computer-aided detection of microcalcification clusters, Proc. of SPIE 9035, Medical Imaging 2014: Computer-Aided Diagnosis:90350Y: 1-8.

16. R. Samala, H.-P. Chan, Y. Lu, L. Hadjiiski, J. Wei, and M Helvie.Digital breast tomosynthesis: application of 2D digital mammography CAD to detection of microcalcification clusters on planar projection image. Proc. of SPIE 9414, Medical Imaging 2015:Computer-Aided Diagnosis:941418:1-7.

17. R. Samala, H.-P. Chan, Y. Lu, L. Hadjiiski, J. Wei, and M Helvie.Comparison of computer-aided detection of clustered microcalcifications in digital mammography and digital breast tomosynthesis. Proc. of SPIE 9414, Medical Imaging 2015:Computer-Aided Diagnosis:94140K:1-7.

18. Y. Chen, Y. Lu, X. Ma, Y. Xu. Regularized CT reconstruction method on unstructured grid, Proc. of SPIE 9783, Medical Imaging 2016: Physics of Medical Imaging:97834G: 1-8.

19. H. Li, D. Yang, L. Yang, Y. Lu and X. Lin. Supervised Massive Data Analysis for Telecommunication Customer Churn Prediction, 2016 IEEE International Conferences on Big Data and Cloud Computing, 2016, 163-169.

20. L. Yang, C. Lin, and Y. Lu. Detection of Human Movement Intention based on Multilayer Feed-Forward Neural Network with Dictionary Learning, CISP-BMEI 2017, 1-6.

21. C. Xu, Y. Lu, Y. Zhou. An Automatic Visible Watermark Removal Technique Using Image Inpainting Algorithms, ICSAI2017, 1152-1157.

22. R. Zeng, S. Zhang, X. Zhang, C. Zheng,J. Zhang, K. Xue, J. Wei, Y. Lu, and J. Shen.Metastatic Breast Cancer: Characterization of Axillary SentinelLymph Node (SLN) on the Preoperative Spectral CT. IWBI2018, 1071815 (6 July 2018),Vol. 10718.

23. J. Jiang, Y. Lu, and Y. Guo. A Novel Nipple Detection Algorithm on Digital Mammography (DM). IWBI2018, 107181C (6 July 2018),Vol. 10718.

24. Z. Jiang, Y. Yin, L. Gao, Y. Lu, and X. Liu. Cross-language Citation Recommendation via HierarchicalRepresentation Learning on Heterogeneous Graph.SIGIR2018,635-644.
25. Z. Jiang, Y. Lu, and X. Liu. Cross-language Citation Recommendation via PublicationContent and Citation Representation Fusion.JCDL2018, June 3-7, 2018, Fort Worth, TX, USA.

26. G. Cai, Y. Guo, Y. Zhang, G. Qin, Y. Zhou, and Y. Lu. A fully automatic microcalcification detection approach based on deep convolution neural network. In Nicholas A. Petrick, Kensaku Mori, editors, Medical Imaging 2018: Computer-Aided Diagnosis, Houston, Texas, USA, 10-15 February 2018. Volume 10575 of SPIE Proceedings, SPIE, 2018. 

27. C. Li, Y. Lu, J. Wu, Y. Zhang, Z. Xia,T. Wang, D. Yu, X. Chen, P. Liu, and J. Guo. LDA Meets Word2Vec: A Novel Mode for Academic Abstract Clustering.In The 2018 Web Conference Companion (WWW 2018), April 23-27, 2018, Lyon, France, ACM,New York, NY, 8 pages.

28. L. Yang and Y. Lu. EEG Neural Correlates of Self-Paced Left- and Right-Hand Movement Intention during a Reaching Task. IEEE EMBS conference.18-21 July 2018, 2040-2043.

29. S. Yu, and Y. Lu. Exploring Potentials of Image-Registration based Cell Tracking. International Conference on Innovation in Artificial Intelligence (ICIAI 2018), shanghai, China, Mar 09-12, 2018.

30.. Yu, and Y. Lu. Joint segmenting and tracking densely packed cells using dynamic-GVF based snakes. IEEE 14th International Colloquium on Signal Processing & Its Applications (CSPA 2018), Penang, Malaysia, Mar 09-10, 2018.

31. S. Yu, and Y. Lu, Derek Molloy. Model&Motion based Shape Tracking in Large-Scale Cellular Datasets, International Conference on Machine Learning and Computing (ICMLC 2018), Macau, China, Feb 26-28, 2018, 102-106.

32. S. Liu,Y. Guo,L. Yan, and Y.  Lu.Three-dimensional reconstruction of internal fascicles of human peripheral nerve.Medical Imaging 2019: Image-Guided Procedures, Robotic Interventions, and Modeling. International Society for Optics and Photonics, 2019, 10951: 109512G.

33. G. Cai, Y. Guo, W. Chen, Hui Zeng, Y. Zhou and Y. Lu. Computer-aided detection and classification of microcalcification clusters on full field digital mammograms using deep convolution neural network. SPIE Medical Imaging 2019, 16-21 February, 2019, San Diego, United States, accepted.

34. X. Jiang, Y. Guo, and Y. Lu. A Novel Region Growing Approach using Similarity Set Score and Homogeneity based on Neutrosophic Set for Ultrasound Image Segmentation. ICGIP2018, accepted.

35. X. Zheng, Z. Liu, L. Chang, W. Long, and Y. Lu. Coordinate-Guided U-Net for Automated Breast Segmentation on MRI Images. ICGIP2018, accepted.

36. X. Ma, J. Wei, C. Zhou, H. Chan, Lubomir M. Hadjiyski,and Y.  Lu. Fully Automated Pectoral Muscle Identification on Mlo-View Mammograms with Deep Convolutional Neural Network. Vol. 10718. The Fourteenth International Workshop on Breast Imaging: SPIE, 2018.

37. X. Ma, Lubomir M. Hadjiiski, J. Wei, H. Chan, Kenny Cha, Richard H. Cohan, Elaine M. Caoili, Ravi Samala, Chuan Zhou, and Y. Lu. U-Net-Based Deep-Learning Bladder Segmentation in Ct Urography. Vol. RSNA Program Book, SSG13-07. Radiological Society of North America 2018 Scientific Assembly and Annual Meeting. Chicago, 2018.

38. X. Ma, Lubomir M. Hadjiiski, J. Wei, H. Chan, Kenny H. Cha, Richard H. Cohan, Elaine M. Caoili, Ravi K. Samala, C. Zhou, and Y. Lu. 2Dand 3D bladder segmentation using U-Net-based deep-learning.SPIE Medical Imaging 2019, 16-21 February, 2019, San Diego, United States, accepted.

39. X. Ma, Caleb E. Fisher, J. Wei, Mark A. Helvie, Heang-Ping Chan, C. Zhou, Lubomir M. Hadjiiski,and Y. Lu.Multi-path deep learning model for automated mammographic density categorization.SPIE Medical Imaging 2019, 16-21 February, 2019, San Diego, United States, accepted.

40. Y. Gu, Y. Lai, P. Xie, J. Wei, and Y. Lu, Muiti-scale Prediction Network for Lung Segmentation, IEEE International Symposium of Biomedical Imaging (ISBI), 2019, accepted.

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