Perelman School of Medicine at the University of Pennsylvania

Shen Lab

Conference Papers

  1. Brand L, Nichols K, Wang H, Huang H, Shen L, for the ADNI. (2020) Predicting longitudinal outcomes of Alzheimer's disease via a tensor-based joint classification and regression model. PSB’20: Pac Symp Biocomput., in press, Big Island of Hawaii, January 3-7, 2020.

  2. Du L, Fang L, Liu K, Yao X, Risacher S, Han J, Guo L, Saykin A, Shen L. (2019) A dirty multi-task learning method for multi-modal brain imaging genetics. MICCAI’19: Med Image Comput Comput Assist Interv, Lecture Notes in Computer Science, in press, Shenzhen, China, October 13-17, 2019. [31% acceptance rate]

  3. Lu L, Elbeleidy S, Backer L, Wang H, Huang H, Shen L. (2019) Improved prediction of cognitive outcomes via globally aligned imaging biomarker enrichments over progressions. MICCAI’19: Med Image Comput Comput Assist Interv, Lecture Notes in Computer Science, in press, Shenzhen, China, October 13-17, 2019. [25% early acceptance rate]

  4. Chung MK, Xie L, Huang S, Wang Y, Yan J, Shen L. (2019) Rapid acceleration of the permutation test via transpositions. CNI’19: MICCAI Workshop on Connectomics in Neuroimaging, Lecture Notes in Computer Science, in press, Shenzhen, China, October 13, 2019.

  5. Peng B, Ren Z, Yao X, Liu K, Saykin AJ, Shen L, Ning X, for the ADNI. (2019) Prioritizing amyloid imaging biomarkers in Alzheimer's disease via learning to rank. MBIA’19: MICCAI Workshop on Multimodal Brain Image Analysis, Lecture Notes in Computer Science, in press, Shenzhen, China, October 17, 2019.

  6. Mussabaeva A, Pisov M, Kurmukov A, Kroshnin A, Shen L, Cong S, Wang L, and Gutman B. (2019) Diffeomorphic metric learning and template optimization for registration-based predictive models. MFCA’19: MICCAI Workshop on Mathematical Foundations of Computational Anatomy, Lecture Notes in Computer Science, in press, Shenzhen, China, October 17, 2019.

  7. Yao X, Cong S, Yan J, Risacher SL, Saykin AJ, Moore JH, Shen L. (2019) Mining regional imaging genetic associations via voxel-wise enrichment analysis. BHI’19: IEEE International Conference on Biomedical and Health Informatics, Chicago, IL, May 19-22, 2019. [31% acceptance rate]

  8. Peng B, Yao X, Risacher SL, Saykin AJ, Shen L, Ning X. (2019) Prioritization of cognitive assessments in Alzheimer's disease via learning to rank using brain morphometric data. BHI’19: IEEE International Conference on Biomedical and Health Informatics, Chicago, IL, May 19-22, 2019. [11% acceptance rate for oral presentations]

  9. Du L, Liu K, Yao X, Risacher SL, Guo L, Saykin AJ, Shen L. (2019) Diagnosis status guided brain imaging genetics via integrated regression and sparse canonical correlation analysis. ISBI’19: IEEE Int. Sym. on Biomedical Imaging, Venice, Italy, April 8-11, 2019.

  10. Chung MK, Huang SG, Gritsenko A, Shen L, Lee H (2019) Statistical inference on the number of cycles in brain networks. ISBI’19: IEEE Int. Sym. on Biomedical Imaging, Venice, Italy, April 8-11, 2019.

  11. Du L, Liu K, Yao X, Risacher SL, Han J, Guo L, Saykin AJ, Shen L. (2018) Fast multi-task SCCA learning with feature selection for multi-modal brain imaging genetics. BIBM’18: IEEE Int. Conf. on Bioinformatics and Biomedicine. Madrid, Spain, December 3-6, 2018. [19.6% acceptance rate] (Best Paper Award)

  12. Liu K, Shen L, Jiang H. (2018) A unified model for robust differential expression analysis of RNA-seq data. BIBM’18: IEEE Int. Conf. on Bioinformatics and Biomedicine. Madrid, Spain, December 3-6, 2018. [19.6% acceptance rate]

  13. Li H, Fang S, Mukhopadhyay S, Saykin A, Shen L. (2018) Interactive machine learning by visualization: A small data solution. HMData’18: The 2nd IEEE Workshop on Human-in-the-loop Methods and Human Machine Collaboration in BigData. Seattle, WA, December 10, 2018.

  14. Brand L, Wang H, Huang H, Risacher S, Saykin A, Shen L, for the ADNI. (2018) Joint high-order multi-task feature learning to predict the progression of Alzheimer's disease. MICCAI’18: Med Image Comput Comput Assist Interv, Lecture Notes in Computer Science, 11070:555-562, Granada, Spain, September 16-20, 2018. [~33% acceptance rate]

  15. Xie L, Amico E, Salama P, Wu Y, Fang S, Sporns O, Saykin A, Goni J, Yan J, Shen L. (2018) Heritability estimation of reliable connectomic features. CNI’17: MICCAI Workshop on Connectomics in NeuroImaging, Lecture Notes in Computer Science, 11083:58-66, Granada, Spain, September 20, 2018.

  16. Musabaeva A, Kroshnin A, Kurmukov A, Dodonova Y, Shen L, Cong S, Wang L, Gutman BA. (2018) Image registration and predictive modeling: Learning the metric on the space of diffeomorphisms. ShapeMI’17: MICCAI Workshop on Shape in Medical Imaging, Lecture Notes in Computer Science, in press, Granada, Spain, September 20, 2018.

  17. Yan J, Raja V, Huang Z, Enrico A, Nho K, Fang S, Sporns O, Wu Y, Saykin AJ, Goni J, Shen L. (2018) Brain-wide structural connectivity alterations under the control of Alzheimer risk genes. ICIBM’18: Int. Conf. on Intelligent Biology and Medicine, Los Angeles, CA, USA, June 10-12, 2018.  

  18. Chiang W, Shen L, Li L, Ning X. (2018) Drug-drug interaction prediction based on co-medication patterns and graph matching. ICIBM’18: Int. Conf. on Intelligent Biology and Medicine, Los Angeles, CA, USA, June 10-12, 2018.  

  19. Liu K, Wang H, Risacher S, Saykin AJ, Shen L, for the ADNI. (2018) Multiple incomplete views clustering via non-negative matrix factorization with its application in Alzheimer’s disease analysis. ISBI’18:  IEEE Int. Sym. on Biomedical Imaging, pages 1402-1405, Washington DC, April 4-7, 2018.

  20. Lu L, Wang H, Yao X, Risacher S, Saykin AJ, Shen L, for the ADNI. (2018) Predicting progressions of cognitive outcomes via high-order multi-modal multi-task feature learning. ISBI’18:  IEEE Int. Sym. on Biomedical Imaging, pages 545-548, Washington DC, April 4-7, 2018.

  21. Yan J, Liu K, Li H, Amico E, Risacher SL, Wu Y, Fang S, Sporns O, Saykin AJ, Goni J, Shen L. (2018) Joint exploration and mining of memory-relevant brain anatomic and connectomic patterns via a three-way association model. ISBI’18:  IEEE Int. Sym. on Biomedical Imaging, pages 6-9, Washington DC, April 4-7, 2018.

  22. Li H, Fang S, Zigon B, Sporns O, Saykin AJ, Goñi J, Shen L. (2017) BECA: A Software Tool for Integrated Visualization of Human Brain Data. In: Zeng Y, He Y, Kotaleski JH, Martone M, Xu B, Peng H, et al., editors. Brain Informatics: International Conference, BI 2017, Beijing, China, November 16-18, 2017, Proceedings. Cham: Springer International Publishing; 2017. p. 285-91. 

  23. Liu K, Yao X, Yan J, Chasioti D, Risacher S, Nho K, Saykin A, Shen L, for the ADNI. (2017) Transcriptome-guided imaging genetic analysis via a novel sparse CCA algorithm. MICGen 2017: MICCAI Workshop on Imaging Genetics, Lecture Notes in Computer Science, 10551:220-229, Quebec City, Canada, September 10, 2017. 

  24. Huang Y, Du L, Liu K, Yao X, Risacher SL, Guo L, Saykin AJ, Shen L, for the ADNI. (2017) A fast SCCA algorithm for big data analysis in brain imaging genetics. MICGen 2017: MICCAI Workshop on Imaging Genetics, Lecture Notes in Computer Science, 10551:210-219, Quebec City, Canada, September 10, 2017.  

  25. Ning X, Shen L, Li L. (2017) Predicting high-order directional drug-drug interaction relations. ICHI’17: The 5th IEEE International Conference on Healthcare Informatics, 6 pages, Park City, Utah, August 23-26, 2017.

  26. Ning X, Schleyer T, Shen L, Li L. (2017) Pattern discovery from directional high-order drug-drug interaction relations. ICHI’17: The 5th IEEE International Conference on Healthcare Informatics, 9 pages, Park City, Utah, August 23-26, 2017. 

  27. Du L, Zhang T, Liu K, Yan J, Yao X, Risacher SL, Saykin AJ, Han J, Guo L, Shen L. (2017) Identifying associations between brain imaging phenotypes and genetic factors via a novel structured SCCA approach. IPMI’17: Information Processing in Medical Imaging, Lecture Notes in Computer Science, 10265:543-555, Boone, North Carolina, USA, June 25-30, 2017. [33% acceptance rate]

  28. Wang X, Liu K, Yan J, Risacher SL, Saykin AJ, Shen L, Huang H. (2017) Predicting interrelated Alzheimer's disease outcomes via new self-learned structured low-rank model. IPMI’17: Information Processing in Medical Imaging, Lecture Notes in Computer Science, 10265:198-209, Boone, North Carolina, June 25-30, 2017. [33% acceptance rate]

  29. Wang X, Yan J, Yao X, Kim S, Nho K, Risacher SL, Saykin AJ, Shen L, Huang H, for the ADNI. (2017) Longitudinal genotype-phenotype association study via temporal structure auto-learning predictive model. RECOMB'17: The 21st Annual International Conference on Research in Computational Molecular Biology, pp 287-302, Hong Kong, May 3-7, 2017. [21% acceptance rate]

  30. Yao X, Yan J, Risacher S, Moore J, Saykin A, Shen L. (2017) Network-based genome wide study of hippocampal imaging phenotype in Alzheimer’s disease to identify functional interaction modules. ICASSP'17: The 42nd IEEE International Conference on Acoustics, Speech and Signal Processing, 10.1109/ICASSP.2017.7953342, New Orleans, March 5-9, 2017.

  31. Shen L, Cooper L (2017) Imaging Genomics (Session Introduction). PSB’17: Pac Symp Biocomput., 22:51-57, Big Island of Hawaii, January 3-7, 2017.

  32. Yan J, Risacher SL, Nho K, Saykin AJ, Shen L. (2017) Identification of discriminative proteomics associations in Alzheimer’s disease via a novel sparse correlation model. PSB’17: Pac Symp Biocomput., 22:94-104, Big Island of Hawaii, January 3-7, 2017.

  33. Du L, Zhang T, Liu K, Yao X, Yan J, Risacher SL, Guo L, Saykin AJ, Shen L. (2017) Sparse Canonical Correlation Analysis via Truncated l1-norm with Application to Brain Imaging Genetics.  BIBM’16: IEEE Int. Conf. on Bioinformatics and Biomedicine. Shenzhen, China; 2016.

  34. Luo D, Huo Z, Wang Y, Saykin AJ, Shen L, Huang H. (2016) New probabilistic multi-graph decomposition model to identify consistent human brain network modules. ICDM’16: IEEE International Conference on Data Mining, Barcelona, December 13-15, 2016. In press.

  35. Wen Q, Stirling BD, Sha L, Shen L, Whalen PJ, Wu Y. (2016) Parcellation of human amygdala subfields using orientation distribution function and spectral k-means clustering. CDMRI'16: MICCAI 2016 Workshop on Computational Diffusion MRI, Mathematics and Visualization, Athens, Greece, October 21, 2016.

  36. Cong S, Rizkalla M, Salama P, Risacher SL, West JD, Wu Y, Apostolova L, Tallman E, Saykin AJ, Shen L, ADNI (2016) Building a surface atlas of hippocampal subfields from high resolution T2-weighted MRI scans using landmark-free surface registration. MWSCAS'16: The IEEE 59th International Midwest Symposium on Circuits and Systems, Abu Dhabi, United Arab Emirates, October 16-19, 2016.

  37. Inlow M, Cong S, Risacher SL, West JD, Rizkalla M, Salama P, Saykin AJ, Shen L, for the ADNI. (2016) A new statistical image analysis approach and its application to hippocampal morphometry. MIAR’16: Medical Imaging and Augmented Reality, Lecture Notes in Computer Science, 9805:302-310, Bern, Switzerland, August 24-26, 2016.

  38. Wang J, Fang S, Li H, Goñi J, Saykin AJ, Shen L. Multigraph visualization for feature classification of brain network data. (2016) In: Sedlmair NAaM, editor. EuroVA’16: EuroVis Workshop on Visual Analytics. Groningen, the Netherlands: The Eurographics Association; 2016. p. 61-65.

  39. Hao X, Yan J, Yao X, Risacher SL, Saykin AJ, Zhang D, Shen L. (2016) Diagnosis-guided method for identifying multi-modality neuroimaging biomarkers associated with genetic risk factors in Alzheimer's disease. Pac Symp Biocomput. 21:108-119, 2016.

  40. Yan J, Du L, Kim S, Risacher SL, Huang H, Inlow M, Moore JH, Saykin AJ, Shen L, for the ADNI. (2015) BoSCCA: Mining stable imaging and genetic associations with implicit structure learning. MICGen 2015: MICCAI Workshop on Imaging Genetics, October 9, 2015. 

  41. Liang H, Meng X, Chen F, Zhang Q, Yan J, Yao X, Kim S, Wang L, Feng W, Saykin AJ, Li J, Shen L, and for the ADNI. (2015) A network-based framework for mining high-level imaging genetic associations. MICGen 2015: MICCAI Workshop on Imaging Genetics, October 9, 2015. 

  42. Li H, Fang S, Goni J, Contreras JA, Liang Y, Cai C, West JD, Risacher SL, Wang Y, Sporns O, Saykin AJ, Shen L†§, for the ADNI. (2015) Integrated visualization of human brain connectome data. BIH 2015 Special Session on Neuroimaging Data Analysis and Applications, Lecture Notes in Artificial Intelligence, 9250:295-305, London, UK, 30 August - 2 September 2015.

  43. Du L, Yan J, Kim S, Risacher SL, Huang H, Inlow M, Moore JH, Saykin AJ, Shen L, for the ADNI. (2015) GN-SCCA: GraphNet sparse canonical correlation analysis for brain imaging genetics. BIH 2015 Special Session on Neuroimaging Data Analysis and Applications, Lecture Notes in Artificial Intelligence, 9250: 275-284, London, UK, 30 August - 2 September 2015.

  44. Yao X, Yan J, Kim S, Nho K, Risacher SL, Inlow M, Moore JH, Saykin AJ, Shen L, for the Alzheimer's Disease Neuroimaging Initiative. (2015) Two-dimensional enrichment analysis for mining high-level imaging genetic associations. BIH 2015: International Conference on Brain Informatics & Health, Lecture Notes in Artificial Intelligence, 9250:115-124, London, UK, 30 August - 2 September 2015. [50% acceptance rate]

  45. Gao H, Cai C, Yan J, Goni Cortes J, Wang Y, Nie F, West J, Saykin AJ, Shen L, Huang H (2015) Identifying connectome module patterns via new balanced multi-graph normalized cut. MICCAI’15: Med Image Comput Comput Assist Interv, Lecture Notes in Computer Science, in press, Munich, Germany, October 5-9, 2015. [~30% acceptance rate]

  46. Cong S, Rizkalla M, Salama P, West JD, Risacher SL, Saykin AJ, Shen L, ADNI (2015) Surface-based morphometric analysis of hippocampal subfields in mild cognitive impairment and Alzheimer's disease. MWSCAS'15: The IEEE 58th International Midwest Symposium on Circuits and Systems, pp 813-816, Fort Collins, Colorado, USA, August 2-5, 2015.

  47. Liang Y, Fang S, Brandstatter T, Cai C, Wang Y, West JD, Goni Cortes J, Saykin AJ, Shen L (2014) Brain connectome visualization for feature classification. IEEE VIS 2014, poster paper, Paris, France, November 9-14, 2014.

  48. Wang D, Wang Y, Nie F, Yan J, Saykin AJ, Shen L, Huang H (2014) Human connectome module pattern detection using a new multi-graph minmax cut model. MICCAI’14: Med Image Comput Comput Assist Interv, Lecture Notes in Computer Science, 8675:313-320, Boston, MA, September 14-18, 2014. [~30% acceptance rate]

  49. Du L*, Yan J*, Kim S, Risacher SL, Huang H, Inlow M, Moore JH, Saykin AJ, Shen L, for the ADNI (2014) A novel structure-aware sparse learning algorithm for brain imaging genetics. MICCAI’14: Med Image Comput Comput Assist Interv, Lecture Notes in Computer Science, 8675:329-336, Boston, MA, September 14-18, 2014. (*equal contribution) [~30% acceptance rate]

  50. Cong S, Rizkalla M, Du EY, West JD, Risacher SL, Saykin AJ, Shen L, ADNI (2014) Building a surface atlas of hippocampal subfields from MRI scans using FreeSurfer, FIRST and SPHARM. MWSCAS'14: The IEEE 57th International Midwest Symposium on Circuits and Systems, pp 813-816, College Station, Texas, USA, August 3-6, 2014.

  51. Yan J, Zhang H, Du L, Wernert E, Saykin AJ and Shen L (2014) Accelerating sparse canonical correlation analysis for large brain imaging genetics data. XSEDE'14: The Annual Extreme Science and Engineering Discovery Environment Conference, Atlanta, GA, July 13-18, 2014.

  52. Sheng J, Kim S, Yan J, Moore JH, Saykin AJ, Shen L, for the ADNI (2014) Data synthesis and method evaluation for brain imaging genetics. ISBI’14:  IEEE Int. Sym. on Biomedical Imaging, pp 1202-1205, Beijing, China, 28 April - 2 May, 2014.

  53. Yan J, Huang H, Kim S, Moore JH, Saykin AJ, Shen L, for the ADNI (2014) Joint identification of imaging and proteomics biomarkers of Alzheimer’s disease using network-guided sparse learning. ISBI’14:  IEEE Int. Sym. on Biomedical Imaging, pp 665-668, Beijing, China, 28 April - 2 May, 2014.

  54. Pan Q, Hu T, Shen L, Saykin AJ, Moore JH (2013) Topological analysis of statistical epistasis networks reveals pathways associated with Alzheimer’s disease. TBC'13: The 3rd Annual Translational Bioinformatics Conference, Seoul, Korea, Oct. 2th-4th, 2013.

  55. Yan J, Huang H, Risacher SL, Kim S, Inlow M, Moore JH, Saykin AJ, Shen L, for the ADNI (2013) Network-guided sparse learning for predicting cognitive outcomes from MRI measures. MBIA’13: MICCAI Workshop on Multimodal Brain Image Analysis, Lecture Notes in Computer Science, 8159:202-210, Nagoya, Japan, September 22, 2013.

  56. Kim D, Kim S, Risacher SL, Shen L, Ritchie MD, Weiner MW, Saykin AJ, Nho K, for the ADNI (2013) A graph-based integration of multimodal brain imaging data for the prediction of early mild cognitive impairment (E-MCI). MBIA’13: MICCAI Workshop on Multimodal Brain Image Analysis, Lecture Notes in Computer Science, 8159:159-169, Nagoya, Japan, September 22, 2013.

  57. Kim S, Nho K, Risacher SL, Inlow M, Swaminathan S, Yoder KK, Shen L, West JD, McDonald BC, Tallman EF, Hutchins GD, Fletcher JW, Farlow MR, Ghetti B, Saykin AJ (2013) PARP1 gene variation and microglial activity on [11C]PBR28 PET in older adults at risk for Alzheimer's disease. MBIA’13: MICCAI Workshop on Multimodal Brain Image Analysis, Lecture Notes in Computer Science, 8159:150-158, Nagoya, Japan, September 22, 2013.

  58. Hibar DP, Medland SE, Stein JL, Kim S, Shen L, Saykin AJ, de Zubicaray GI,  McMahon KL, Montgomery GW, Martin NG, Wright MJ, Djurovic S, Agartz I, Andreassen OA, Thompson PM (2013) Genetic clustering on the hippocampal surface for genome-wide association studies. MICCAI’13: Med Image Comput Comput Assist Interv, LNCS, in press, Nagoya, Japan, September 22-26, 2013. [33% acceptance rate]

  59. Huang H, Yan J, Nie F, Huang J, Cai W, Saykin AJ, Shen L (2013) A new sparse simplex model for brain anatomical and genetic network analysis. MICCAI’13: Med Image Comput Comput Assist Interv, Lecture Notes in Computer Science, 8150:625-632, Nagoya, Japan, September 22-26, 2013. [33% acceptance rate]

  60. Wang D, Nie F, Huang H, Yan J, Risacher SL, Saykin AJ, Shen L, for the ADNI (2013) Structural brain network constrained neuroimaging marker identification for predicting cognitive functions. IPMI'13: Information Processing in Medical Imaging, Lecture Notes in Computer Science, 7917:536-547, Asilomar, CA, 6/29-7/3, 2013. [32% acceptance rate]

  61. Wang H, Nie F, Huang H, Yan J, Kim S, Risacher SL, Saykin AJ, Shen L, ADNI (2012) High-order multi-task feature learning to identify longitudinal phenotypic markers for Alzheimer disease progression prediction. NIPS’12: Neural Information Processing Systems, Lake Tahoe, Nevada, December 3-6, 2012. [1.36% acceptance rate for full oral presentation, 20/1467]

  62. Yan J, Li T, Wang H, Huang H, Wan J, Nho K, Kim S, Risacher SL, Saykin AJ, Shen L, for the ADNI (2012) Identification of novel cortical surface biomarkers for predicting cognitive outcomes based on group-level L-21 norm. MICCAI Workshop on Novel Imaging Biomarkers for Alzheimer's Disease and Related Disorders, pp 199-208, Nice, France, October 5, 2012.

  63. Li T, Wan J, Zhang Z, Yan J, Kim S, Risacher SL, Fang S, Beg MF, Wang L, Saykin AJ, Shen L, for the ADNI (2012) Hippocampus as a predictor of cognitive performance: Comparative evaluation of analytical methods and morphometric measures. MICCAI Workshop on Novel Imaging Biomarkers for Alzheimer's Disease and Related Disorders, pp 125-136, Nice, France, October 5, 2012.

  64. Yan J, Risacher SL, Kim S, Simon JC, Li T, Wan J, Wang H, Huang H, Saykin AJ, Shen L, for the ADNI (2012) Multimodal neuroimaging predictors for cognitive performance using structured sparse learning. MBIA’12: MICCAI Workshop on Multimodal Brain Image Analysis, Lecture Notes in Computer Science, 7509:1-17, Nice, France, October 1, 2012. 

  65. Wan J, Zhang Z, Yan J, Li T, Rao B, Fang S, Kim S, Risacher S, Saykin A, Shen L, for the ADNI (2012) Sparse Bayesian multi-task learning for predicting cognitive outcomes from neuroimaging measures in Alzheimer’s disease. CVPR’12: IEEE Int. Conf. on Computer Vision and Pattern Recognition, 940-947, Providence, Rhode Island, June 18-20, 2012. [24% acceptance rate]

  66. Guo Y, Wang Y, Fang S, Chao H, Saykin AJ, Shen L (2012) Pattern visualization of human connectome data. EuroVis'12: Eurographics/IEEE Int Visualization Symp, pp 79-83, Vienna, Austria, June 5-8, 2012. [42% acceptance rate]

  67. Wang H, Nie F, Huang H, Risacher SL, Saykin AJ, Shen L (2011) Sparse multi-task regression and feature selection to identify brain imaging predictors for memory performance. ICCV’11: IEEE Int. Conf. on Computer Vision, pp 557-562, Barcelona, Nov 6-13, 2011. [24% acceptance rate]

  68. Nho K, Shen L, Kim S, Risacher SL, Swaminathan S, Saykin AJ (2011) The effect of reference datasets and software tools on genotype imputation. American Medical Informatics Association (AMIA) Annual Symp Proc, pp 1013-1018, Washington, DC, October 22-26, 2011. 

  69. Wang H, Nie F, Huang H, Risacher SL, Saykin AJ, Shen L, ADNI (2011) Identifying AD-sensitive and cognition-relevant imaging biomarkers via joint classification and regression. MICCAI’11: Med Image Comput Comput Assist Interv, LNCS 6893:115-123, Toronto, Canada, September 18-22, 2011. [4.15% acceptance rate for oral papers, 34/819]

  70. Wan J, Kim S, Inlow M, Nho K, Swaminathan S, Risacher SL, Fang S, Weiner M, Beg F, Wang L, Saykin AJ, Shen L, ADNI (2011) Hippocampal surface mapping of genetic risk factors in AD via sparse learning models. MICCAI’11: Med Image Comput Comput Assist Interv, LNCS 6892:376-383, Toronto, Canada, September 18-22, 2011. [30% acceptance rate]

  71. Shen L, Kim S, Qi Y, Inlow M, Swaminathan S, Nho K, Wan J, Risacher S, Shaw L, Trojanowski J, Weiner M, Saykin A, ADNI (2011) Identifying neuroimaging and proteomic biomarkers for MCI and AD via the elastic net. MBIA’11: MICCAI Workshop on Multimodal Brain Image Analysis, LNCS 7012:27-34, Toronto, Canada, September 18, 2011.

  72. Nho K, Shen L, Kim S, Risacher SL, West JD, Foroud T, Jack CR, Weiner MW, Saykin AJ, ADNI (2010) Automatic prediction of MCI conversion to probable AD using baseline structural MRI in the ADNI cohort. American Medical Informatics Association (AMIA) Annual Symp Proc, pp 542-6, Washington, DC, Nov. 13-17, 2010. 

  73. Shen L, Qi Y, Kim S, Nho K, Wan J, Risacher SL, Saykin AJ, ADNI (2010) Sparse Bayesian learning for identifying imaging biomarkers in AD prediction. MICCAI’10: Med Image Comput Comput Assist Interv, LNCS 6363, pp 611-618, Beijing, China, 2010. [32% acceptance rate]

  74. Wan J, Shen L, Fang S, McLaughlin J, Autti-Ramo I, Fagerlund A, Riley E, Hoyme HE, Moore ES, Foroud T, CIFASD (2010) A framework for 3D analysis of facial morphology in fetal alcohol syndrome. MIAR’10: Medical Imaging and Augmented Reality, LNCS 6326:118-127, Beijing, China,  September 19-20, 2010. [29% acceptance rate for oral papers] 

  75. Wan J, Shen L, Sheehan KE, Kim S, Roth RM, Ford J, Fang S, Saykin AJ, Wishart HA (2009) Shape analysis of thalamic atrophy in multiple sclerosis. MICCAI Workshop on Medical Image Analysis on Multiple Sclerosis, pp 93-104, Imperial College London, UK, September 20, 2009. 

  76. Kim S, Shen L, Saykin AJ, West JD (2009) Data synthesis and tool development for exploring imaging genomic patterns. CIBCB'09: IEEE Symp on Computational Intelligence in Bioinformatics and Computational Biology, pp 298-305, Nashville, TN, 3/30-4/2, 2009.

  77. Kim S, Shen L, Saykin AJ, West JD (2009) Visual exploration of genetic association with voxel-based imaging phenotypes in an MCI/AD study. EMBC'09: Conf Proc IEEE Eng Med Biol Soc., pp 3849-3852, Minneapolis, Minnesota, September 2-6, 2009.

  78. Li H, Yan M, Henschel R, Shen L (2009) Implementing 3D SPHARM surfaces registration on cell processor. SAAHPC'09: Symp on Application Accelerators in High Performance Computing, 3 pages, Urbana, Illinois, July 28-30, 2009.

  79. Shen L, Firpi HA, Saykin AJ, West JW (2008) Parametric surface modeling and registration for comparison of manual and automated segmentation of the hippocampus. MICCAI’08 Workshop on the Computational Anatomy and Physiology of the Hippocampus, 12 pages, NYC, Sep 6, 2008.

  80. Shen L, Saykin AJ, Chung MK, Huang H (2007) Morphometric analysis of hippocampal shape in mild cognitive impairment: an imaging genetics study. BIBE’07: IEEE 7th Int Symp on Bioinfo & BioEngi, pp 211-217, Boston, MA, October 14-17, 2007. [12% acceptance rate]

  81. Shen L, Huang H, Makedon FS, Saykin AJ (2007) Efficient registration of 3D SPHARM surfaces. CRV 2007: Fourth Canadian Conf on Computer and Robot Vision, pp 81-88, Montreal, QC, May 28-30, 2007. [24% acceptance rate for oral papers]

  82. Xu Y, Ford JC, Makedon FS, Popa D, Huang H, Shen L (2007) In-home localization for home care of Alzheimer's disease patients using wireless sensor networks. Int Workshop on Pervasive Technologies for the Support of Alzheimer's Disease and Related Disorders Sufferers, 6 pages, Thessaloniki, February 24, 2007.

  83. Huang H, Shen L. Surface harmonics for shape modeling (2007) ICIP’07: 14th IEEE Int Conf on Image Processing, 2:553-556, San Antonio, Texas, September 16-19, 2007.

  84. Shen L, Saykin AJ, Chung MK, Huang H, Ford JC, Makedon FS, McHugh TL, Rhodes CH (2006) Morphometric analysis of genetic variation in hippocampal shape in mild cognitive impairment: Role of an IL-6 promoter polymorphism. CSB’06: LSS Computational Systems Bioinformatics Conf, 6 pages, Stanford University, CA, August 14-18, 2006.

  85. Chung MK, Shen L, Dalton KM, Davidson RJ (2006) Multi-scale voxel-based morphometry via weighted spherical harmonic representation. MIAR’06: Medical Imaging and Augmented Reality, LNCS 4091: 36-43, Shanghai, China, August 17-18, 2006.

  86. Shen L and Chung MK (2006) Large-scale modeling of parametric surfaces using spherical harmonics. 3DPVT’06: Int Symp on 3D Data Processing, Visualization & Transmission, 8 pages, UNC-CH, June 14-16, 2006.

  87. Huang H, Zhang L, Samaras D, Shen L, Makedon FS, Pearlman JD (2006) Hemispherical harmonic surface description and applications to medical image analysis. 3DPVT’06: Int Symp on 3D Data Processing, Visualization & Transmission, 8 pages, UNC-CH, June 14-16, 2006.

  88. Huang H, Shen L, Makedon FS, Pearlman JD (2006) A Spatio-temporal modeling method for shape representation. 3DPVT’06: Int Symp on 3D Data Processing, Visualization & Transmission, 7 pages, UNC-CH, June 14-16, 2006.

  89. Moolani V, Balasubramanian R, Shen L, Tandon A (2006) Shape analysis and spatio-temporal tracking of mesoscale eddies in Miami isopycnic coordinate ocean model. 3DPVT’06: Int Symp on 3D Data Processing, Visualization & Transmission, 8 pages, UNC-CH, June 14-16, 2006.

  90. Shen L, Huang H, Ford JC, Lu C, Gao L, Zheng W, Makedon FS, Pearlman JD (2006) Spatio-temporal analysis tool for modeling pulmonary nodules in MR images.  SPIE Medical Imaging, 6141:740-749, San Diego, CA, February 2006. 

  91. Huang H, Shen L, Zhang R, Makedon FS, Hettleman B, Pearlman JD (2006) Fast surface alignment for cardiac spatiotemporal modeling. SPIE Medical Imaging, 6144:1002-1009, San Diego, CA, February 2006.

  92. Zheng W, Wang Z, Shen L, Makedon FS, Pearlman JD (2006) Measuring blood delivery to solitary pulmonary nodule by perfusion magnetic resonance imaging. SPIE Medical Imaging, 6143:614332, 9 pages, San Diego, CA, February 2006.

  93. Huang H, Shen L, Zhang R, Makedon FS, Hettleman B, Pearlman JD (2005) Surface alignment of 3D spherical harmonic models: Application to cardiac MRI analysis. MICCAI’05: Med Image Comput Comput Assist Interv, LNCS 3749:67-74, Springer, Heidelberg, 2005. 

  94. Huang H, Shen L, Zhang R, Makedon FS, Pearlman JD (2005) A prediction framework for cardiac resynchronization therapy via 4D cardiac motion analysis. MICCAI’05: Med Image Comput Comput Assist Interv, LNCS 3749:704-711, Springer, Heidelberg, 2005.

  95. Huang H, Shen L, Zhang R, Makedon FS, Hettleman B, Pearlman JD (2005) Clustering based cardiac resynchronization therapy prediction using open source toolkit PRTools. ISC/NA-MIC Open-Source Workshop at MICCAI’05: Med Image Comput Comput Assist Interv, Palm Springs, California, USA, Oct 26-29, 2005.

  96. Huang H, Shen L, Makedon FS, Sheng Zhang, Greenberg M, Gao L, Pearlman JD (2005) A clustering-based approach for prediction of cardiac resynchronization therapy. 20th ACM Symp on Applied Computing, pp 260-266, Santa Fe, NM, March 13-17, 2005.

  97. Shen L, Gao L, Zhuang Z, DeMuinck E, Huang H, Makedon FS, Pearlman JD (2005) An interactive 3D visualization and manipulation tool for effective assessment of angiogenesis and arteriogenesis using computed tomographic angiography. SPIE Medical Imaging, 5744: 848-858, San Diego, CA, February 12-17, 2005.

  98. Huang H, Shen L, Ford JC, Makedon FS, Zhang R, Gao L, Pearlman JD (2005) Functional analysis of cardiac MR images using SPHARM modeling. SPIE Medical Imaging, 5747:1384-1391, San Diego, CA, February 12-17, 2005.

  99. Shen L, Zheng W, Gao L, Huang H, Makedon FS, Pearlman JD (2005) Modeling time-intensity profiles for pulmonary nodules in MR images.  EMBC’05: Conf Proc IEEE Eng Med Biol Soc, pp 1359-1362, Shanghai, China, September 1-4, 2005.

  100. Huang H, Zhang R, Fei Xiong, Makedon FS, Shen L, Hettleman B, Pearlman JD (2005) K-means+ method for improving gene selection for classification of microarray Data. CSB’05: IEEE Computational Systems Bioinformatics Conf, pp 110-111, Stanford, California, Aug 8-11, 2005.

  101. Shen L, Saykin AJ, McHugh TL, West JD, Rabin LA, Wishart HA, Chung MK, Makedon FS (2005) Morphometric analysis of 3D surfaces: Application to hippocampal shape in mild cognitive impairment. CVPRIP’05: 6th Int. Conf. on Computer Vision, Pattern Recognition and Image Processing, pp 699-702, Salt Lake City, Utah, July 21-26, 2005.

  102. Wang Y, Makedon FS, Ford JC, Shen L, Goldin D (2004) Generating fuzzy semantic metadata describing spatial relations from images using the R-histogram. The 4th ACM/IEEE-CS Joint Conf. on Digital Libraries, pp 202-211, Tucson, Arizona, June 7-11, 2004.

  103. Steinberg T, Ford JC, Ouyang Y, Shen L, Wang Y, Zheng W, Makedon FS (2004) Tracking resource usage using heterogeneous feature spaces with local exceptions. EDBT'04 Workshop: Clustering Information over the Web, Heraklion-Crete, Greece, March 14th, 2004.

  104. Shen L and Makedon FS (2004) Spherical parameterization for 3D surface analysis in volumetric images. ITCC'04: IEEE Int Conf Info Tech, pp 643-649, Las Vegas, NV, April 5-7, 2004.

  105. Makedon FS, Ye S, Sheng Zhang, Ford JC, Shen L, Kapidakis S (2004) Data brokers: Building collections through automated negotiation. SETN'04: The 3rd Hellenic Conf on Artificial Intelligence, LNCS 3025, pp 13-22, Samos, Greece, May 5-8, 2004.

  106. Shen L, Makedon FS, Saykin AJ (2004) Shape-based discriminative analysis of combined bilateral hippocampi using multiple object alignment. SPIE Medical Imaging, 5370: 274-282, San Diego, CA, February 14-19, 2004.

  107. Huang H, Makedon FS, Pearlman JD, Ford JC, Shen L, Wang Y, Gao L (2004) Efficient similarity retrieval framework for temporal shape sequences: A case study in cardiac MR images. EMBC’ 04: Conf Proc IEEE Eng Med Biol Soc, pp 3250-3253, San Francisco, California, September 1, 2004.

  108. Shen L, Ford JC, Makedon FS, Wang Y, Steinberg T, Ye S, Saykin AJ (2003) Morphometric analysis of brain structures for improved discrimination. MICCAI’03: Med Image Comput Comput Assist Interv, LNCS 2879:513-520, Springer, Heidelberg, 2003.

  109. Makedon FS, Tzika AA, Astrakas L, Pearlman JD, Wang Y, Steinberg T, Shen L, Chambers K, Ford JC (2003) Fusing information for tracking tumors. 8th World Cong on Advances in Oncology and 6th Int Symp on Molecular Medicine, Hersonissos, Greece, Oct 16-18, 2003.

  110. Shen L, Ford JC, Makedon FS, Saykin AJ (2003) Hippocampal shape analysis: Surface-based representation and classification. SPIE Medical Imaging, 5032:253-264, San Diego, Feb 2003.

  111. Shen L, Ford JC, Makedon FS, Saykin AJ (2003) Effective classification of 3D closed surfaces: Application to modeling neuroanatomical structures. CVPRIP’03: Int Conf on Computer Vision, Pattern Recognition and Image Processing, pp 708-711, Cary, NC, September 26-30, 2003. 

  112. Steinberg T, Wang Y, Makedon FS, Shen L, Saykin AJ, Wishart HA (2003) A spatio-temporal multi-modal data management and analysis environment for tracking MS lesions. SSDBM'03: Int Conf on Scientific & Statistical Database Management, pp 245-246, Cambridge, MA, July 9-11, 2003.

  113. Ye S, Makedon FS, Steinberg T, Shen L, Wang Y, Zhao Y, Ford JC (2003) SCENS: a system for the mediated sharing of sensitive data. JCDL'03: The 3rd ACM/IEEE-CS Joint Conf on Digital Libraries, pp 263-265, Houston, TX, May 27-31, 2003.

  114. Makedon FS, Wang Y, Steinberg T, Wishart HA, Saykin AJ, Ford JC, Ye S, Shen L (2003) A system framework for the integration and analysis of multi-modal spatio-temporal data streams: A case study in MS lesion analysis. The 1st Int IEEE EMBS Neural Engineering Conf, pp 495-498, Capri Island, Italy, March 20-22, 2003.

  115. Makedon FS, Ford JC, Shen L, Steinberg T, Saykin AJ, Wishart HA, Kapidakis S (2002) MetaDL: A digital library of metadata for sensitive or complex research data. ECDL'02: European Conf on Digital Libraries, LNCS 2458, pp 374-389, Rome, Italy, September 16-18, 2002.

  116. Ford JC, Makedon FS, Shen L, Steinberg T, Saykin AJ, Wishart HA (2002) Evaluation metrics for user-centered ranking of content in metaDLs. The 4th DELOS Workshop on Evaluation of Digital Libraries: Testbeds, Measurements, Metrics, Budapest, Hungary, May 6-7, 2002.

  117. Ford JC, Shen L, Makedon FS, Flashman LA, Saykin AJ. (2002) A combined structural-functional classification of schizophrenia using hippocampal volume plus fMRI activation. EMBS-BMES'02: The 2nd Joint Meeting of the IEEE Engineering in Medicine and Biology Society and the Biomedical Engineering Society, 1:48-49, Houston, Texas, October 23-26, 2002.

  118. Shen L, Cheng L, Teng F, Makedon FS, Ford JC, Steinberg T, Saykin AJ (2001) A multimedia system for tracing and studying regions-of-interest in brain images. MTAC'01: IEEE Multimedia Technology and Application Conf, pp 238-245, Irvine, CA, November 7-9, 2001.

  119. Cheng L, Shen L, Makedon FS, Donnelly AM, Flashman LA, Saykin AJ (2001) On the development of a training and research system for tracing human brain structures. SCI'01: The 5th World Multi-Conf on Systemics, Cybernetics and Informatics, VIII:151-155, Orlando, FL, July 22-25, 2001.

  120. Shen L, Cheng L, Ford JC, Makedon FS, Megalooikonomou V, Steinberg T (2000) Mining the most interesting web access associations. WebNet'00: World Conf on the WWW and Internet, pp 489-494, San Antonio, TX, Oct. 30 - Nov. 4, 2000.

  121. Steinberg T, Shen L, Cheng L, Makedon FS. Tracking human expression actions in lectures (2000) ED-MEDIA'00: World Conf on Educational Multimedia, Hypermedia & Telecommunication, pp 1090-1095, Montreal, Quebec, Canada, June 26 - July 1, 2000.

  122. Steinberg T, Cheng L, Shen L, Makedon FS, Owen C, Ottmann T (1999) A model for authoring for retrieval (AFR): Retrieval on parallel data streams of recorded lecture information. Multimedia Storage and Archiving Systems IV, SPIE Photonics EAST, pp 423-430, Boston, MA, September 19-22, 1999.

  123. Shen L, Shen H, Cheng L. (1999) New algorithms for efficient mining of association rules. IEEE Frontiers'99: The 7th Symp on the Frontiers of Massively Parallel Computation, pp 234-241, Annapolis, Maryland, February 21-25, 1999.

  124. Shen L, Shen H, Pritchard P, Topor R (1998) Finding the N largest itemsets. ICDM'98: Int Conf on Data Mining, pp 211-222, Rio de Janeiro, RJ, Brazil, September 2-4, 1998.

  125. Shen L, Shen H (1998) Mining flexible multiple-level association rules in all concept hierarchies. DEXA'98: The 9th Int Conf on Database and Expert Systems Applications, Lecture Notes in Computer Science (LNCS) 1460:786-795, Vienna, Austria, August 24-28, 1998.