Vision Problems from two face images?
Color from Gray?
Novel View Rendering?
Job Link @ Nvidia: Seeking world-class researchers on deep learning, medical imaging for high-performance clinical informatics!
I have joined NVIDIA AI-Infra division after nearly five productive years at National Institutes of Health, Clinical Center, Radiology and Imaging Science Department, pursuing how to push modern medical image understanding and semantic parsing to fit into revolutionary clinical workflow practices. There are four key ingredients: software and hardware code development platforms; close R&D collaboration with physicians-in-the-loop; evaluation & validation via large scale clinical imaging datasets; and mapping the recent progresses in statistical learning, machine learning, computer vision and video computing (from 2D/3D to 3D and 4D) towards medical imaging. Recently, I won the Best Summer Intern Mentor Award 2013, NIH Clinical Center (only one from my institute); and the Postbac Mentor of the Year Award 2015, NIH (one of three awardees in NIH).
was a Senior Staff Scientist, Image Analytics and Informatics, at Siemens
Corporate Research, from Nov. 2011 until Jan. 2013. I was a Staff Scientist at
Siemens Computer Aided Diagnosis (CAD) Group, Siemens Medical Solutions at
received my Ph.D. degree of Computer Science from
IEEE Senior Member, since 2014
Ph.D. in Computer Science,
MSE in Computer Science,
Internships at Microsoft Research Beijing & Redmond, 2000-2001, 2004 (Mentors: Harry Shum, Kentaro Toyama, Zhengyou Zhang, Long Quan)
Visiting Student in Electronic Engineering Department, Chinese University of Hong Kong (Advisors: Hung-Tat Tsui, Zhanyi Hu)
Student in Pattern Recognition and
Intelligent Systems, NLPR,
B.E. in ME & Automation Control,
CVPR 2016 Workshop on How Big
Data is Possible for Medical Image Analysis, invited talks only, Las Vegas, NV, July 1st, 2016
CVPR 2015 Workshop on How Big Data is Possible for Medical Image Analysis, invited talks only, Boston, MA, June 11th, 2015
Program / Paper Review Committee: IEEE CVPR, 2016, 2015, 2014, 2013, 2012, 2011, 2010, 2009; IEEE ICCV 2015, 2013, 2011, 2009; ECCV 2016, 2012, 2010; ACCV 2016, 2014, 2012, 2010, 2009
Journal Paper Reviewer: IEEE Trans. PAMI, IEEE Trans. Image Processing, IEEE Trans. Medical Imaging, Medical Image Analysis, PLOS One, Pattern Recognition, Pattern Recognition Letter; Academic Radiology, Medical Physics, Computerized Medical Imaging and Graphics, IEEE Journal of Biomedical and Health Informatics
Wokshop Organizer/Co-organizer: IEEE CVPR Medical Computer Vision Workshop, 2015, 2012; NIPS workshop on Machine Learning for Clinical Data Analysis and Healthcare, 2013
Recent & not-so-recent Talks:
Talk at GTC, GTCx and GTC-DC http://registration.gputechconf.com/quicklink/7L1Rg10, April 6th, 2016, Silicon Valley, CA, USA (pdf)
Talk on "A
Statistical Aspect of Imaging Analytics Based Computer-Aided Diagnosis"
(Summary of my Siemens work in 2006~2013, still with some insights: pdf)
Talk at MICCAI 2014 Tutorial: Thoracoabdominal Lymph-node Detection: Exploration of Shallow and Deep Models, Sept. 2014, Cambridge, MA, USA (ppt)
Talk at MICCAI
2010 on Vertebra Segmentation and Identification, Sept. 2010,
Computational and Visualization Challenges in the New Era of Virtual
Colonoscopy Meeting, MICCAI, Sept. 06, 2008,
RSNA Talk on ICV
ICML Talk on Clustering (International Conference of Machine Learning, June 2006, Pittsburgh), (ppt)
on Nonparametric Robust Visual Tracking (IEEE Conference
on Computer Vision and Pattern Recognition, June 2007,
I Gave a Tech Talk at Google in May 2006! The video was an overview of my graduate research on image patch representations/modeling for visual recognition and tracking. During the past year, some parts have been updated.
Deep Learning for Everything, :-)) (40+++)
Learning based 3D Volumetric, Surface, Curve Parsing for Medical Diagnosis (20+++)
New Classification Paradigms for Computer-aided Diagnosis (MICCAI 2011, CVPR 2011, Ongoing)
Discriminative/Generative Feature Learning for Computer-aided Diagnosis (Ongoing)
Structure Parsing for Medical Imaging and Analysis (ICCV 2009, MICCAI 2009, MICCAI 2010, Ongoing)
Supervised Learning Approach for Medical Imaging and Analysis (CVPR 2008, ECCV 2008, CVPR 2010, CVPR 2011, Ongoing)
Supervised Discriminative Dimension Reduction (Ongoing)
Online Appearance Modeling for Tracking and Recognition
(NIPS 2006, CVPR 2007)
New Clustering Method for Visual Data (ICML 2006)
Scene Analysis and Category Recognition (CVPR 2005)
Articulated Object Motion Modeling and Recognition (NIPS 2004)
Efficient Particle Filtering using RANSAC (FPIV 2004, IVC 2006)
Real-time Video Mosacing with Medical and Non-medical Applications (CVPR 2003 Demo)
Graphical Models and Tree-Structured Object Tracking (Life time interest, but never get a chance to do it, :-)) )
Publications (peer-refereed major conferences and journals):
110, Ling Zhang*, Le Lu, Ronald Summers, Electron Kebebew, Jianhua Yao, "Convolutional Invasion and Expansion Networks for Tumor Growth Prediction", IEEE Tran. on Medical Imaging (accepted), pp.1-11, 2017
109, Jiamin Liu, David Wang, Le Lu, Zhuoshi Wei, L. Kim, E. Turkbey, B. Sahiner, N. Petrick, Ronald Summers, "DETECTION AND DIAGNOSIS OF COLITIS ON COMPUTED TOMOGRAPHY USING DEEP CONVOLUTIONAL NEURAL NETWORKS", Journal of Medical Physics, (accepted), 2017
108, R. Cheng, H. Roth, N. Lay, Le Lu, B. Turkbey, W. Gander, E. McCreedy, P. Choyke, R. Summers, M. McAuliffe, "Automatic MR prostate segmentation by deep learning with holistically-nested networks", Journal of Medical Imaging, (accepted), 2017
107, Ling Zhang*, Le Lu, Isabella Nogues*, Ronald Summers, Shaoxiong Liu, Jianhua Yao, "DeepPap: Deep Convolutional Networks for Cervical Cell Classification", IEEE J. of Biomedical and Health Informatics (in press), 2017
106, Yifan Peng, Xiaosong Wang, Le Lu, Mohammadhadi Bagheri, Ronald Summers, Zhiyong Lu, "DeepText Mining Radiology Reports for Deep Learning Radiology Images", American Medical Informatics Association (AMIA) Annual Symposium (Oral), Nov. 2017
105, Adam Harrison*, Ziyue Xu, Kevin George*, Le Lu, Ronald Summers, Daniel Mollura, "Progressive and Multi-Path Holistically Nested Neural Networks for Pathological Lung Segmentation from CT Images", MICCAI Travel Award & Young Scientist Award Runner-up, (pdf), 2017
104, Ling Zhang*, Le Lu, Ronald Summers, Electron Kebebew, Jianhua Yao, "Personalized Pancreatic Tumor Growth Prediction via Group Learning", MICCAI (pdf), 2017
103, Jinzheng Cai*, Le Lu, Yuanpu Xie, Fuyong Xing, Lin Yang, "Improving Deep Pancreas Segmentation in CT and MRI Images via Recurrent Neural Contextual Learning and Direct Loss Function", MICCAI (pdf), 2017
102, Xiaosong Wang*, Yifan Peng*, Le Lu, Zhiyong Lu, M. Bagheri, Ronald Summers, "ChestX-ray8:
Hospital-scale Chest X-ray Database and Benchmarks on Weakly-Supervised
Classification and Localization of Common Thorax Diseases", IEEE CVPR (Spotlight, V2, pdf), 2017 (pp.1-19)
90, H. Shin*, H. Roth*, M. Chen*, Le Lu, Z. Xu, I. Nogues, J. Yao, D. Mollura, R. Summers, "Deep
Convolutional Neural Networks for Computer-Aided Detection: CNN
Architectures, Dataset Characteristics and Transfer Learning", IEEE Trans. on Medical Imaging, May 2016 (pdf).
70, Qian Wang*, Le
Lu, Dijia Wu, Noha El-zehiry, Yefeng Zheng, Kevin S. Zhou, Dinggang Shen,
"Sequential Automatic Segmentation of Spinal Canal in CT Images via
Iterative Topology Refinement", IEEE Trans. on Medical Imaging,
Aug. 2015 (pdf).
57, Ari Seff*, Le Lu,
Kevin Cherry, Holger Roth, Jiamin Liu, Shijun Wang, Evrim Turkbey, Ronald
Summers, "2D View Aggregation for Lymph Node Detection using a Shallow
Hierarchy of Linear Classifiers", early accepted, MICCAI 2014, Boston,
56, Holger Roth*, Le Lu, Ari Seff, Kevin Cherry, Shijun Wang, Jiamin Liu, Evrim Turkbey, Ronald Summers, "A New 2.5D Representation for Lymph Node Detection using Random Sets of Deep Convolutional Neural Network Observations", accepted, MICCAI 2014, Boston, MA (arXiv)
55, Holger Roth*, Jianhua Yao, Le Lu, Joseph Burns, Ronald Summers, "Detection of Sclerotic Spine Metastases via Random Aggregation of Deep Convolutional Neural Network Classifications", accepted (Oral), MICCAI Spine Imaging Workshop 2014 , Boston, MA (arXiv)
54, Amal Farag*, Le Lu, Jiamin
Liu, Evrim Turkbey, Ronald Summers, "A Bottom-up Approach for Automatic
Pancreas Segmentation Abdominal CT Scans", accepted (Oral), MICCAI
Abdominal Imaging Workshop 2014 , Boston, MA (arXiv)
53, Jiamin Liu, Jocelyn Zhao, Joanne Hoffman, Jianhua Yao, Le Lu, Evrim Turkbey, Christine Kim, Ronald M. Summers, "Detection and Station Mapping of Mediastinal Lymph Nodes on Thoracic Computed Tomography Using Spatial Prior from Multi-Atlas Label Fusion", ISBI, 2014 (oral)
52, David Allen*, Le Lu, Jianhua
Yao, Jiamin Liu, Evrim Turkbey, Ronald M. Summers,"Robust Automated
Lymph Node Segmentation with Random Forests", SPIE Medical Imaging,
90343X-90343X-8, 2014 (link)
51, Le Lu, Jianhua Yao, Evrim Turkbey, Ronald M. Summers, "Multilevel Image Recognition using Discriminative Patches and Kernel Covariance Descriptor", SPIE Medical Imaging, 903528-903528-8, 2014 (link)
R6, Ari Seff*, Evrim Turkbey, Le Lu, Holger Roth, Jiamin Liu, Ronald Summers, "Automated Lymphadenopathy Detection by Sparse Linear Fusion of 2D Views", Oral accepted, RSNA 2014, Chicago, IL
R5, Lauren Kim,
Holger Roth*, Le Lu, Shijun Wang, Evrim Turkbey, Ronald Summers,
"Performance Assessment of Retroperitoneal Lymph Node Computer-Assisted
Detection Using Random Forest and Deep Convolutional Neural Network Learning
Algorithms in Tandem", Oral, RSNA 2014
R4, Amal Farag*, Evrim Turkbey, Le Lu, Jiamin Liu, Ronald Summers, "Automated Pancreas Segmentation using a Multi-level Information Propagation Approach in Abdominal Computed Tomography", Oral accepted, RSNA 2014, Chicago, IL
50, Jianhua Yao, Hector Munoz, Joseph E.
Burns, Le Lu, Karen Kurdziel, Ronald D. Summers,
Detection of Spinal Degenerative Osteophytes on Sodium Fluoride PET/CT", Computational Methods and
Clinical Applications for Spine Imaging
Workshop, MICCAI 2013
49, Qian Wang*, Le Lu, Dijia Wu, Noha El-Zehiry, Dinggang Shen, S. Kevin Zhou, "Automatic and Reliable Segmentation of Spinal Canals in Low-Resolution, Low-Contrast CT Images", Computational Methods and Clinical Applications for Spine Imaging Wokshop, MICCAI 2013
48, Quan Wang*, Dijia Wu, Le Lu, Meizhu Liu, S. Kevin Zhou, "Semantic Context Feature Boosting for Learning-Based Knee Cartilage Segmentation in 3D MR Images", MCV'2013: Medical Computer Vision Workshop, MICCAI 2013
47, Le Lu, Pandu Devarakota, Siddharth Vikal, Dijia Wu, Yefeng Zheng, Matthias Wolf, "Computer Aided Diagnosis using Multilevel Image Features on Large-Scale Evaluation", MCV'2013: Medical Computer Vision Workshop, MICCAI 2013
46, Le Lu, Bing Jian, Dijia Wu, Matthias Wolf, "A New Algorithm of Electronic Cleansing for Weak Faecal-Tagging CT Colonography", MLMI'2013: Machine Learning in Medical Imaging Workshop, MICCAI 2013
45, Shijun Wang, Brandon Peplinski, Le Lu, Weidong Zhang, Jianfei Liu, Zhuoshi Wei, Ronald D. Summers, "Sequential Monte Carlo Tracking for Marginal Artery Segmentation on CT Angiography by Multiple Cue Fusion", MICCAI'2013
44, Evrim Turkbey, Le Lu, JianHua Yao, Zhuoshi Wei, Ronald D. Summers, "Computer-aided Detection of Colitis in Computed Tomography Examinations", Oral presentation, RSNA 2013
43, Jianhua Yao, H. Munoz, J.E. Burns, K.A. Kurdziel, P.L. Choyke, Le Lu, et al., "Detection Vertebral Degenerative Diesease on 18F-NaF PET/CT Using a Novel Cortical Shell Map", Oral presentation, RSNA 2013
42, Chi Li*, Le Lu, Gregory D. Hager, Jianyu Tang, Hanzi
Wang, Robust Object Tracking in Crowd Dynamic Scenes Using
Explicit Stereo Depth, ACCV'2012: The 11th Asian Conference on Computer Vision, Volume 3,
pages 71-85, Daejeon, Korea
41, Jun Ma*, Le Lu, Hierarchical Segmentation and Identification of Thoracic Vertebra Using Learning-based Edge Detection and Coarse-to-fine Deformable Model, Computer Vision and Image Understanding, SI of Shape Modeling, 117(9):1072-83, Sept., 2013
40, Automatic Spinal Canal Segmentation Using Cascaded Random Walks, Qian Wang*, Le Lu, Dijia Wu, S. Kevin Zhou, US Patent 9,317,926. US9317926
39, Automatic Spatial Context Based Multi-Object Segmentation in 3D Images, Quan Wang*, Dijia Wu, Meizhu Liu, Le Lu, S. Kevin Zhou, US Patent 9,218,524 CN104956397A, EP2929509A2, US9218524,WO2014089455A2, WO2014089455A3.
38, 一种在动态场景下以深度为主导线索的多目标跟踪方法，Hanzi Wang, Chi Li*, Jianyu Tang*, Le Lu, Gregory D. Hager, ZL 2012 1 0073384.0
37, Meizhu Liu*, Le Lu, Xiaojing Ye, Shipeng Yu, Heng Huang, Coarse-to-fine Classification using Parametric and Nonparametric Models for Computer-Aided Diagnosis, CIKM'2011: 20th ACM Conference on Information and Knowledge Management, October 2011, Glasgow, UK (the short version)
The Formula of something "WoW" that works magically (then supposedly): "simple intuitive, or counter-intuitive design accept" + "fine engineered implementation" = "think globally, act locally" = "Good vision/idea, fine engineering"
36, Meizhu Liu*, Le Lu, Xiaojing Ye, Shipeng Yu, Marcos Salganicoff, Sparse Classification for Computer Aided Diagnosis Using Learned Dictionaries, MICCAI'2011: 14th International Conference on Medical Image Computing and Computer Assisted Intervention, September 2011, Toronto, Canada
35, Meizhu Liu*, Le Lu, Jinbo Bi, Vikas Raykar, Matthias Wolf, Marcos Salganicoff, Robust Large Scale Prone-Supine Polyp Matching Using Local Features: A Metric Learning Approach, MICCAI'2011: 14th International Conference on Medical Image Computing and Computer Assisted Intervention, September 2011, Toronto, Canada
34, Le Lu, Jinbo Bi, Matthias Wolf, Marcos
Salganicoff, Effective 3D Object Detection and
Regression Using Probabilistic Segmentation Features in CT Images, CVPR'2011: IEEE Conference
on Computer Vision and Pattern Recognition, June 2011,
33, Jinbo Bi, Dijia Wu*, Le Lu,
Meizhu Liu*, Yimo Tao*, Matthias Wolf, AdaBoost on
Low-Rank PSD Matrices for Metric Learning with Applications in Computer Aided
Diagnosis, CVPR'2011: IEEE Conference on Computer Vision and
Pattern Recognition, June 2011,
32, Matching of Regions of Interests Across Multiple Views, Meizhu Liu*, Le Lu, Vikas Raykar, Matthias Wolf, Marcos Salganicoff, US Patent 8,885,898 B2#, granted in Nov. 2014
31, Le Lu, Matthias Wolf, Jinbo Bi, and Marcos
Salganicoff, "Correcting Misalignment
of Automatic 3D Detection by Classification: Ileo-cecal Valve False Positive
Reduction in CT Colonography", MICCAI-MCV'2010: Medical Computer Vision: Recognition
Techniques and Applications in Medical Imaging, joint with 13th
International Conference on Medical Image Computing and Computer Assisted
Intervention, Springer Verlag, Sept. 2010,
30, Jun Ma*, Le Lu, Yiqiang Zhan, Xiang Sean Zhou, Marcos Salganicoff and Arun Krishnan, "Hierarchical Segmentation and Identification of Thoracic Vertebra Using Learning-based Edge Detection and Coarse-to-fine Deformable Model", MICCAI'2010: 13th International Conference on Medical Image Computing and Computer Assisted Intervention, Sept. 2010, Beijing, China (Oral).
29, Dijia Wu*, Le Lu, Jinbo Bi, Yoshihisa Shinagawa, Kim Boyer, Arun Krishnan and Marcos Salganicoff, "Stratified Learning of Local Anatomical Context for Lung Nodules in CT Images", CVPR'2010: IEEE Conference on Computer Vision and Pattern Recognition, June 2010, San Francisco, CA.
28, Systems and Methods for Automatic
Vertebra Edge Detection, Segmentation and Identification in 3D Imaging,
Le Lu, Marcos Salganicoff, Yiqiang Zhan, Xiang Zhou, and Jun
Ma*, US Patent granted, 8,437,521#,
May 7th, 2013.
27, Systems and Methods for Multilevel Nodule Attachment Classification in 3D CT Lung Images, Jinbo Bi, Le Lu, Marcos Salganicoff, Yoshihisa Shinagawa, and Dijia Wu*, Non-Provisional US Patent Application 12/880,385, filled on September 13th, 2010.
26, Multi-level Contextual Learning of Data, Dijia Wu*, Le Lu, Jinbo Bi, Yoshihisa Shinagawa, and Marcos Salganicoff, US Patent granted, 8,724,866#, May 14th, 2014.
25, Le Lu, Jinbo Bi, Shipeng Yu, Zhigang Peng, Arun Krishnan and Xiang Sean Zhou, "A Hierarchical Learning Approach for 3D Tubular Structure Parsing in Medical Imaging", ICCV'2009: 12th International Conference on Computer Vision, September 29-October 2, 2009, Kyoto, Japan.
24, Le Lu, Matthias Wolf, Jianming Liang, Murat Dundar, Jinbo Bi and Marcos Salganicoff, "A Two-level Approach Towards Semantic Colon Segmentation: Removing Extra-colonic Findings", MICCAI'2009: 12th International Conference on Medical Image Computing and Computer Assisted Intervention, vol. 1, pp. 1009-1016, September 20-24, 2009, London, UK.
23, Yimo Tao*, Le Lu, Maneesh
Dewan, Albert Y. Chen*, Jason Corso, Marcos Salganicoff, and Arun Krishnan,
Ground Glass Opacity Detection and Segmentation in CT Lung Images",
MICCAI'2009: 12th International
Conference on Medical Image Computing and Computer Assisted Intervention, vol.
1, pp. 715-723, September 20-24, 2009,
22, User Interface for Polyp Annotation, Segmentation, and Measurement in 3D Computed Tomography Colonography, Le Lu, Adrian Barbu, Matthias Wolf, Sarang Lakare, Luca Bogoni, Marcos Salganicoff, and Dorin Comaniciu, US Patent Granted, 8,126,244#, 2012.
21, Method and System for Polyp Segmentation for 3D Computed Tomography Colonography, Le Lu, Adrian Barbu, Matthias Wolf, Sarang Lakare, Luca Bogoni, Marcos Salganicoff, and Dorin Comaniciu, Non-provisional US Patent Granted, 8,184,888#, 2012, WO Patent WO/2009/038,647
INTERFACE UTILISATEUR POUR UNE ANNOTATION, UNE SEGMENTATION, ET UNE MESURE DE POLYPE EN COLOSCOPIE VIRTUELLE 3D, Le LU, A BARBU, M WOLF, S LAKARE, L BOGONI, M SALGANICOFF, D COMANICIU, WO Patent WO/2009/042,034
20, Le Lu, Adrian Barbu, Matthias Wolf, Jianming Liang, Luca Bogoni, Marcos Salganicoff, and Dorin Comaniciu, "Simultaneous Detection and Registration for Ileo-Cecal Valve Detection in 3D CT Colonography", ECCV'2008: European Conference on Computer Vision, October, 2008, Marseille, France.
19, Le Lu, Adrian Barbu, Matthias Wolf, Jianming Liang, Marcos Salganicoff, and Dorin Comaniciu, "Accurate Polyp Segmentation for 3D CT Colonography Using Multi-Staged Probabilistic Binary Learning and Compositional Model", CVPR'2008: IEEE Conference on Computer Vision and Pattern Recognition, June, 2008, Anchorage, USA.
18, Method and System for Detection and Registration of 3D Objects Using Incremental Parameter Learning, Adrian Barbu, Le Lu, Luca Bogoni, Marcos Salganicoff, and Dorin Comaniciu, US Patent Granted, 8,068,654#, November 29th, 2011.
2007 (Johns Hopkins)
17, Le Lu, "Image and Video Exploration by Classification and
Clustering Using Global and Local Visual Features", PH.D. Thesis, Computer Science Department,
16, Le Lu and Gregory D. Hager, "A Nonparametric Treatment on Location/Segmentation
Based Visual Tracking", CVPR'2007: IEEE Conference on
Computer Vision and Pattern Recognition (Oral), June, 2007,
15, Le Lu and Gregory D. Hager, "Dynamic Background/Foreground Segmentation From Images and
Videos using Random Patches", NIPS'2006: Neural Information
Processing and System,
14, Le Lu and Rene Vidal, "Combined Central and Subspace Clustering on Computer Vision Applications", ICML'2006: International Conference of Machine Learning, June 2006,
13, Le Lu, Xiangtian Dai and Gregory D. Hager, "Efficient Particle Filtering Using RANSAC with Application to 3D Face Tracking", Journal of Image and Vision Computing, vol 24, issue 6, pp.581-592, June 2006.
12, Le Lu, Kentaro Toyama and Gregory D. Hager,
"A Two Level Approach for Scene Recognition", CVPR'2005: IEEE Computer
Society Conference on Computer Vision and Pattern Recognition, June 2005,
11, Le Lu, Gregory D. Hager and Laurent Younes,
"A Three Tiered Approach for Articulated Object Action
Modeling and Recognition", NIPS'2004: Neural Information
Processing and System,
10, Le Lu, Xiangtian Dai and Gregory D. Hager, "A Particle Filter without Dynamics for Robust 3D Face Tracking", IEEE Workshop of Face Processing in Video jointed with CVPR'2004, June 2004,
9, Long Quan , Yichen Wei , Le Lu and Heung-Yeung Shum, "Constrained planar motion analysis by decomposition", Journal of Image and Vision Computing, vol 22, issue 5, pp. 379-389, May 2004.
8, Xiangtian Dai, Le Lu and
Gregory D. Hager, "Real-time Video
Mosaicing with Adaptive Parameterized Warping", Demo
Program, CVPR'2003: IEEE Computer Society Conference on Computer Vision
and Pattern Recognition, May 2003, Midson, USA.
2002 (MSRA & NLPR)
7, Le Lu and Hung-Tat Tsui, "Algebraic Characteristic, Geometric
Interpretation and Degeneracy Analysis of Planar Motions, with Applications to
Camera Self-calibration ", extended version submitted to Journal of Pattern
6, Le Lu and Hung-Tat Tsui, "Algebraic Characteristic and Geometric Interpretation of Planar Motions and their Applications to Camera Self-calibration", ACCV'2002: the 5th Asian Conference on Computer Vision, Jan. 2002,
5, Le Lu, Zhengyou Zhang, Heung-Yeung Shum,
Zhicheng Liu and Hong Chen, Model- and Exemplar-based Robust Head Pose
Tracking Under Occlusion and Varying Expression, IEEE Workshop on
Models versus Exemplars in computer Vision jointed with CVPR'2001, Dec. 2001, Hawaii,
4, Long Quan, Le Lu, Heung-Yeung Shum and M. Lhuillier, Concentric Mosaic(s), Planar Motion and 1D Cameras, ICCV'2001: The 8th international Conference on Computer Vision, pp.193-200, Jul. 2001, Vancouver, Canada.
3, Le Lu and Zhanyi Hu, "A New Factorization Technique for Projective Reconstruction", Chinese Journal of Electronics (English Edition), No.2, pp.196-202, Feb 2001.
2, Le Lu, Hung-Tat Tsui and Zhanyi Hu, "A Novel
Planar Motion Detection Method and the Robust Estimation of 1D Trifocal Tensor", ICPR'2000: The 15th
International Conference on Pattern Recognition, Vol. 3, pp.815-818, Sept.
2000, Barcelona, Spain.
1, Le Lu, Zhanyi Hu and Hung-Tat Tsui, "Sub-sequence Factorization - an Efficient Approach for Projective Reconstruction", ACCV'2000: The 4th Asian Conference on Computer Vision, pp.1052-1057, Jan. 2000,
Publications (Technical Report and Peer Reviewed Abstracts):
R3, Le Lu, A. Barbu, M. Wolf, J. Liang, S. Lakare, L. Bogoni, M. Salganicoﬀ, D. Comaniciu, A. Krishnan, A Supervised Learning Approach for Fast and Accurate Polyp Segmentation/Measurement in Virtual Colonoscopy, MICCAI: Workshop on Computational and Visualization Challenges in the New Era of Virtual Colonoscopy, New York, USA, 2008. (15 Minutes Talk)
R2, L. Bogoni, M. Wolf, A. Barbu, S. Lakare, M. Dundar, Le Lu, Learning-based Component for Suppression of False Positives located on the Ileo Cecal Valve: Evaluation of Performance on 802 CTC Cases, RSNA: Radiology Society of North America Annual Meeting, Chicago, USA, 2007. (12 Minutes Talk)
R1, S. Lakare, M. Wolf, L. Bogoni, A. Barbu, M. Dundar, Le Lu, M. Salganicoﬀ, Evaluation of a Learning-based Component for Suppression of False Positives Located on the Ileo Cecal Valve or Rectal Tube, ISVC: the 9th International Symposium on Virtual Colonoscopy, Boston, 2007.
Le Lu, "Real-time Video Mosaicing with Adaptive Parameterized Warping", Computational Interaction and Robotics Lab, Technical report, Computer Science Department, Johns Hopkins University, 2003. (example and code)
Radiology and Imaging Science, National Institutes of Health Clinical Center, 01/2013-now
Image Analytics and Informatics, Siemens Corporate Research, 11/2011-01/2013
Computer Aided Diagnosis Group, Siemens Medical Solutions, 11/2009-10/2011
Integrated Data Systems Dept., Siemens Corporate Research, Inc. 10/2006-11/2009
Computer Science Dept.,
Interactive Visual Media Group, Microsoft Research, Redmond, (Intern), 06/2004-08/2004
Visual Computing Group, Microsoft
Electronic Engineering Dept.,
National Laboratory of Pattern
Prof. Laurent Younes, Center of Imaging Science, Johns Hopkins university
Prof. Rene Vidal, Center of Imaging Science, Johns Hopkins University
Dr. Kentaro Toyama, Microsoft Research, summer 2004
Prof. Long Quan, HKUST, 2000
Dr. Zhengyou Zhang, Microsoft Research, 2000-2001
Dr. Harry Shum, Microsoft Research Asia, 2000-2001
Collaborators (colleagues, postdocs, interns & IRTA fellows):
Dr. Hoo-Chang Shin (NIH), Dr. Holger Roth (NIH), Mr. Ari Seff (NIH), Dr. Amal Farag (NIH); Dr. Mingchen Gao (NIH), Dr. Ziyue Xu (NIH), Dr. Adrian Barbu (FSU), Dr. Jianhua Yao (NIH), Dr. Jianmin Liu (NIH), Dr. Ronald M. Summers (NIH);
Dr. Jinbo Bi (UCONN), Dr. Matthias Wolf, Dr. Bing Jian (Google), Dr. Jianming Liang (ASU), Dr. Shipeng Yu (Linkedin), Dr. Yiqiang Zhan (Siemens), Dr. Zhigang Peng (Siemens), Dr. Maneesh Dewan (Google), Dr. Shijun Wang (NIH);
*Summer Interns: Dr. Albert Y.C. Chen
National Institutes of Health Clinical Center
Radiology and Imaging Sciences
Clinical Image Processing & Services
10 Center Drive, 1C515