User:Tigerlelu/sandbox

Dr. Le Lu lead PAII Inc's division of Bethesda Research Lab, after more than five productive years at National Institutes of Health, Clinical Center, Radiology and Imaging Science Department, and from NVIDIA AI-Infra division. He is an IEEE Fellow on medical imaging, AI and oncology imaging; also serve as an Associate Editer for IEEE Trans. Pattern Analysis and Machine Intelligence (IF: 17.8), and IEEE Signal Processing Letters.

He has been serving as one of the active strong links between the MICCAI/TMI/MedIA community and IEEE Computer Society (CVPR/TPAMI). His work have been selected for MICCAI 2020 and 2019 Medical Image Analysis special issues (best selected paper track), MICCAI 2018 young researcher publication impact award, MICCAI 2017 Young Scientist Award runner up, MICCAI 2017 and 2016 travel awards; IEEE Trans. Medical Imaging's the most cited article in 5 years (2016~2020), IEEE CVPR most cited medical imaging paper in 5 years (2016~2020). His two most important medical imaging dataset work both were published at IEEE CVPR 2017 (NIH ChestXray14) and 2018 (NIH DeepLesion). He also contributed to AAAI/NeurIPS/ICML in the past. My former NIH trainees won the RSNA Informatics best paper awards four times in the last 5 years (X. Wang 2016, K. Yan 2018, Y. Tang 2019, Y. Tang 2020)!

IEEE Fellow (Contributions to Machine Learning for Cancer Detection and Diagnosis) class of 2021, IEEE Senior Member, since 2014

Ph.D. in Computer Science, Johns Hopkins University, Baltimore, Maryland, May 2007 (Advisor: Gregory D. Hager) MSE in Computer Science, Johns Hopkins University, Baltimore, Maryland, May 2004 (Advisor: Gregory D. Hager)

DeepPrognosis: Preoperative Prediction of Pancreatic Cancer Survival and Surgical Margin via Dynamic Contrast-Enhanced CT Imaging. MICCAI 2020 (Invited for Medical Image Analysis Best Paper Special Issue) "Accurate Esophageal Gross Tumor Volume Segmentation in PET/CT using Two-Stream Chained 3D Deep Network Fusion", MICCAI 2019 (Invited for Medical Image Analysis Best Paper Special Issue) "Deep Lesion Graphs in the Wild: Relationship Learning and Organization of Significant Radiology Image Findings in a Diverse Large-scale Lesion Database", IEEE CVPR, 2018 "ChestX-ray8: Hospital-scale Chest X-ray Database and Benchmarks on Weakly-Supervised Classification and Localization of Common Thorax Diseases", IEEE CVPR, 2017 "Progressive and Multi-Path Holistically Nested Neural Networks for Pathological Lung Segmentation from CT Images", Travel Award & Young Scientist Award Runner-up, MICCAI 2017 "Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning", IEEE Trans. on Medical Imaging, May 2016 "A New 2.5D Representation for Lymph Node Detection using Random Sets of Deep Convolutional Neural Network Observations", MICCAI 2014 (MICCAI 2018 Young Research Publication Impact Award)