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Stefan
Jaeger
,
PhD
NIH Research Fellow
Location: 
38A
/
10N1003O
Phone Number: (
301
435-3198
Expertise and Research Interests: 

Dr. Stefan Jaeger is an NIH Research Fellow at the Lister Hill National Center for Biomedical Communications at the United States National Library of Medicine (NLM), part of the National Institutes of Health (NIH). He received his diploma in computer science from University of Kaiserslautern and his PhD from University of Freiburg, Germany. Dr. Jaeger has an international research background, both in academia and industry. He has held, among others, positions at Chinese Academy of Sciences, University of Maryland, Tokyo University of Agri. & Tech., University of Karlsruhe, and Daimler. His research interests include biomedical imaging, medical informatics, pattern recognition, machine learning, and Chinese medicine. He has about sixty publications in these areas, several of which received best paper awards and nominations, including two patents.

Professional Activities: 

He is associate editor of Electronic Letters on Computer Vision and Image Analysis, and editorial board member of Quantitative Imaging in Medicine and Surgery.

Honors and Awards: 
  • HHS-Ignite Pathway Team Award for Automatic X-ray Screening for Rural Areas, U.S. Department of Health and Human Services, 2014.
  • Certificate of Appreciation, Communications Engineering Branch, Lister Hill National Center for Biomedical Communications, 2014.
  • IAPR/ICDAR Young Investigator Award Nomination, International Association of Pattern Recognition, International Conference on Document Analysis and Recognition, 2007.
  • Best Student Paper, International Workshop on Frontiers in Handwriting Recognition (IWFHR), La   Baule, France;  Y. Li, Y. Zheng, D. Doermann, S. Jaeger. A New Algorithm for Detecting Text Line in Handwritten Documents, 2006.
  • Best Paper Nomination, International Conference on Document Analysis and Recognition (ICDAR), Seoul, Korea: S. Jaeger, H. Ma, D. Doermann. Identifying Script on Word-Level with Informational  Confidence, 2005.
  • Research Fellowship, New Energy and Industrial Technology Development Organization (NEDO), Japan, Nov. 2000 – March 2003.
  • PhD Thesis Award, German Research Centers for Artificial Intelligence, 1999.
  • Daimler-Benz Graduate Fellow, Daimler-Benz Research Center, Ulm, Germany, 1994 –1998.
Publications/Tools by Stefan Jaeger: 
Moallem G, Sari-Sarraf H, Poostchi Mohammadabadi M, Maude R, Silamut K, Antani SK, Jaeger S. Detecting and segmenting overlapping red blood cells in microscopic images of thin blood smears. SPIE Medical Imaging, 2018.
Jaeger S, Antani SK, Rajaraman S, Yang F, Yu H. Malaria Screening: Research into Image Analysis and Deep Learning. Report to the Board of Scientific Counselors September 2018.
Jaeger S, Juarez-Espinosa O, Candemir S, Poostchi Mohammadabadi M, Yang F, Kim L, Ding M, Folio L, Antani SK, Gabrielian A, Hurt D, Rosenthal A, Thoma GR. Detecting drug-resistant tuberculosis in chest radiographs International Journal of Computer Assisted Radiology and Surgery https://doi.org/10.1007/s11548-018-1857-9
Vajda S, Karargyris A, Jaeger S, Santosh KC, Candemir S, Xue Z, Antani SK, Thoma GR. Feature Selection for Automatic Tuberculosis Screening in Frontal Chest Radiographs. J Med Syst. 2018 Jun 29;42(8):146. doi: 10.1007/s10916-018-0991-9.
Rajaraman S, Silamut K, Hossain MA, Ersoy I, Maude RJ, Jaeger S, Thoma GR, Antani SK. Understanding the learned behavior of customized convolutional neural networks toward malaria parasite detection in thin blood smear images. J Med Imaging (Bellingham). 2018 Jul;5(3):034501. doi: 10.1117/1.JMI.5.3.034501. Epub 2018 Jul 18.
Xue Z, Long LR, Jaeger S, Folio L, Thoma GR. Extraction of Aortic Knuckle Contour in Chest Radiographs Using Deep Learning. EMBC 2018.
Rajaraman S, Antani SK, Poostchi Mohammadabadi M, Silamut K, Hossain MA, Maude RJ, Jaeger S, Thoma GR. Pre-trained convolutional neural networks as feature extractors toward improved malaria parasite detection in thin blood smear images. PeerJ. 2018 Apr 16;6:e4568. doi: 10.7717/peerj.4568. eCollection 2018.
Xue Z, Jaeger S, Antani SK, Long LR, Karargyris A, Siegelman J, Folio L, Thoma GR. Localizing tuberculosis in chest radiographs with deep learning. Proc SPIE 10579, Medical Imaging 2018: Imaging Informatics for Healthcare, Research, and Applications, 105790U (6 March 2018) pp. doi: 10.1117/12.2293022
Xue Z, Jaeger S, Antani SK, Long LR, Karargyris A, Siegelman J, Folio LR, Thoma GR. Localizing tuberculosis in chest radiographs with deep learning. SPIE Medical Imaging 2018
Poostchi M, Silamut K, Maude RJ, Jaeger S, Thoma GR. Image analysis and machine learning for detecting malaria. Transl Res. 2018 Apr;194:36-55. doi: 10.1016/j.trsl.2017.12.004. Epub 2018 Jan 12.

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