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

Dr. Stefan Jaeger is a staff scientist at the Lister Hill National Center for Biomedical Communications at the United States National Library of Medicine (NLM), which is part of the National Institutes of Health (NIH). He received his diploma from the University of Kaiserslautern and his PhD from the University of Freiburg, Germany, both in computer science. Dr. Jaeger has an international research background in academia as well as in industry. He has held research positions at Chinese Academy of Sciences, University of Maryland, University of Karlsruhe, Daimler, and others. At NLM, he supervises research on deep machine learning and data science for diagnosing infectious diseases, and conducts research into image informatics and artificial intelligence for clinical care and education. His research interests include machine learning, biomedical image analysis, artificial intelligence, medical informatics, and theoretical medicine. He has more than hundred publications in these areas, several of which received best paper awards and nominations, including two patents.

Professional Activities: 

Dr. Jaeger has acted as reviewer for national research councils and programs. He has served on the editorial boards of Quantitative Imaging in Medicine and Surgery, Electronic Journal of Emerging Infectious Diseases (China), and Electronic Letters on Computer Vision and Image Analysis (ELCVIA). He has also served as conference chair, keynote speaker, or program committee member for many conferences and workshops in his research area.

Honors and Awards: 
  • Award of Merit, National Institutes of Health, 2017.
  • HHS Innovation Ventures Award, U.S. Department of Health and Human Services, 2015.
  • Special Achievement Award, U.S. National Library of Medicine, 2015.
  • 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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