PERSONNEL

MISSING

Stefan Jaeger, PhD

Computational Health Research Branch
Staff Scientist

Contact Information
Building 38A - Lister Hill Center, 10N1003O
301.435.3198
stefan.jaeger@nih.gov


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:

Yang F, Yu H, Kantipudi K, Rosenthal A, Hurt D, Antani S, Yaniv ZR, Jaeger S. Differentiating between Drug-Sensitive and Drug-Resistant Tuberculosis with Machine Learning for Clinical and Radiological Features. Quantitative Imaging in Medicine and Surgery, 0(0): 1–16, 2021. Publish Ahead of Print.

Karki M, Kantipudi K, Yu H, Yang F, Kassim Y, Yaniv Z,Jaeger S. Identifying Drug-Resistant Tuberculosis in Chest Radiographs: Evaluation of CNN Architectures and Training Strategies. 43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, accepted on July 15th, 2021, will be held virtually October 31 – November 4, 2021.

Kassim YM, Palaniappan K, Yang F, Poostchi M, Palaniappan N, Maude RJ, Antani S, Jaeger S. Clustering-Based Dual Deep Learning Architecture for Detecting Red Blood Cells in Malaria Diagnostic Smears. IEEE J Biomed Health Inform. 2021 May;25(5):1735-1746. doi: 10.1109/JBHI.2020.3034863. Epub 2021 May 11.

Yu H, Yang F, Rajaraman S, Ersoy I, Moallem G, Poostchi M, Palaniappan K, Antani S, Maude RJ, Jaeger S. Malaria Screener: a smartphone application for automated malaria screening. BMC Infect Dis. 2020 Nov 11;20(1):825. doi: 10.1186/s12879-020-05453-1.

Zheng Q, Lu Y, Lure F, Jaeger S, Lu P. Clinical and radiological features of novel coronavirus pneumonia. Journal of X-Ray Science and Technology, vol. 28, no. 3, pp. 391-404, 2020.

Jaeger S. The Golden Ratio of Learning and Momentum. arXiv:2006.04751 [cs.LG], 2020.

Yang F, Quizon N, Silamut K, Maude RJ, Jaeger S, Antani SK. Cascading YOLO: Automated Malaria Parasite Detection for Plasmodium Vivax in Thin Blood Smears. Proc. SPIE 11314, Medical Imaging 2020: Computer-Aided Diagnosis, 113141Q (16 March 2020); https://doi.org/10.1117/12.2549701

Cheng P, Lu P, Wang P, Zhou W, Yu W, Jaeger S, Li J, Wu T, Ke X, Zheng B, Antani SK, Candemir S, Quan S, Lure F, Li H, Guo L. Applying Deep Learning and Radiomics to Determine Biological Lung and Heart Age from Chest Radiographs. Chinese Congress of Radiology.

Wang X, Guan Y, Lu P, Cheng G, Zhou W, Jaeger S, Zhen B, Antani SK, Yin X, Yu W, Guo L, Quan S, Lure F, Hurt D, Gabrielian A, Li H, Ke X. Screening of Tuberculosis in a TB High-burden Large Rural Region in China with Deep Learning Multi-modality Artificial Intelligence. Chinese Congress of Radiology.

Yu H, Yang F, Silamut R, Maude S, Jaeger S, Antani SK. Automatic Blood Smear Analysis with Artificial Intelligence and Smartphones. ASTMH 68th Annual Meeting, Washington DC, Nov. 20-24, 2019.

Rajaraman S, Jaeger S, Antani SK. Performance evaluation of deep neural ensembles toward malaria parasite detection in thin-blood smear images. PeerJ. doi: 10.7717/peerj.6977.

Lure F, Jaeger S, Cheng G, Li H, Lu P, Yu W, Kung J, Guan Y. Applying Multi-modality Artificial Intelligence for Screening of Tuberculosis in a TB High-burden Large Rural Region in China. TBScience, 50th Union World Conference on Lung Health, Hyderabad, India.

Yang F, Poostchi M, Silamut K, Maude RJ, Jaeger S, Thoma G. Automated Parasite Classification of Malaria on Thick Blood Smears. ASTMH 67th Annual Meeting, New Orleans, LA, Oct. 28 – Nov. 1, 2018.

Yang F, Yu H, Silamut K, Maude RJ, Jaeger S, Antani SK. Parasite Detection in Thick Blood Smears Based on Customized Faster-RCNN. Proceedings of AIPR2019, Washington DC, USA, Oct 15-17, 2019.

Yang F, Yu H, Silamut K, Maude R, Jaeger S, Antani SK. Smartphone-Supported Malaria Diagnosis Based on Deep Learning. Proceedings of 10th Workshop on Machine Learning in Medical Imaging (MLMI 2019) in conjunction with MICCAI, Shenzhen, China, Oct 13-17, 2019.

Yang F, Poostchi M, Yu H, Zhou Z, Silamut K, Yu J, Maude RJ, Jaeger S, Antani S. . Deep learning for smartphone-based malaria parasite detection in thick blood smears. IEEE J Biomed Health Inform. 2020 May;24(5):1427-1438. doi: 10.1109/JBHI.2019.2939121. Epub 2019 Sep 23.

Rajaraman S, Jaeger S, Antani SK. Performance evaluation of deep neural ensembles toward malaria parasite detection in thin-blood smear images. PeerJ 7:e6977

Kesav N, Yang Q, Losert W, Kim J, Jaeger S, Sen HN. Novel automated processing techniques of fluorescein angiography (FA) images in patients with Uveitis. Annual Meeting of the Association for Research in Vision and Ophthalmology (ARVO).

Yang F, Yu H, Poostchi M, Silamut K, Maude RJ, Jaeger S. Smartphone-Supported Automated Malaria Parasite Detection. SIIM conference on Machine Intelligence in 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.

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.

Moallem G, Sari-Sarraf H, Poostchi M, Maude RJ, Silamut K, Hossain MA, Antani SK, Jaeger S, Thoma G. Detecting and segmenting overlapping red blood cells in microscopic images of thin blood smears. Proc. SPIE 10581, Medical Imaging 2018:Digital Pathology, 105811F (6 March 2018); doi: 10.1117/12.2293762.

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.

Rajaraman S, Antani SK, Xue Z, Candemir S, Jaeger S, Thoma GR. Visualizing abnormalities in chest radiographs through salient network activations in Deep Learning. Proc. IEEE Life Sciences Conference (LSC), Sydney, Australia, 2017. pp. 71-74, DOI:10.1109/LSC.2017.8268146.

Moallem G, Poostchi M, Yu H, Palaniappan N, Silamut K, Maude RJ, Hossain Md Amir, Jaeger S, Antani SK, Thoma GR. Detecting and Segmenting White Blood Cells in Microscopy Images of Thin Blood Smears [Poster]. Annual Meeting of the American Society of Tropical Medicine & Hygiene (ASTMH), Poster, 2017

Guan Y, Li M, Jaeger S, Lure F, Raptopoulos V, Lu P, Folio LR, Candemir S, Antani SK, Siegelman J, Li J, Wu T, Thoma GR, Qu S. Applying Artificial Intelligence and Radiomics for Computer Aided Diagnosis and Risk Assessment in Chest Radiographs. 2nd Conference on Machine Intelligence in Medical Imaging (CMIMI) of the Society for Imaging Informatics in Medicine (SIIM), Poster, 2017.

Moallem G, Jaeger S, Poostchi M, Palaniappan N, Yu H, Silamut K, Maude RJ, Antani SK, Thoma GR. White Blood Cell Detection and Segmentation in Microscopy Images of Thin Blood Smears [Poster]. NIH Research Festival, Poster, 2017

Rajaraman S, Antani SK, Jaeger S. Visualizing Deep Learning Activations for Improved Malaria Cell Classification. Proceedings of The First Workshop in Medical Informatics and Healthcare (MIH 2017), Proceedings of Machine Learning Research (PMLR), v. 69, p. 40-47.

Jaeger S. Malaria Datasets.

Ding M, Antani SK, Jaeger S, Xue Z, Candemir S, Kohli M, Thoma GR. Local-Global Classifier Fusion for Screening Chest Radiographs. Proc. SPIE 10138, Medical Imaging 2017: Imaging Informatics for Healthcare, Research, and Applications, 101380A (March 13, 2017); doi:10.1117/12.2252459

Lure F, Jaeger S, Antani SK. Automated Systems for microscopic and radiographic tuberculosis screening. Electronic Journal of Emerging Infectious Diseases, Vol. 2, No. 1, pp. 5-9, February 2017. [In Chinese]

Liang Z, Powell A, Ersoy I, Poostchi M, Silamut K, Palaniappan K, Guo P, Hossain M, Antani SK, Maude R, Huang J, Jaeger S, Thoma GR. CNN-Based Image Analysis for Malaria Diagnosis. IEEE International Conference on Bioinformatics & Biomedicine (BIBM), Shenzhen, China, 2016.

Kwon J, Wang A, Burke DJ, Boudreau HE, Lekstrom KJ, Korzeniowska A, Sugamata R, Kim YS, Yi L, Ersoy I, Jaeger S, Palaniappan K, Ambruso DR, Jackson SH, Leto TL. Peroxiredoxin 6 (Prdx6) supports NADPH oxidase1 (Nox1)-based superoxide generation and cell migration. Free Radic Biol Med. 2016 Jul;96:99-115. doi: 10.1016/j.freeradbiomed.2016.04.009. Epub 2016 Apr 14.

Candemir S, Jaeger S, Antani S, Bagci U, Folio LR, Xu Z, Thoma G. Atlas-based rib-bone detection in chest X-rays. Comput Med Imaging Graph. 2016 Jul;51:32-9. doi: 10.1016/j.compmedimag.2016.04.002. Epub 2016 Apr 13.

Candemir S, Jaeger S, Lin W, Xue Z, Antani SK, Thoma GR. Automatic heart localization and radiographic index computation in chest x-rays. Proc. SPIE. 9785, Medical Imaging 2016: Computer-Aided Diagnosis, 978517. DOI: 10.1117/12.2217209.

Karargyris A, Siegelman J, Tzortzis D, Jaeger S, Candemir S, Xue Z, KC S, Vajda S, Antani SK, Folio L, Thoma GR. Combination of texture and shape features to detect pulmonary abnormalities in digital chest X-rays. Int J Comput Assist Radiol Surg. 2016 Jan;11(1):99-106. doi: 10.1007/s11548-015-1242-x. Epub 2015 Jun 20.

Xue Z, Candemir S, Antani SK, Long LR, Jaeger S, Demner-Fushman D, Thoma GR. Foreign Object Detection in Chest X-rays. Proc IEEE International Conference on Bioinformatics and Biomedicine (BIBM) 2015, International Workshop on Biomedical and Health Informatics, Bethesda, Maryland, Nov. 9-12, 2015, pp: 56-61.

Folio, L, Sigelman, J, Wang, Y, Lu, P, Antani SK, Jaeger S. Automatic Identification and Classification of Tuberculosis Findings on Chest Radiographs for Global Surveillance Programs [Abstract]. Annual Meeting of the American Roentgen Ray Society (ARRS)

Ruiz A, Allette K, Francis D, Lamping E, Jaeger S, Folio L, Apolo A. Patterns of soft tissue metastasis in patients with urothelial carcinoma using tumor volume heatmaps [Poster]. NIH Summer Research Program Poster Day, Aug 6, 2015

Xue Z, You D, Candemir S, Jaeger S, Antani SK, Long LR, Thoma GR. Chest X-ray Image View Classification. The 28th IEEE International Symposium on Computer-Based Medical Systems

Candemir S, Antani SK, Jaeger SR, Thoma GR. Lung boundary detection in pediatric chest x-rays. Proc. SPIE. 9418, Medical Imaging 2015: PACS and Imaging Informatics: Next Generation and Innovations, 94180Q. (March 17, 2015) doi: 10.1117/12.2081060.

KC S, Candemir S, Jaeger S, Folio L, Karargyris A, Antani SK, Thoma GR. Automatically detecting rotation in chest radiographs using principal rib-orientation measure for quality control. Int. J. Patt. Recogn. Artif. Intell, Vol 29 No. 2. DOI: 10.1142/S021800141.5570013

Jaeger S. Detecting Disease in Radiographs with Intuitive Confidence. ScientificWorldJournal. 2015;2015:946793. doi: 10.1155/2015/946793. Epub 2015 Oct 1.

Jaeger S, Candemir S, Antani SK, Wang, Lu P, Thoma GR. Two public chest X-ray datasets for computer-aided screening of pulmonary diseases. Quant Imaging Med Surg. 2014 Dec;4(6):475-7. doi: 10.3978/j.issn.2223-4292.2014.11.20.

Rajaraman S, Jaeger S, Antani SK. Datasets: Tuberculosis Chest X-ray Datasets.

Gordon, E, Ersoy, I, Jaeger S, Waisberg, M, Pena, M, Thoma GR, Antani SK, Pierce, S, Palaniappan, K. Retinal Microcirculation Dynamics During an Active Malarial Infection [Poster]. Annual Meeting of the American Society of Tropical Medicine and Hygiene (ASTMH), 2014.

Kwon J, Burke DJ, Wang A, Boudreau HE, Lekstrom KJ, Korzeniowska A, Kim YS, Li L, Bunyak F, Jaeger S, Palaniappan K, Ambruso DR, Jackson SH, Leto TL. Peroxiredoxin 6 (Prdx6) supports NADPH oxidase1 (Nox1)-based reactive oxygen species generation and cell migration: collaboration of oxidant generating and scavenging systems [Poster]. NIH Research Festival 2014.

KC S, Candemir S, Jaeger S, Folio L, Karargyris A, Antani SK, Thoma GR. Rotation detection in chest radiographs based on generalized line histogram of rib-orientations. IEEE 27th International Symposium on Computer-Based Medical Systems, New York, NY, USA, May 27-29, 2014: page 138-142.

Jaeger S, Karargyris A, Candemir S, Folio L, Siegelman J, Callaghan FM, Xue Z, Palaniappan K, Singh RK, Antani SK, Thoma GR, Wang, Lu P, McDonald CJ. Automatic tuberculosis screening using chest radiographs. IEEE Trans Med Imaging. 2014 Feb;33(2):233-45. doi: 10.1109/TMI.2013.2284099. Epub 2013 Oct 1.

Candemir S, Jaeger S, Palaniappan K, Musco J, Singh RK, Xue Z, Karargyris A, Antani SK, Thoma GR, McDonald CJ. Lung segmentation in chest radiographs using anatomical atlases with nonrigid registration. IEEE Trans Med Imaging. 2014 Feb;33(2):577-90. doi: 10.1109/TMI.2013.2290491. Epub 2013 Nov 13.

Karargyris A, Candemir S, Jaeger S, Xue Z, Antani SK, Thoma GR. A Combined Approach for Lung Boundary Segmentation of Chest X-Ray Images [Poster]. NIH Intramural Research Festival, Bethesda MD, November 6-8, 2013.

Xue Z, Jaeger S, Karargyris A, Candemir S, Antani SK, Long LR, Thoma GR, McDonald CJ. A System for Automated Screening for Tuberculosis using Digital Chest X-rays for Resources-Constrained Regions [Poster]. NIH Intramural Research Festival, Bethesda MD, November 6-8, 2013.

Karargyris A, Folio L, Siegelman J, Callaghan FM, Candemir S, Xue Z, Lu P-X, Wang, Antani SK, Thoma GR, Jaeger S. Comparing the Performance of Man and Machine for TB Screening in Chest Radiographs [Poster]. NIH Intramural Research Festival, Bethesda MD, November 6-8, 2013.

Gordon E, Waisberg M, Ersoy I, Pena M, Jaeger S, Pierce S. The eye as a window to investigate the CNS microvasculature during a dynamic malaria infection (Abstract). Third Annual Seminar on Molecular Imaging of Infectious Diseases, September 23, 2013.

Jaeger S, Karargyris A, Candemir S, Siegelman J, Folio L, Antani S, Thoma G. Automatic screening for tuberculosis in chest radiographs: a survey. Quant Imaging Med Surg. 2013 Apr;3(2):89-99. doi: 10.3978/j.issn.2223-4292.2013.04.03.

Jaeger S. The neurological principle: how traditional Chinese medicine unifies body and mind. Int. J. Functional Informatics and Personalised Medicine, Vol. 4, No. 2, 2013.

Pearson G, Gill MJ, Antani SK, Neve L, Miernicki G, Phichaphop K, Kanduru A, Jaeger S, Thoma GR. The Role of Location For Family Reunification During Disasters. HealthGIS 2012. Redondo Beach, CA. November 2012.

Candemir S, Jaeger S, Palaniappan K, Antani SK, Thoma GR. Graph Cut Based Automatic Lung Boundary Detection in Chest Radiographs. 1st Annual IEEE Healthcare Innovation Conference of the IEEE EMBS Houston, Texas USA, 7 - 9 November, 2012.

Jaeger S, Karargyris A, Antani SK, Thoma GR. Automatic Screening For Lung Diseases In Chest Radiographs: a Global Health Initiative [Poster].. NIH Research Festival. October 2012.

Jaeger S. An information-theoretic neural model based on concepts in Chinese medicine. 2012 IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW).

Jaeger S, Karargyris A, Antani SK, Thoma GR. Detecting tuberculosis in radiographs using combined lung masks. 34th Int. Conf. of the IEEE Engineering in Medicine & Biology Society (EMBC). San Diego, CA. August 2012:4978-4981. doi: 10.1109/EMBC.2012.6347110.

Jaeger S. A geomedical approach to Chinese medicine: The origin of the yin-yang symbol. Recent Advances in Theories and Practice of Chinese Medicine, Haixue Kuang (Ed.), ISBN: 978-953-307-903-5, InTech, 2012.

Jaeger S, Antani S, Thoma GR. Tuberculosis Screening of Chest Radiographs. 2 June 2011, SPIE Newsroom. DOI: 10.1117/2.1201105.003732i.