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Branch Chief
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Expertise and Research Interests: 

Dr. Antani is a versatile lead researcher advancing the role of computational sciences and automated decision making in biomedical research, education, and clinical care. His research interests include topics in medical imaging and informatics, machine learning, data science, artificial intelligence, and global health. He applies his expertise in machine learning, biomedical image informatics, automatic medical image interpretation, data science, information retrieval, computer vision, and related topics in computer science and engineering technology His primary R&D areas include cervical cancer, HIV/TB, and visual information retrieval, among others. Google Scholar.

Dr. Antani is currently also (Acting) Branch Chief for the Communications Engineering Branch and the Computer Science Branch in the Lister Hill National Center for Biomedical Communications at the National Library of Medicine.

Professional Activities: 

Dr. Antani is a Senior Member of the International Society of Photonics and Optics (SPIE), Institute of Electrical and Electronics Engineers (IEEE) and the IEEE Computer Society. He serves as the Vice Chair for Computational Medicine on the IEEE Technical Committee on Computational Life Sciences (TCCLS) and the IEEE Life Sciences Technical Community (LSTC). Dr. Antani currently serves on the editorial boards of the MDPI Journal Data and the Elsevier Journal Heliyon.

Honors and Awards: 

In addition to many staff achievement awards, in 2016, Dr. Antani received the NIH Director’s Award -- “For exemplary leadership and creative engineering in developing an automated chest x-ray screening system for tuberculosis and deploying it in Africa”. In 2016, he also received the Federal Computer Weekly - Federal 100 Award. 2015, Dr. Antani received the Information Technology Excellence Award from the Food and Drug Administration (FDA) - Center for Drug Evaluation and Research (CDER) along with other RAPID Project Team members for OTS Data Mining for developing a mobile application “that uses modern technology for real time adverse event reports and management in FDA”. In 2013, he received the NIH Award of Merit for his contribution to novel image and text based methods for searching the biomedical literature. In 2012, he received the NIH Award of Merit for his contributions to novel ways of search biomedical literature using visual and text queries in the Open-i® project. In 2009, he received the NIH Award of Merit for his contributions to Content-Based Image Retrieval in Geographically Distributed Systems. In 2008, he was a member of the NLM team recognized by Internet2 for developing geography-independent cancer research tools.

Publications/Tools by Sameer Antani: 
Candemir S, Rajaraman S, Thoma GR, Antani SK. Deep Learning for Grading Cardiomegaly Severity in Chest X-rays: An Investigation. Proc. IEEE Life Sciences Conference (LSC 2018), Montreal, Quebec, Canada, 28 – 30 October 2018. pp. 109-113.
Rajaraman S, Candemir S, Kim I, Thoma GR, Antani SK. Visualization and Interpretation of Convolutional Neural Network Predictions in Detecting Pneumonia in Pediatric Chest Radiographs. Appl. Sci. 2018, 8, 1715.
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
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.
Rajaraman S, Candemir S, Xue Z, Alderson P, Kohli M, Abuya J, Thoma GR, Antani SK. A novel stacked generalization of models for improved TB detection in chest radiographs. Proc. IEEE Engineering in Medicine and Biology Conference (EMBC 2018), Honolulu, Hawaii, 2018. pp. 718-721.
Xue Z, Rajaraman S, Long LR, Antani SK, Thoma GR. Gender Detection from Spine X-ray Images Using Deep Learning. Proc. IEEE International Symposium on Computer-Based Medical Systems (CBMS), Karlstad, Sweden, 2018. pp. 54-58, DOI:10.1109/CBMS.2018.00017.
Sornapudi S, Stanley RJ, Stoecker WV, Almubarak H, Long LR, Antani SK, Thoma GR, Zuna R, Frazier SR. Deep Learning Nuclei Detection in Digitized Histology Images by Superpixels. J Pathol Inform. 2018 Mar 5;9:5. doi: 10.4103/jpi.jpi_74_17. eCollection 2018.