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NLM Intramural Research Program

About

Picture of Sameer Antani, PhD

Sameer Antani, PhD

Staff Scientist, Biomedical Informatics Branch, LHNCBC

Research in machine learning and artificial intelligence, medical image and signal processing, and information retrieval for solving challenging problems and advancing health.

Contact Information

Building 38A, 8600 Rockville Pike MSC 6075 Bethesda, MD 20894

Tel: (301) 435-3218

sameer.antani@nih.gov

Research Interests

Dr. Antani is a versatile senior researcher with expertise in machine learning and artificial intelligence (ML/AI), biomedical image informatics, image processing and computer vision, and information retrieval. His research studies the use of Ml/AI as a part of his interest in advancing computational sciences and engineering in biomedical research, education, and clinical care. In addition to advancing AI techniques for decision making and analysis of large biomedical data, his research extends to applying lessons learned on important health problems through trans-NIH collaborations, e.g., NCI (cervical cancer), NIAID (HIV/TB in adults and children, and drug resistant variants), among others. Dr. Antani is a senior member of the International Society of Photonics and Optics (SPIE), the Institute of Electrical and Electronics Engineers (IEEE). He serves as the vice chair for computational medicine on the IEEE Computer Society's Technical Committee on Computational Life Sciences (TCCLS) and the IEEE Life Sciences Technical Community (LSTC).

Publications

Rajaraman S, Kim I, Antani S. Evaluating and visualizing the learned behavior of convolutional neural network ensembles toward for abnormality detection in chest radiographs. PeerJ. Forthcoming; 8:e8693. doi: https://doi.org/10.7717/peerj.8693.

Sornapudi S, Hagert J, Stanley R, Stoecker WV, Long R, Antani S, Thoma G, Zuna R, Frazier SR. EpithNet: Deep Regression for Epithelium Segmentation in Cervical Histology Images. J Pathology Informatics. 2020 March; 11(10). doi: 10.4103/jpi.jpi_53_19.

Rajaraman S, Antani S. Modality-specific deep learning model ensembles toward improving TB detection in chest radiographs. IEEE Access. 2020 February; 8:27318-26. doi: 10.1109/ACCESS.2020.2971257.

Zou J, Thoma G, Antani S. Unified Deep Neural Network for Segmentation and Labeling of Multipanel Biomedical Figures. Journal of the Association for Information Science and Technology. 2020 January; doi: 10.1002/asi.24334.

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