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Sameer
K
Antani
,
PhD
Staff Scientist
Location: 
38A
/
10S1010
Phone Number: (
301
435-3218
Expertise and Research Interests: 

Dr. Antani is a versatile researcher leading several scientific and technical research projects. He applies his expertise in biomedical image informatics, automatic medical image interpretation, machine learning, information retrieval, computer vision, and related topics in computer science and engineering technology toward advancing the role of computational sciences in biomedical research, education, and clinical care. His current R&D projects include: an automatic screening system for detecting presence of Tuberculosis (TB) and other pulmonary abnormalities in digital chest x-ray images; an automatic cell counting system for malaria screening; retrieval of fMRI data based on activation similarity; and, the OPEN-iSM biomedical image retrieval system that provides text and visual search capability to retrieve over 3.2 million images and videos from approximately 1.2 million Open Access biomedical research articles from NLM’s PubMed Central® repository.

His other work includes contributions to cervical cancer diagnostics through cervicography and histology image analysis; retrieval of spine x-rays from an image database using visual and shape queries; and, next generation scientific publishing.

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 as an Associate Editor for the IEEE Journal of Biomedical and Health Informatics.

Honors and Awards: 

In 2015, the malaria screening project received awards from HHS Ventures Fund, a Department of Health and Human Services initiative that serves as an “incubator for new ideas” run out of the HHS IDEA Lab. Prior, in 2014, his project on automated chest X-ray screening project was, similarly, an awardee of HHS Ignite. In addition to several staff achievement awards, 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: 
Rajaraman S, Antani SK, Candemir S, Xue Z, Abuya J, Kohli M, Alderson P, Thoma GR. Comparing deep learning models for population screening using chest radiography. Proc. SPIE 10575, Medical Imaging 2018: Computer-Aided Diagnosis, 105751E (27 February 2018).
Xue Z, Antani SK, Long LR, Thoma GR. Using deep learning for detecting gender in adult chest radiographs. SPIE Medical Imaging 2018
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
Almubarak HA, Stanley RJ, Long LR, Antani SK, Thoma GR, Zuna R, Frazier SR. Convolutional Neural Network Based Localized Classification of Uterine Cervical Cancer Digital Histology Images. Procedia Computer Science, Volume 114, 2017, Pages 281-287, ISSN 1877-0509, https://doi.org/10.1016/j.procs.2017.09.044.
Bryant B, Sari-Sarraf H, Long LR, Antani SK. A Kernel Support Vector Machine Trained Using Approximate Global and Exhaustive Local Sampling. Proceedings of the 4th IEEE/ACM International Conference on Big Data Computing, Applications and Technologies (BDCAT) 2017, Austin, Texas, USA, December 2017. Pp. 267-8 DOI: https://doi.org/10.1145/3148055.3149206
de Herrera G, Long LR, Antani SK. Graph Representation for Content–based fMRI Activation Map Retrieval. Proceedings of 1st Life Sciences Conference, Sydney, Australia, December 2017 pp. 129-32 DOI: https://doi.org/10.1109/LSC.2017.8268160.
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.
Zou J, Antani SK, Thoma GR. Localizing and Recognizing Labels for Multi-Panel Figures in Biomedical Journals. Proceedings of International Conference on Document Analysis and Recognition, November 13, 2017
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
Moallem G, Poostchi M, Yu H, Silamut K, Palaniappan N, Antani SK, Hossain Md Amir, Maude RJ, Jaeger S, Thoma GR. Detecting and Segmenting White Blood Cells in Microscopy Images of Thin Blood Smears. Applied Imagery Pattern Recognition Workshop (AIPR), 2017

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