Last updated: October 02, 2011

National Library of Medicine
Communications Engineering Branch/MSC 3824
Bldg. 38A, Room B1N 28V
8600 Rockville Pike
Bethesda, MD 20894 USA
(301) 435-3262

Dr. Mahmudur Rahman joined the Lister Hill National Center for Biomedical Communications at the National Library of Medicine (NLM) in Nov 2008. He has a Ph.D. degree in Computer Science from Concordia University, Montreal, Canada with an emphasis on Medical informatics and Image Retrieval. He is currently working with Dr. Sameer Antani and Dr. Dina Demner-Fushman on multiple imaging projects, such as Multimodal Retrieval in Context and Concept feature space, Machine Learning and Interactive algorithm for Content-Based Image Retrieval, and Chest X-ray screening/TB image analysis. Over the course of his doctoral and post-doctoral research, he has authored a book, published articles in several journals, such as IEEE Transaction on Information Technology in Biomedicine, Computerized Medical Imaging and Graphics, Journal of Visual Communication and Image Representation, and presented his works in numerous conferences and workshops, such as, CBMS, ISBI, CIVR, ACM-MIR, SPIE, CLEF, etc.

Current Projects

Image and Text Integration (ITI): The goal of this project is to develop robust algorithms to augment the repository of facts for informed clinical decision making with images. This research focuses on the algorithms for automatic biomedical image annotation by utility for evidence-based practice, and integration of text and image content search strategies. Dr. Sameer Antani and Dr. Dina Demner-Fushman lead this development combining our complementary strengths in textual searching and content-based image retrieval (CBIR).

Chest X-ray Screening / TB image analysis Project: The aim of this project is to develop a biomedical image processing system for clinically screening patients in rural parts of Kenya for pulmonary pathologies, in general, and tuberculosis, in particular. The screening system will classify the radiology images into coarse categories (normal/abnormal) and with an aim to refine the classification according to the radiologist's readings. Once the equipment is deployed, the project aims to obtain routinely collected data about the usage of the equipment, the number of X-rays acquired, durability of the equipment, and performance of the screening algorithm to determine the long-term viability of such systems in other parts of the world, and possibly during resource constrained settings often resulting from disasters.