Biomedical Image Analysis and Informatics

Center For Information Technology

Investigators

Linked publications & trials

Abstract

The Biomedical Image Analysis and Services Section has a commitment to providing computational and engineering expertise to a variety of clinical and biomedical activities at NIH. Specifically, PET, ultrasound, CT, MRI, microscopy, imaging in cancer research, and imaging related to neural dysfunction have been supported in a number of ways. To support science in the NIH intramural program, CIT has developed and continues to enhance a sophisticated platform-independent, n-dimensional, extensible image processing and visualization application. The MIPAV (Medical Image Processing Analysis and Visualization) is an application that enables quantitative analysis and visualization of biomedical imaging modalities (from micro to macro) and is used by researchers at NIH and around the world. At NIH, MIPAV has been used to analyze anatomical structures in CT datasets, assist in pretreatment analysis (registration and segmentation) of image datasets associated with radio frequency ablation (RFA) procedures, analysis of MRI datasets for NIMH, and has been used by NCI for the analysis of 2D and 3D microscopic samples. We also continue to support the NEI with research of diseases of the eye and support analysis of image data from the Osteoarthritis Initiative, a nationwide research study sponsored by the National Institutes of Health, that will help us better understand how to prevent and treat knee osteoarthritis. In addition, we manage and develop major components of the National Database for Autism Research (NDAR) project which is a collaborative biomedical informatics system created by the National Institutes of Health to provide a national resource to support and accelerate research in autism. NDAR is a collection of information systems supporting the full range of autism research activities, including genomic, imaging, laboratory, clinical, and behavioral data sources. It will provide the core technology for a data warehouse, a data-entry system, and a centralized source for common measures and their documentation. It will support large-scale, multi-site projects as well as pilot studies and basic science investigations.