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The NLM-Mayo Image Collection: Common Access to Uncommon Data

Holmes, David R III, Workman, Ellis L, Robb, Richard A
Biomedical Imaging Resource, Mayo Clinic
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Please use this identifier to cite or link to this publication: http://hdl.handle.net/1926/22
New: Prefer using the following doi: https://doi.org/10.54294/2wypjk
Published in The Insight Journal - 2005 MICCAI Open-Source Workshop.
Submitted by David Holmes on 2005-08-01T17:13:05Z.

For over two decades, the National Library of Medicine (NLM) has provided support for the collection of biomedical image data for use throughout the biomedical image, visualization and analysis community. Data collected during the Visible Human Project has been utilized to advance development of medical image research, education, and other ventures. One goal of our research has been to further diversify such image data and make it openly available to the biomedical imaging community. The approach is to provide open access to a diverse collection of biomedical image data that can be used for the development and validation of new image processing and analysis techniques. With support from NLM, over 100 datasets were incorporated into the NLM-Mayo data collection. There is variation in species, anatomy, pathology, scale, and modality. In addition to providing linical qualitymedical image data, the collection also includes newly acquired datasets of several animals, including a whole mouse with both T and R data volumes. This unique collection of data was categorized and organized into an intuitive web-based browser which allows a user to rapidly access descriptive information as well as the actual data volumes. The data collection will be made available by the NLM for distribution, vis-a-vis its Visible Human Project (VHP). Because the landscape of biomedical imaging continues to change with new, advanced image acquisition systems and techniques, continuously updating the VHP data collection seems prudent. Additional new and varied image data will be incorporated into our collection and disseminated to researchers in the medical image analysis community.