The Digital Fish Library: using MRI to digitize, database, and document the morphological diversity of fish

PLoS One. 2012;7(4):e34499. doi: 10.1371/journal.pone.0034499. Epub 2012 Apr 6.

Abstract

Museum fish collections possess a wealth of anatomical and morphological data that are essential for documenting and understanding biodiversity. Obtaining access to specimens for research, however, is not always practical and frequently conflicts with the need to maintain the physical integrity of specimens and the collection as a whole. Non-invasive three-dimensional (3D) digital imaging therefore serves a critical role in facilitating the digitization of these specimens for anatomical and morphological analysis as well as facilitating an efficient method for online storage and sharing of this imaging data. Here we describe the development of the Digital Fish Library (DFL, http://www.digitalfishlibrary.org), an online digital archive of high-resolution, high-contrast, magnetic resonance imaging (MRI) scans of the soft tissue anatomy of an array of fishes preserved in the Marine Vertebrate Collection of Scripps Institution of Oceanography. We have imaged and uploaded MRI data for over 300 marine and freshwater species, developed a data archival and retrieval system with a web-based image analysis and visualization tool, and integrated these into the public DFL website to disseminate data and associated metadata freely over the web. We show that MRI is a rapid and powerful method for accurately depicting the in-situ soft-tissue anatomy of preserved fishes in sufficient detail for large-scale comparative digital morphology. However these 3D volumetric data require a sophisticated computational and archival infrastructure in order to be broadly accessible to researchers and educators.

Publication types

  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Animals
  • Databases, Factual / statistics & numerical data*
  • Fishes / anatomy & histology*
  • Image Processing, Computer-Assisted
  • Internet
  • Libraries, Digital / statistics & numerical data*
  • Magnetic Resonance Imaging