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Large Image Microscope Array for the Compilation of Multimodality Whole Organ Image Databases
Author(s) -
Namati Eman,
de Ryk Jessica,
Thiesse Jacqueline,
Towfic Zaid,
Hoffman Eric,
Mclennan Geoffrey
Publication year - 2007
Publication title -
the anatomical record: advances in integrative anatomy and evolutionary biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.678
H-Index - 62
eISSN - 1932-8494
pISSN - 1932-8486
DOI - 10.1002/ar.20600
Subject(s) - multimodality , microscope , computer science , image (mathematics) , artificial intelligence , database , computer graphics (images) , computer vision , information retrieval , medicine , world wide web , pathology
Three‐dimensional, structural and functional digital image databases have many applications in education, research, and clinical medicine. However, to date, apart from cryosectioning, there have been no reliable means to obtain whole‐organ, spatially conserving histology. Our aim was to generate a system capable of acquiring high‐resolution images, featuring microscopic detail that could still be spatially correlated to the whole organ. To fulfill these objectives required the construction of a system physically capable of creating very fine whole‐organ sections and collecting high‐magnification and resolution digital images. We therefore designed a large image microscope array (LIMA) to serially section and image entire unembedded organs while maintaining the structural integrity of the tissue. The LIMA consists of several integrated components: a novel large‐blade vibrating microtome, a 1.3 megapixel peltier cooled charge‐coupled device camera, a high‐magnification microscope, and a three axis gantry above the microtome. A custom control program was developed to automate the entire sectioning and automated raster‐scan imaging sequence. The system is capable of sectioning unembedded soft tissue down to a thickness of 40 μm at specimen dimensions of 200 × 300 mm to a total depth of 350 mm. The LIMA system has been tested on fixed lung from sheep and mice, resulting in large high‐quality image data sets, with minimal distinguishable disturbance in the delicate alveolar structures. Anat Rec 290:1377‐1387, 2007. © 2007 Wiley‐Liss, Inc.