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Cardiac histo-anatomical structure is a key determinant in all aspects of cardiac function. While some characteristics of micro- and macrostructure can be quantified using non-invasive imaging methods, histology is still the modality that provides the best combination of resolution and identification of cellular/sub-cellular substrate identities. The main limitation of histology is that it does not provide inherently consistent three-dimensional (3D) volume representations. This paper presents methods developed within our group to reconstruct 3D histological datasets. It includes the use of high-resolution MRI and block-face images to provide supporting volumetric datasets to guide spatial reintegration of 2D histological section data, and presents recent developments in sample preparation, data acquisition, and image processing. © 2012 Springer-Verlag.

Original publication




Journal article


Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Publication Date



7605 LNBI


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