= Michael J. Moore
{c}
\b[Michael J. Moore] is a coauthor of the 2004 quantitative study of interconnectivity in porous biodegradable scaffolds. The primary institutional publication record verifies his full given name and the paper’s use of <micro-computed tomography> to assess scaffold architecture.<Quantitative analysis of interconnectivity of porous biodegradable scaffolds with micro-computed tomography by Michael J. Moore and others>[University publication record and primary indexed abstract]{ref}
The scientific problem is that <porosity> alone does not determine access through a <tissue-engineering scaffold>. Isolated cavities and a connected channel can contribute the same void volume while supporting very different transport. A three-dimensional image allows the solid and void regions to be segmented and their communicating pathways examined. The analysis therefore connects imaging to a property relevant to <tissue engineering>, rather than treating an image as only a visual illustration.
For an illustrative segmentation, suppose 36 of 40 units of void volume are connected to the chosen exterior boundary. The accessible fraction is $36/40=0.90$. If a different image threshold gives 39 connected units out of 44 void units, the result is about $0.886$. Neither number is a result from Moore’s paper; they show why reporting the threshold, image resolution and boundary definition is part of interpreting a connectivity measurement. A flow experiment supplies complementary evidence about the resulting <intrinsic permeability>.
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