Optimal segmentation of microcomputed tomographic images of porous tissue-engineering scaffolds

Srinivasan Rajagopalan, Lichun Lu, Michael J Yaszemski, Richard A. Robb

Research output: Contribution to journalArticle

52 Citations (Scopus)

Abstract

The morphometric properties of the porous tissue-engineering scaffolds play a dominant role in the initial cell attachment and subsequent tissue regeneration. These properties can be derived nondestructively with the use of quantitative analysis of high-resolution microcomputed tomography (μCT) imaging of scaffolds. Accurate segmentation of these acquired images into solid and porous subspaces is critical to the integrity of morphometric analysis. The absence of a single image-processing technique to provide such accurate separability immune to all the intricacies of the acquired data makes this seemingly simple task significantly error prone. Consequently, an optimal segmentation has to be selected by ranking the segmentations produced by a multiplicity of methods. This article proposes a robust, easy-to-implement, unambiguous, signal-processing-based, ground-truth-free, segmentation rating metric that correlates with visual acuity. With the use of this metric it is possible, for the first time, to threshold the data with a wide range of techniques and select automatically the technique that best delineates the acquired image. The proposed solution has been extensively tested on μCT images of scaffolds fabricated with biodegradable poly (propylene fumarate) (PPF) with the use of a solvent casting particulate leaching process. The approaches proposed and the results obtained may have profound implications for accurate image-based characterization of tissue-engineering scaffolds.

Original languageEnglish (US)
Pages (from-to)877-887
Number of pages11
JournalJournal of Biomedical Materials Research - Part A
Volume75
Issue number4
DOIs
StatePublished - Dec 15 2005

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Tissue Scaffolds
Scaffolds (biology)
Tissue engineering
Scaffolds
Tissue regeneration
Leaching
Tomography
Polypropylenes
Signal processing
Casting
Image processing
Imaging techniques
Chemical analysis
poly(propylene fumarate)

Keywords

  • Image segmentation, validation
  • Microcomputed tomography (μCT)
  • Porous scaffolds
  • Tissue engineering

ASJC Scopus subject areas

  • Biomedical Engineering
  • Biomaterials

Cite this

Optimal segmentation of microcomputed tomographic images of porous tissue-engineering scaffolds. / Rajagopalan, Srinivasan; Lu, Lichun; Yaszemski, Michael J; Robb, Richard A.

In: Journal of Biomedical Materials Research - Part A, Vol. 75, No. 4, 15.12.2005, p. 877-887.

Research output: Contribution to journalArticle

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