Micro-CT based quantification of non-mineralized tissue on cultured hydroxyapatite scaffolds

Amanda Hilldore, Abigail Wojtowicz, Amy Wagoner Johnson

Research output: Contribution to journalArticlepeer-review


An improved method to determine material volumes from microcomputed tomography (micro-CT) data is presented. In particular, the method can account for materials with significantly overlapping peaks and small volumes. The example case is a hydroxyapatife scaffold cultured with osteoprogenitor cells. The histogram obtained from the micro-CT data is decomposed into a Gaussian attenuation distribution for each material in the sample, including scaffold, pore and surface tissue, and background. This is done by creating a training set of attenuation data to find initial parameters and then using a nonlinear curve fit, which produced R2 values greater than 0.998. To determine the material volumes, the curves that simulated each material are integrated, allowing small volume fractions to be accurately quantified. Thresholds for visualizing the samples are chosen based on volume fractions of the Gaussian curves. Additionally, the use of dual-material regions helps accurately visualize tissue on the scaffold, which is otherwise difficult because of the large volume fraction of scaffold. Finally, the curve integration method is compared with Bayesian estimation and intersection thresholding methods. The pore tissue is not represented at all by the Bayesian estimation, and the intersection thresholding method is less accurate than the curve integration method.

Original languageEnglish (US)
Pages (from-to)1012-1021
Number of pages10
JournalJournal of Biomedical Materials Research - Part A
Issue number4
StatePublished - Sep 15 2007


  • Bone tissue engineering
  • Image analysis
  • Micro-computed tomography
  • Segmentation

ASJC Scopus subject areas

  • Biomedical Engineering
  • Biomaterials


Dive into the research topics of 'Micro-CT based quantification of non-mineralized tissue on cultured hydroxyapatite scaffolds'. Together they form a unique fingerprint.

Cite this