Multi-site validation of image analysis methods - Assessing intra and inter-site variability

Martin A. Styner, H. Cecil Charles, Jin Park, Guido Gerig

Research output: Contribution to journalArticlepeer-review


In this work, we present a unique set of 3D MRI brain data that is appropriate for testing the intra and inter-site variability of image analysis methods. A single subject was scanned two times within a 24 hour time window each at five different MR sites over a period of six weeks using GE and Phillips 1.5 T scanners. The imaging protocol included T1 weighted, Proton Density and T2 weighted images. We applied three quantitative image analysis methods and analyzed their results via the coefficients of variability (COV) and the intra correlation coefficient. The tested methods include two multi-channel tissue segmentation techniques based on an anatomically guided manual seeding and an atlas-based seeding. The third tested method was a single-channel semi-automatic segmentation of the hippocampus. The results show that the outcome of image analysis methods varies significantly for images from different sites and scanners. With the exception of total brain volume, which shows consistent low variability across all images, the COV's were clearly larger between sites than within sites. Also, the COV's between sites with different scanner types are slightly larger than between sites with the same scanner type. The presented existence of a significant inter-site variability requires adaptations in image methods to produce repeatable measurements. This is especially of importance in multi-site clinical research.

Original languageEnglish (US)
Pages (from-to)278-286
Number of pages9
JournalProceedings of SPIE - The International Society for Optical Engineering
Volume4684 I
StatePublished - 2002


  • MRI
  • Multi-site
  • Quantitative Image Analysis
  • Reliability
  • Validation

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering


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