Knee cartilage: Efficient and reproducible segmentation on high-spatial-resolution MR images with the semiautomated graph-cut algorithm method

Hackjoon Shim, Samuel Chang, Cheng Tao, Jin Hong Wang, C. Kent Kwoh, Kyongtae T. Bae

Research output: Contribution to journalArticle

56 Scopus citations

Abstract

This HIPAA-compliant study was exempt from institutional review board approval because the 10 image data sets were deidentified in the Osteoarthritis Initiative database, and they were processed and analyzed without any clinical information being accessed. The purpose of this study was to prospectively evaluate the efficiency and reproducibility of the semiautomated graph-cut method (SA method) in the segmentation of knee cartilage and to compare its performance with that of the conventional manual delineation segmentation method (M method). Two radiologists independently performed segmentation with each method in two separate sessions: They performed the M method (M1 and M2 for the first and second sessions, respectively) for every third section and the SA method (SA1 and SA2 for the first and second sessions, respectively) for every section. The SA method was significantly more efficient (mean processing time, 53 minutes vs 156 minutes for SA1 vs M1 and 53 minutes vs 118 minutes for SA2 vs M2; P < .001) and reproducible (mean volume overlap, 94.3% vs 87.8% for the SA method vs the M method; P < .001) than the M method.

Original languageEnglish (US)
Pages (from-to)548-556
Number of pages9
JournalRadiology
Volume251
Issue number2
DOIs
StatePublished - May 1 2009
Externally publishedYes

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging

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