Knee cartilage: efficient and reproducible segmentation on high-spatial-resolution MR images with the semiautomated graph-cut algorithm method.
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.
Shim
Hackjoon
H
Department of Radiology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15213, USA.
Chang
Samuel
S
Tao
Cheng
C
Wang
Jin-Hong
JH
Kwoh
C Kent
CK
Bae
Kyongtae T
KT
D000465:Algorithms; D001185:Artificial Intelligence; D002358:Cartilage, Articular / Q000473:pathology*; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D007719:Knee Joint / Q000473:pathology*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D020370:Osteoarthritis, Knee / Q000473:pathology*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity