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Automated analysis of contrast enhancement in breast MRI lesions using mean shift clustering for ROI selection
Author(s) -
Stoutjesdijk Mark J.,
Veltman Jeroen,
Huisman Henkjan,
Karssemeijer Nico,
Barentsz Jelle O.,
Blickman Johan G.,
Boetes Carla
Publication year - 2007
Publication title -
journal of magnetic resonance imaging
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.563
H-Index - 160
eISSN - 1522-2586
pISSN - 1053-1807
DOI - 10.1002/jmri.21026
Subject(s) - quartile , medicine , cluster analysis , breast mri , confidence interval , nuclear medicine , receiver operating characteristic , repeatability , radiology , pattern recognition (psychology) , breast cancer , mathematics , computer science , artificial intelligence , mammography , statistics , cancer
Abstract Purpose To evaluate a new method for automated determination of a region of interest (ROI) for the analysis of contrast enhancement in breast MRI. Materials and Methods Mean shift multidimensional clustering (MS‐MDC) was employed to divide 92 lesions into several spatially contiguous clusters each, based on multiple enhancement parameters. The ROIs were defined as the clusters with the highest probability of malignancy. The performance of enhancement analysis within these ROIs was estimated using the area under the receiver operator characteristic curve (AUC), and compared against a radiologist's final assessment and a classifier using histogram analysis (HA). For HA, the first, second, and third quartiles were evaluated. Results MS‐MDC resulted in AUC = 0.88 with a 95% confidence interval (CI) of 0.81–0.95. The AUC for the radiologist's assessment was 0.93 (95%CI = 0.87–0.97). Best HA performance was found using the first quartile, with AUC = 0.79 (95%CI = 0.69–0.88). There was no significant difference between MS‐MDC and the radiologist ( P = 0.40). The improvement of MS‐MDC over HA was significant ( P = 0.018). Conclusion Mean shift clustering followed by automated selection of the most suspicious cluster resulted in accurate ROIs in breast MRI lesions. J. Magn. Reson. Imaging 2007;26:606–614. © 2007 Wiley‐Liss, Inc.