title: A dual approach for minimizing false lesion classifications on magnetic resonance images.
abstract: Segmentation methods based on dual-echo MR images are generally prone to significant false lesion classifications. We have minimized these false classifications by (1) improving the lesion-to-tissue contrast on MR images by developing a fast spin-echo sequence that incorporates both cerebrospinal fluid signal attenuation and magnetization transfer contrast and (2) including information from MR flow images. Studies on patients with multiple sclerosis indicate that this dual approach to tissue segmentation reduces the volume of false lesion classifications by an average of 87%.
authors.affiliation: Department of Radiology, University of Texas Medical School at Houston, 77030, USA.
authors.forename: B J
authors.initials: BJ
authors.lastname: Bedell
authors.forename: P A
authors.initials: PA
authors.lastname: Narayana
authors.forename: J S
authors.initials: JS
authors.lastname: Wolinsky
mesh_terms: D000465:Algorithms; D001921:Brain / Q000473:pathology*; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008279:Magnetic Resonance Imaging / Q000379:methods*; D009103:Multiple Sclerosis / Q000473:pathology*