Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
A dual approach for minimizing false lesion classifications on magnetic resonance images
62
Zitationen
3
Autoren
1997
Jahr
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%.
Ähnliche Arbeiten
A Computational Approach to Edge Detection
1986 · 28.995 Zit.
Textural Features for Image Classification
1973 · 22.413 Zit.
Automated Anatomical Labeling of Activations in SPM Using a Macroscopic Anatomical Parcellation of the MNI MRI Single-Subject Brain
2002 · 16.742 Zit.
Normalized cuts and image segmentation
2000 · 15.667 Zit.
Nonlinear total variation based noise removal algorithms
1992 · 15.618 Zit.