Edward A. Ashton
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Research Interests
Edward A. Ashton has a total of 5 co-authors. Here are the top co-authors by number of shared publications:
Andrew Goodman
Department of Neurology, University of Rochester Medical Center, Rochester, New York
1 shared publicationChihiro Takahashi
Department of Radiology, University of Rochester Medical Center, Rochester, New York
1 shared publicationMichel J. Berg
Department of Neurology, University of Rochester Medical Center, Rochester, New York
1 shared publicationSaara Totterman
Department of Radiology, University of Rochester Medical Center, Rochester, New York
1 shared publicationSven Ekholm
Department of Radiology, University of Rochester Medical Center, Rochester, New York
1 shared publication
Latest Publications
- 19 February 2003
- Published by Wiley in Journal of Magnetic Resonance Imaging
- Vol. 17 (3) , 300-308
Accuracy and reproducibility of manual and semiautomated quantification of MS lesions by MRI
Purpose: To evaluate the accuracy, reproducibility, and speed of two semiautomated methods for quantifying total white matter lesion burden in multiple sclerosis (MS) patients with respect to manual tracing and to other methods presented in recent literature.Materials and Methods: Two methods involving the use of MRI for semiautomated quantification of total lesion burden in MS patients were examined. The first method, geometrically constrained region growth (GEORG), requires user specification of lesion location. The second technique, directed multispectral segmentation (DMSS), requires only the location of a single exemplar lesion. Test data sets included both clinical MS data and MS brain phantoms.Results: The mean processing times were 60 minutes for manual tracing, 10 minutes for region growth, and 3 minutes for directed segmentation. Intra‐ and interoperator coefficients of variation (CVs) were 5.1% and 16.5% for manual tracing, 1.4% and 2.3% for region growth, and 1.5% and 5.2% for directed segmentation. The average deviations from manual tracing were 9% for region growth and 5.7% for directed segmentation.Conclusion: Both semiautomated methods were shown to have a significant advantage over manual tracing in terms of speed and precision. The accuracy of both methods was acceptable, given the high variability of the manual results. J. Magn. Reson. Imaging 2003;17:300–308.
- 19 February 2003
- Published by Wiley in Journal of Magnetic Resonance Imaging
- Vol. 17 (3) , 300-308
Accuracy and reproducibility of manual and semiautomated quantification of MS lesions by MRI
Purpose: To evaluate the accuracy, reproducibility, and speed of two semiautomated methods for quantifying total white matter lesion burden in multiple sclerosis (MS) patients with respect to manual tracing and to other methods presented in recent literature.Materials and Methods: Two methods involving the use of MRI for semiautomated quantification of total lesion burden in MS patients were examined. The first method, geometrically constrained region growth (GEORG), requires user specification of lesion location. The second technique, directed multispectral segmentation (DMSS), requires only the location of a single exemplar lesion. Test data sets included both clinical MS data and MS brain phantoms.Results: The mean processing times were 60 minutes for manual tracing, 10 minutes for region growth, and 3 minutes for directed segmentation. Intra‐ and interoperator coefficients of variation (CVs) were 5.1% and 16.5% for manual tracing, 1.4% and 2.3% for region growth, and 1.5% and 5.2% for directed segmentation. The average deviations from manual tracing were 9% for region growth and 5.7% for directed segmentation.Conclusion: Both semiautomated methods were shown to have a significant advantage over manual tracing in terms of speed and precision. The accuracy of both methods was acceptable, given the high variability of the manual results. J. Magn. Reson. Imaging 2003;17:300–308.