Literature DB >> 10571928

On standardizing the MR image intensity scale.

L G Nyúl1, J K Udupa.   

Abstract

The lack of a standard image intensity scale in MRI causes many difficulties in image display and analysis. A two-step postprocessing method is proposed for standardizing the intensity scale in such a way that for the same MR protocol and body region, similar intensities will have similar tissue meaning. In the first step, the parameters of the standardizing transformation are "learned" from a set of images. In the second step, for each MR study these parameters are used to map their histogram into the standardized histogram. The method was tested quantitatively on 90 whole-brain studies of multiple sclerosis patients for several protocols and qualitatively for several other protocols and body regions. Measurements using mean squared difference showed that the standardized image intensities have statistically significantly (P < 0.01) more consistent range and meaning than the originals. Fixed gray level windows can be established for the standardized images and used for display without the need of per case adjustment. Preliminary results also indicate that the method facilitates improving the degree of automation of image segmentation. Magn Reson Med 42:1072-1081, 1999. Copyright 1999 Wiley-Liss, Inc.

Entities:  

Mesh:

Year:  1999        PMID: 10571928     DOI: 10.1002/(sici)1522-2594(199912)42:6<1072::aid-mrm11>3.0.co;2-m

Source DB:  PubMed          Journal:  Magn Reson Med        ISSN: 0740-3194            Impact factor:   4.668


  134 in total

1.  Estimation of tumor volume with fuzzy-connectedness segmentation of MR images.

Authors:  Gul Moonis; Jianguo Liu; Jayaram K Udupa; David B Hackney
Journal:  AJNR Am J Neuroradiol       Date:  2002-03       Impact factor: 3.825

2.  New similarity search based glioma grading.

Authors:  Katrin Haegler; Martin Wiesmann; Christian Böhm; Jessica Freiherr; Oliver Schnell; Hartmut Brückmann; Jörg-Christian Tonn; Jennifer Linn
Journal:  Neuroradiology       Date:  2011-12-14       Impact factor: 2.804

3.  Early detection of Alzheimer's disease using MRI hippocampal texture.

Authors:  Lauge Sørensen; Christian Igel; Naja Liv Hansen; Merete Osler; Martin Lauritzen; Egill Rostrup; Mads Nielsen
Journal:  Hum Brain Mapp       Date:  2015-12-21       Impact factor: 5.038

4.  Classification of suspicious lesions on prostate multiparametric MRI using machine learning.

Authors:  Deukwoo Kwon; Isildinha M Reis; Adrian L Breto; Yohann Tschudi; Nicole Gautney; Olmo Zavala-Romero; Christopher Lopez; John C Ford; Sanoj Punnen; Alan Pollack; Radka Stoyanova
Journal:  J Med Imaging (Bellingham)       Date:  2018-09-06

5.  Effects of perfusion on diffusion changes in human brain tumors.

Authors:  Alexander D Cohen; Peter S LaViolette; Melissa Prah; Jennifer Connelly; Mark G Malkin; Scott D Rand; Wade M Mueller; Kathleen M Schmainda
Journal:  J Magn Reson Imaging       Date:  2013-02-06       Impact factor: 4.813

6.  Vascular change measured with independent component analysis of dynamic susceptibility contrast MRI predicts bevacizumab response in high-grade glioma.

Authors:  Peter S LaViolette; Alex D Cohen; Melissa A Prah; Scott D Rand; Jennifer Connelly; Mark G Malkin; Wade M Mueller; Kathleen M Schmainda
Journal:  Neuro Oncol       Date:  2013-02-03       Impact factor: 12.300

7.  LONGITUDINAL INTENSITY NORMALIZATION IN THE PRESENCE OF MULTIPLE SCLEROSIS LESIONS.

Authors:  Snehashis Roy; Aaron Carass; Navid Shiee; Dzung L Pham; Peter Calabresi; Daniel Reich; Jerry L Prince
Journal:  Proc IEEE Int Symp Biomed Imaging       Date:  2013

8.  Effects of changing from non-accelerated to accelerated MRI for follow-up in brain atrophy measurement.

Authors:  Kelvin K Leung; Ian M Malone; Sebastien Ourselin; Jeffrey L Gunter; Matt A Bernstein; Paul M Thompson; Clifford R Jack; Michael W Weiner; Nick C Fox
Journal:  Neuroimage       Date:  2014-12-04       Impact factor: 6.556

9.  A collaborative resource to build consensus for automated left ventricular segmentation of cardiac MR images.

Authors:  Avan Suinesiaputra; Brett R Cowan; Ahmed O Al-Agamy; Mustafa A Elattar; Nicholas Ayache; Ahmed S Fahmy; Ayman M Khalifa; Pau Medrano-Gracia; Marie-Pierre Jolly; Alan H Kadish; Daniel C Lee; Ján Margeta; Simon K Warfield; Alistair A Young
Journal:  Med Image Anal       Date:  2013-09-13       Impact factor: 8.545

10.  Visual saliency-based active learning for prostate magnetic resonance imaging segmentation.

Authors:  Dwarikanath Mahapatra; Joachim M Buhmann
Journal:  J Med Imaging (Bellingham)       Date:  2016-02-19
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.