کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
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557624 | 874752 | 2011 | 10 صفحه PDF | دانلود رایگان |

Medical image segmentation and registration problems based on magnetic resonance imaging are frequently disturbed by the intensity inhomogeneity or intensity non-uniformity (INU) of the observed images. Most compensation techniques have serious difficulties at high amplitudes of INU. This study proposes a multiple stage hybrid c-means clustering approach to the estimation and compensation of INU, by modeling it as a slowly varying additive or multiplicative noise. The slowly varying behavior of the estimated inhomogeneity field is assured by a context sensitive smoothing filter based on a morphological criterion. The qualitative and quantitative evaluation using 2-D synthetic phantoms and real T1-weighted MR images place the proposed methodology among the most accurate segmentation techniques in the presence of high-magnitude inhomogeneity.
Journal: Biomedical Signal Processing and Control - Volume 6, Issue 1, January 2011, Pages 3–12