کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
10712578 | 1025204 | 2014 | 13 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Image-guided regularization level set evolution for MR image segmentation and bias field correction
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موضوعات مرتبط
مهندسی و علوم پایه
فیزیک و نجوم
فیزیک ماده چگال
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: Image-guided regularization level set evolution for MR image segmentation and bias field correction Image-guided regularization level set evolution for MR image segmentation and bias field correction](/preview/png/10712578.png)
چکیده انگلیسی
Magnetic resonance (MR) image segmentation is a crucial step in surgical and treatment planning. In this paper, we propose a level-set-based segmentation method for MR images with intensity inhomogeneous problem. To tackle the initialization sensitivity problem, we propose a new image-guided regularization to restrict the level set function. The maximum a posteriori inference is adopted to unify segmentation and bias field correction within a single framework. Under this framework, both the contour prior and the bias field prior are fully used. As a result, the image intensity inhomogeneity can be well solved. Extensive experiments are provided to evaluate the proposed method, showing significant improvements in both segmentation and bias field correction accuracies as compared with other state-of-the-art approaches.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Magnetic Resonance Imaging - Volume 32, Issue 1, January 2014, Pages 71-83
Journal: Magnetic Resonance Imaging - Volume 32, Issue 1, January 2014, Pages 71-83
نویسندگان
Lingfeng Wang, Chunhong Pan,