کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
504130 864271 2014 11 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Segmentation of heterogeneous or small FDG PET positive tissue based on a 3D-locally adaptive random walk algorithm
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نرم افزارهای علوم کامپیوتر
پیش نمایش صفحه اول مقاله
Segmentation of heterogeneous or small FDG PET positive tissue based on a 3D-locally adaptive random walk algorithm
چکیده انگلیسی


• We propose to use the distance between adjacent nodes in place of a constant β parameter to take into account the different distances between adjacent nodes in 26 connectivity.
• To reduce the partial volume effect in PET imaging, we propose to strengthen the grouping of voxels having similar intensity by adding the likelihood of probability to each class (tumor and non-tumor).
• The accuracy in the small and heteregenous tumor segmentation is improved using our improvements.

A segmentation algorithm based on the random walk (RW) method, called 3D-LARW, has been developed to delineate small tumors or tumors with a heterogeneous distribution of FDG on PET images. Based on the original algorithm of RW [1], we propose an improved approach using new parameters depending on the Euclidean distance between two adjacent voxels instead of a fixed one and integrating probability densities of labels into the system of linear equations used in the RW. These improvements were evaluated and compared with the original RW method, a thresholding with a fixed value (40% of the maximum in the lesion), an adaptive thresholding algorithm on uniform spheres filled with FDG and FLAB method, on simulated heterogeneous spheres and on clinical data (14 patients). On these three different data, 3D-LARW has shown better segmentation results than the original RW algorithm and the three other methods. As expected, these improvements are more pronounced for the segmentation of small or tumors having heterogeneous FDG uptake.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computerized Medical Imaging and Graphics - Volume 38, Issue 8, December 2014, Pages 753–763
نویسندگان
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