کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6920576 | 1447924 | 2018 | 31 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
3-D segmentation of lung nodules using hybrid level sets
ترجمه فارسی عنوان
سه بعدی سازی گره های ریه با استفاده از مجموعه های سطح هیبریدی
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کلمات کلیدی
ترکیبی سطح مجموعه، خطوط فعال، تقسیم بند نود، مدل غیر قابل انطباق،
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
نرم افزارهای علوم کامپیوتر
چکیده انگلیسی
Lung nodule segmentation in CT images and its subsequent volume analysis can help determine the malignancy status of a lung nodule. While several efficient segmentation schemes have been proposed, only a few studies evaluated the segmentation's performance for large nodules. In this research, we contribute a semi-automatic system which is capable of performing robust 3-D segmentations on both small and large nodules with good accuracy. The target CT volume is de-noised with an anisotropic diffusion filter and a region of interest is selected around the target nodule on a reference slice. The proposed model performs nodule segmentation by incorporating a mean intensity based threshold in Geodesic Active Contour model in level sets. We also devise an adaptive technique using image intensity histogram to estimate the desired mean intensity of the nodule. The proposed system is validated on both lung nodules and phantoms collected from publicly available diverse databases. Quantitative and visual comparative analysis of the proposed work with the Chan-Vese algorithm and statistic active contour model of 3D Slicer platform is also presented. The resulting mean spatial overlap between segmented nodules and reference nodules is 0.855, the mean volume bias is 0.10±0.2 ml and the algorithm repeatability is 0.060â¯ml. The achieved results suggest that the proposed method can be used for volume estimations of small as well as large-sized nodules.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computers in Biology and Medicine - Volume 96, 1 May 2018, Pages 214-226
Journal: Computers in Biology and Medicine - Volume 96, 1 May 2018, Pages 214-226
نویسندگان
Hina Shakir, Tariq Mairaj Rasool Khan, Haroon Rasheed,