کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
8130920 | 1523230 | 2018 | 8 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Semi-Automated Segmentation of the Tumor Vasculature in Contrast-Enhanced Ultrasound Data
ترجمه فارسی عنوان
نیمه اتوماتیک تقسیم محوری تومور در داده های اولتراسوند پیشرفته کنتراست
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کلمات کلیدی
سونوگرافی، میکروبابابل، تومور، میکروواسکولاتور،
موضوعات مرتبط
مهندسی و علوم پایه
فیزیک و نجوم
آکوستیک و فرا صوت
چکیده انگلیسی
The vascular architecture in tumors contains relevant information for tumor classification and evaluation of therapy responses. To develop a reliable and user-independent analysis tool, a foreground detection algorithm was combined with a maximum-intensity projection to obtain a high signal-to-noise image from contrast-enhanced B-mode data sets, enabling vessel segmentation by thresholding. Parameters describing the density of the vascular network, the number of vessels and the number of branches were extracted. The highly angiogenic A431 tumors had a relative blood volume of 49%, a mean pixel distance to the next vessel of 1.8â±â0.3 px, 51â±â29 individual vessels and 478â±â184 branching points, whereas the more mature and heterogeneous vascularized human epithelial ovarian carcinoma (MLS) and A549 tumors had values of 30%, 3.7â±â2.7 px, 65â±â12 and 220â±â159, and 13%, 7.4â±â2 px, 31â±â9 and 59â±â40, respectively. Thus, our semi-automated analysis method enables the extraction of quantitative vascular features that may help to simplify and standardize tumor characterization.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Ultrasound in Medicine & Biology - Volume 44, Issue 8, August 2018, Pages 1910-1917
Journal: Ultrasound in Medicine & Biology - Volume 44, Issue 8, August 2018, Pages 1910-1917
نویسندگان
Benjamin Theek, Tatjana Opacic, Twan Lammers, Fabian Kiessling,