کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6883328 | 1444171 | 2018 | 15 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Carotid wall segmentation in longitudinal ultrasound images using structured random forest
ترجمه فارسی عنوان
جداسازی دیواره کاروتید در تصاویر سونوگرافی طولی با استفاده از جنگل تصادفی ساختار یافته
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
شبکه های کامپیوتری و ارتباطات
چکیده انگلیسی
Edge detection is a primary image processing technique used for object detection, data extraction, and image segmentation. Recently, edge-based segmentation using structured classifiers has been receiving increasing attention. The intima media thickness (IMT) of the common carotid artery is mainly used as a primitive indicator for the development of cardiovascular disease. For efficient measurement of the IMT, we propose a fast edge-detection technique based on a structured random forest classifier. The accuracy of IMT measurement is degraded owing to the speckle noise found in carotid ultrasound images. To address this issue, we propose the use of a state-of-the-art denoising method to reduce the speckle noise, followed by an enhancement technique to increase the contrast. Furthermore, we present a novel approach for an automatic region of interest extraction in which a pre-trained structured random forest classifier algorithm is applied for quantifying the IMT. The proposed method exhibits IMTmeanâ¯Â±â¯ standard deviation of 0.66mmâ¯Â±â¯0.14, which is closer to the ground truth value 0.67mmâ¯Â±â¯0.15 as compared to the state-of-the-art techniques.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computers & Electrical Engineering - Volume 69, July 2018, Pages 753-767
Journal: Computers & Electrical Engineering - Volume 69, July 2018, Pages 753-767
نویسندگان
Nagaraj Y., Asha C.S., Hema Sai Teja A., A.V. Narasimhadhan,