کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
383109 660802 2016 11 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Smoothing of ultrasound images using a new selective average filter
ترجمه فارسی عنوان
صاف کردن تصاویر سونوگرافی با استفاده از یک فیلتر متوسط انتخابی جدید
کلمات کلیدی
پردازش تصویر؛ صاف کردن نویز لکه ؛ فیلتر انتخابی؛ تصویربرداری پزشکی؛ حفره لگن زن
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
چکیده انگلیسی


• A new method is proposed to perform selective smoothing of images affected by speckle noise.
• A new smoothing criterion is defined for the average smoothing filter.
• The convolution window of the smoothing filter is adjustable.
• The method is evaluated using real ultrasound medical images based on image quality metrics.
• The proposed method produced better results than the current methods evaluated.

Ultrasound images are strongly affected by speckle noise making visual and computational analysis of the structures more difficult. Usually, the interference caused by this kind of noise reduces the efficiency of extraction and interpretation of the structural features of interest. In order to overcome this problem, a new method of selective smoothing based on average filtering and the radiation intensity of the image pixels is proposed. The main idea of this new method is to identify the pixels belonging to the borders of the structures of interest in the image, and then apply a reduced smoothing to these pixels, whilst applying more intense smoothing to the remaining pixels. Experimental tests were conducted using synthetic ultrasound images with speckle noisy added and real ultrasound images from the female pelvic cavity. The new smoothing method is able to perform selective smoothing in the input images, enhancing the transitions between the different structures presented. The results achieved are promising, as the evaluation analysis performed shows that the developed method is more efficient in removing speckle noise from the ultrasound images compared to other current methods. This improvement is because it is able to adapt the filtering process according to the image contents, thus avoiding the loss of any relevant structural features in the input images.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Expert Systems with Applications - Volume 60, 30 October 2016, Pages 96–106
نویسندگان
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