Measuring the Effect of Filters on Segmentation of Developmental Dysplasia of the Hip
العنوان: | Measuring the Effect of Filters on Segmentation of Developmental Dysplasia of the Hip |
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المؤلفون: | Hasan Erdinc Kocer, Mesut Sivri, Kerim Kürşat Çevik, Mustafa Koplay |
المساهمون: | Selçuk Üniversitesi, [Kocer, Hasan Erdinc] Selcuk Univ, Tech Educ Fac, Dept Elect & Comp Educ, Konya, Turkey -- [Cevik, Kerim Kursat] Nigde Univ, Bor Vocat High Sch, Dept Comp Programming, Nigde, Turkey -- [Sivri, Mesut -- Koplay, Mustafa] Selcuk Univ, Fac Med, Dept Radiol, Konya, Turkey, 0-Belirlenecek |
المصدر: | Iranian Journal of Radiology |
سنة النشر: | 2015 |
مصطلحات موضوعية: | medicine.medical_specialty, Image quality, Image Processing, 0206 medical engineering, Image processing, 02 engineering and technology, symbols.namesake, 0202 electrical engineering, electronic engineering, information engineering, Medicine, Radiology, Nuclear Medicine and imaging, Ultrasonography, business.industry, Physics, Speckle noise, Pattern recognition, Salt-and-pepper noise, Filter (signal processing), 020601 biomedical engineering, Peak signal-to-noise ratio, Surgery, Noise, Gaussian noise, symbols, Developmental Dysplasia of the Hip, 020201 artificial intelligence & image processing, Artificial intelligence, business, Filtering |
الوصف: | WOS: 000384820700004 PubMed ID: 27853489 Background: Developmental dysplasia of the hip(DDH) can be detected with ultrasonography (USG) images. However, the accuracy of this method is dependent on the skill of the radiologist. Radiologists measure the hip joint angles without computer-based diagnostic systems. This causes mistakes in the diagnosis of DDH. Objectives: In this study, we aimed to automate segmentation of DDH ultrasound images in order to make it convenient for radiologic diagnosis by this recommended system. Materials and Methods: This experiment consisted of several steps, in which pure DDH and various noise-added images were formed. Then, seven different filters (mean, median, Gaussian, Wiener, Perona and Malik, Lee, and Frost) were applied to the images, and the output images were evaluated. The study initially evaluated the filter implementations on the pure DDH images. Then, three different noise functions, speckle, salt and pepper, and Gaussian, were applied to the images and the noisy images were filtered. In the last part, the peak signal to noise ratio (PSNR) and mean square error (MSE) values of the filtered images were evaluated. PSNR and MSE distortion measurements were applied to determine the image qualities of the original image and the output image. As a result, the differences in the results of different noise removal filters were observed. Results: The best results of PSNR values obtained in filtering were: Wiener (43.49), Perona and Malik (27.68), median (40.60) and Lee (35.35) for the noise functions of raw images, Gaussian noise added, salt and pepper noise added and speckle noise added images, respectively. After the segmentation process, it was seen that applying filtering to DDH USG images had low influence. We correctly segmented the ilium zone with the active contour model. Conclusion: Various filters are needed to improve the image quality. In this study, seven different filters were implemented and investigated on both noisy and noise-free images. |
تدمد: | 1735-1065 0003-8482 2785-3489 |
URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e67c75db972a34ec1dc06417e57c5f3b https://pubmed.ncbi.nlm.nih.gov/27853489 |
Rights: | OPEN |
رقم الانضمام: | edsair.doi.dedup.....e67c75db972a34ec1dc06417e57c5f3b |
قاعدة البيانات: | OpenAIRE |
تدمد: | 17351065 00038482 27853489 |
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