روش خودکار مرزبندی عروق و تشخیص دقیق پلاک سخت در تصاویر اولتراسوند داخل عروقی
محورهای موضوعی : مهندسی برق و کامپیوتربهشاد مهران 1 * , محمدرضا یزدچی 2 , حسین پورقاسم 3
1 - دانشگاه آزاد اسلامی، واحد نجف‌آباد
2 - دانشگاه اصفهان
3 - دانشگاه آزاد اسلامی، واحد نجف‌آباد
کلید واژه: تشخیص پلاک تصویر‌برداری اولتراسوند داخل عروقی کانتور فعال مرزبندی عروق,
چکیده مقاله :
بخش‌بندی تصویر به منظور تشخیص مرز‌های رگ امری ضروری جهت تشخیص دقیق بیماری انسداد عروق قلب به وسیله تصویر‌برداری اولتراسوند درون‌رگی (IVUS) است. در این مقاله یک روش جدید جهت بخش‌بندی تصاویر IVUS پیشنهاد شده است. ابتدا پیش‌پردازش‌هایی به منظور تبدیل تصاویر از مختصات دکارتی به مختصات قطبی، حذف کاتتر موجود در تصاویر و از بین بردن نویز اسپکل با فیلتر غیر خطی و غیر ایزوتروپیک انتشاری انجام شده است. سپس با استفاده از فیلتر گابور ویژگی‌های بافت تصاویر استخراج شده و با استفاده از مدل کانتور فعال برداری، به بخش‌بندی تصاویر و تعیین مرز عروق پرداخته شده است. با روش خوشه‌بندی فازی پلاک‌های کلسیم، مشخص و با استفاده از مدل کانتور فعال مرز دقیق پلاک‌های کلسیم استخراج شده است. این روش بر روی سی تصویر نمونه آزمایش شده و نتایج بخش‌بندی تصویر با نظر پزشک متخصص اعتبار‌سنجی شده است. اختلاف مساحت مرز داخلی رگ با نظر پزشک متخصص 236/0431/0 و اختلاف مساحت مرز خارجی رگ با نظر پزشک متخصص 723/0653/0 است. اختلاف مساحت پلاک‌های کلسیم استخراج‌شده با الگوریتم پیشنهادی در مقایسه با تصاویر بافت‌شناسی 90/5 درصد حاصل شده است.
Segmentation is necessary to determine the boundaries of the vessel. Intravascular ultrasound imaging (IVUS) is used for the diagnosis of coronary artery diseases. In this study, a new method is proposed for segmentation of IVUS images. First preprocessing is done to convert images from Cartesian coordinates to polar coordinates, remove the catheter in images and speckle noise with Nonlinear Anisotropic Diffusion Filtering. Then, texture features of an image are extracted using Gabor filter, and the image segmentation and determining the vessels boundary will be discussed using active contour without edge for vector value model. Calcium plaques have been determined using phase clustering and the exact boundary of calcium plaques is extracted using active contour model. This method has been tested on thirty images, and the results of the image segmentation have been validated by an expert. The area diffusion between the internal border and the expert’s opinion is 0.4310.236, and the area diffusion between the external border and the expert’s opinion is 0.6530.723. Area diffusion of calcium plaque extracted by the proposed algorithm compared with virtual histology images has been achieved equal to 5.90 percent.
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