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Delineation of breast lesions in ultrasound images using Level-set method

استخدام مجموعة السويات في تحديد حافات الكتل في الثدي ضمن صور الأمواج فوق الصوتية

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 Publication date 2014
and research's language is العربية
 Created by Shamra Editor




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Breast cancer is the second leading cause of death of women in the world. The early detection gives a better chance to cure it. Physicians diagnose breast tumors by analyzing the characteristics of the lesion in ultrasound images. Shape data, provided by a tumor contour, is important to physicians in making diagnostic decisions. However, due to the increasing use of technology in medicine, a computer aided detection systems (CAD) have been built to help the expert. This research focuses on using a level-set method as an effective lesion segmentation method for breast ultrasound images. By applying non-local means filter on image, the unwanted speckle noise will be removed and the image's important details will be preserved. Then the initial contours are sketched using the GUI in order to apply level-set method which delineates the contour of the lesion in breast ultrasound image. The proposed method was found to determine the breast tumor contours that are very similar to manual-sketched contours (about 96%).


Artificial intelligence review:
Research summary
يتناول هذا البحث مشكلة الكشف المبكر عن سرطان الثدي باستخدام صور الأمواج فوق الصوتية. يهدف إلى تطوير نظام بمساعدة الحاسوب لتحديد حافات الكتل في هذه الصور باستخدام طريقة مجموعة السويات. يتضمن النظام إزالة الضجيج من الصور باستخدام مرشح وسطي لا محلي، ثم تحديد الحافات مبدئياً لتقوم بعدها طريقة مجموعة السويات بتحديد حافات الكتل بدقة. أظهرت النتائج تطابقاً بنسبة 96% بين الحافات المحددة بالبرنامج وتلك التي رسمها اختصاصي الأشعة، مما يشير إلى فعالية النظام ويفتح الباب أمام تطبيقه في العيادات والمراكز الطبية. تم تنفيذ البحث باستخدام لغة MATLAB على صور لأشخاص تتراوح أعمارهم بين 22 و70 عاماً، وتمت معالجة الصور وإزالة الضجيج منها قبل تطبيق خوارزمية التجزئة. أظهرت النتائج أن النظام قادر على تحديد حافات الكتل بدقة عالية، مما يساعد في تحسين دقة التشخيص والكشف المبكر عن سرطان الثدي.
Critical review
دراسة نقدية: يعد هذا البحث خطوة مهمة في مجال الكشف المبكر عن سرطان الثدي باستخدام تقنيات الحوسبة، إلا أن هناك بعض النقاط التي يمكن تحسينها. أولاً، العينة المستخدمة في الدراسة صغيرة نسبياً (10 مرضى فقط)، مما قد يؤثر على تعميم النتائج. ثانياً، لم يتم اختبار النظام على أنواع أخرى من الصور الطبية مثل التصوير بالرنين المغناطيسي أو التصوير المقطعي، مما قد يحد من تطبيقه. ثالثاً، الاعتماد الكبير على MATLAB قد يكون عائقاً في تحويل النظام إلى تطبيق عملي يمكن استخدامه في العيادات. وأخيراً، لم يتم مناقشة تأثير العوامل البيئية أو التقنية الأخرى التي قد تؤثر على دقة النظام.
Questions related to the research
  1. ما الهدف الرئيسي من البحث؟

    الهدف الرئيسي هو تطوير نظام بمساعدة الحاسوب لتحديد حافات الكتل في صور الأمواج فوق الصوتية للثدي باستخدام طريقة مجموعة السويات.

  2. ما هي نسبة التطابق بين الحافات المحددة بالبرنامج وتلك التي رسمها اختصاصي الأشعة؟

    نسبة التطابق بلغت 96%.

  3. ما هي التقنية المستخدمة لإزالة الضجيج من الصور؟

    تم استخدام مرشح وسطي لا محلي لإزالة الضجيج من الصور.

  4. ما هي اللغة البرمجية المستخدمة في تنفيذ البحث؟

    تم استخدام لغة MATLAB لتنفيذ البحث.


References used
Guo Y., (2010), " Computer-aided detection of breast cancer using ultrasound images", Utah state university, Logan, UT ,US,pages:18- 258
Gomez W., Leija L., Pereira W. C. A., Infantosi A. F. C. ,(2009), “Semiautomatic contour detection of breast lesions in ultrasonic images with morphological operators and average radial derivative function ” International Congress on Ultrasonics, Universidad de Santiago de Chile, ScienceDirect Physics Procedia Vol:3, No.1 Pages:373-380
Huang Y. and Chen D. ,(2004), “Watershed segmentation for breast tumor in 2-D Sonography” Department of Computer Science and Information Engineering, Tunghai University, Taichung, Taiwan. Ultrasound in Med. & Biol., Vol. 30, No. 5, Pages:625-636
Grau V. et al,(2004)," Improved watershed transform for medical image segmentation using prior information.", IEEE Transactions Medical Imagining Vol: 23 ,No. 4 ,Pages:447-458
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