3D Shape-Weighted Level Set Method for Breast MRI 3D Tumor Segmentation
المؤلفون المشاركون
Yang, Sheng-Chih
Huang, Chieh-Ling
Wang, Chuin-Mu
المصدر
Journal of Healthcare Engineering
العدد
المجلد 2018، العدد 2018 (31 ديسمبر/كانون الأول 2018)، ص ص. 1-15، 15ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2018-06-13
دولة النشر
مصر
عدد الصفحات
15
التخصصات الرئيسية
الملخص EN
Three-dimensional (3D) medical image segmentation is used to segment the target (a lesion or an organ) in 3D medical images.
Through this process, 3D target information is obtained; hence, this technology is an important auxiliary tool for medical diagnosis.
Although some methods have proved to be successful for two-dimensional (2D) image segmentation, their direct use in the 3D case has been unsatisfactory.
To obtain more precise tumor segmentation results from 3D MR images, in this paper, we propose a method known as the 3D shape-weighted level set method (3D-SLSM).
The proposed method first converts the LSM, which is superior with respect to 2D image segmentation, into a 3D algorithm that is suitable for overall calculations in 3D image models, and which improves the efficiency and accuracy of calculations.
A 3D shape-weighted value is then added for each 3D-SLSM iterative process according to the changes in volume.
Besides increasing the convergence rate and eliminating background noise, this shape-weighted value also brings the segmented contour closer to the actual tumor margins.
To perform a quantitative analysis of 3D-SLSM and to examine its feasibility in clinical applications, we have divided our experiments into computer-simulated sequence images and actual breast MRI cases.
Subsequently, we simultaneously compared various existing 3D segmentation methods.
The experimental results demonstrated that 3D-SLSM exhibited precise segmentation results for both types of experimental images.
In addition, 3D-SLSM showed better results for quantitative data compared with existing 3D segmentation methods.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Wang, Chuin-Mu& Huang, Chieh-Ling& Yang, Sheng-Chih. 2018. 3D Shape-Weighted Level Set Method for Breast MRI 3D Tumor Segmentation. Journal of Healthcare Engineering،Vol. 2018, no. 2018, pp.1-15.
https://search.emarefa.net/detail/BIM-1187583
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Wang, Chuin-Mu…[et al.]. 3D Shape-Weighted Level Set Method for Breast MRI 3D Tumor Segmentation. Journal of Healthcare Engineering No. 2018 (2018), pp.1-15.
https://search.emarefa.net/detail/BIM-1187583
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Wang, Chuin-Mu& Huang, Chieh-Ling& Yang, Sheng-Chih. 3D Shape-Weighted Level Set Method for Breast MRI 3D Tumor Segmentation. Journal of Healthcare Engineering. 2018. Vol. 2018, no. 2018, pp.1-15.
https://search.emarefa.net/detail/BIM-1187583
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1187583
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر