کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
5499096 | 1533484 | 2017 | 22 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Simulation of breast compression in mammography using finite element analysis: A preliminary study
ترجمه فارسی عنوان
شبیه سازی فشرده سازی سینه در ماموگرافی با استفاده از تحلیل عناصر محدود: مطالعه مقدماتی
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کلمات کلیدی
ماموگرافی، ضخامت سینه فشرده، تجزیه و تحلیل عنصر محدود،
موضوعات مرتبط
مهندسی و علوم پایه
فیزیک و نجوم
تشعشع
چکیده انگلیسی
Adequate compression during mammography lowers the absorbed dose in the breast and improves the image quality. The compressed breast thickness (CBT) is affected by various factors, such as breast volume, glandularity, and compression force. In this study, we used the finite element analysis to simulate breast compression and deformation and validated the simulated CBT with clinical mammography results. Image data from ten subjects who had undergone mammography screening and breast magnetic resonance imaging (MRI) were collected, and their breast models were created according to the MR images. The non-linear tissue deformation under 10â16 daN in the cranial-caudal direction was simulated. When the clinical compression force was used, the simulated CBT ranged from 2.34 to 5.90Â cm. The absolute difference between the simulated CBT and the clinically measured CBT ranged from 0.5 to 7.1Â mm. The simulated CBT had a strong positive linear relationship to breast volume and a weak negative correlation to glandularity. The average simulated CBT under 10, 12, 14, and 16 daN was 5.68, 5.12, 4.67, and 4.25Â cm, respectively. Through this study, the relationships between CBT, breast volume, glandularity, and compression force are provided for use in clinical mammography.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Radiation Physics and Chemistry - Volume 140, November 2017, Pages 295-299
Journal: Radiation Physics and Chemistry - Volume 140, November 2017, Pages 295-299
نویسندگان
Yan-Lin Liu, Pei-Yuan Liu, Mei-Lan Huang, Jui-Ting Hsu, Ruo-Ping Han, Jay Wu,