کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6484130 | 1416072 | 2018 | 9 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
A fast and robust level set motion-assisted deformable registration method for volumetric CT guided lung intervention
ترجمه فارسی عنوان
روش ثبت سریع شکل گیری سریع و پایدار برای مداخله ریه مبتنی بر سیگنال حجمی اندازه گیری شده است
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کلمات کلیدی
پردازش تصویر پزشکی، ثبت نام تصویر، روش اندازه گیری سطح،
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی شیمی
بیو مهندسی (مهندسی زیستی)
چکیده انگلیسی
This paper describes the accurate deformable registration method for image-guided lung interventions, including lung nodule biopsy and radiofrequency ablation of lung tumours. A level set motion assisted deformable registration method for computed tomography (CT) images was proposed and its accuracy and speed were compared with those of other conventional methods. Fifteen 3D CT images obtained from lung biopsy patients were scanned. Each scan consisted of diagnostic and preoperative CT images. Each deformable registration method was initially evaluated with a landmark-based affine registration algorithm. Various deformable registration methods such as level set motion, demons, diffeomorphic demons, and b-spline were compared. Visual assessment by two expert thoracic radiologists using five scales showed an average visual score of 3.2 for level set motion deformable registration, whereas scores were below 3 for other deformable registration methods. In the qualitative assessment, the level set motion algorithm showed better results than those obtained with other deformable registration methods. A level set motion based deformable registration algorithm was effective for registering diagnostic and preoperative volumetric CT images for image-guided lung intervention.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Biocybernetics and Biomedical Engineering - Volume 38, Issue 3, 2018, Pages 439-447
Journal: Biocybernetics and Biomedical Engineering - Volume 38, Issue 3, 2018, Pages 439-447
نویسندگان
Daegwan Kim, Namkug Kim, Sangmin Lee, Joon Beom Seo,