کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4964675 | 1447885 | 2017 | 23 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Individual refinement of attenuation correction maps for hybrid PET/MR based on multi-resolution regional learning
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
نرم افزارهای علوم کامپیوتر
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چکیده انگلیسی
PET/MR is an emerging hybrid imaging modality. However, attenuation correction (AC) remains challenging for hybrid PET/MR in generating accurate PET images. Segmentation-based methods on special MR sequences are most widely recommended by vendors. However, their accuracy is usually not high. Individual refinement of available certified attenuation maps may be helpful for further clinical applications. In this study, we proposed a multi-resolution regional learning (MRRL) scheme to utilize the internal consistency of the patient data. The anatomical and AC MR sequences of the same subject were employed to guide the refinement of the provided AC maps. The developed algorithm was tested on 9 patients scanned consecutively with PET/MR and PET/CT (7 [18F]FDG and 2 [18F]FET). The preliminary results showed that MRRL can improve the accuracy of segmented attenuation maps and consequently the accuracy of PET reconstructions.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computerized Medical Imaging and Graphics - Volume 60, September 2017, Pages 50-57
Journal: Computerized Medical Imaging and Graphics - Volume 60, September 2017, Pages 50-57
نویسندگان
Kuangyu Shi, Sebastian Fürst, Liang Sun, Mathias Lukas, Nassir Navab, Stefan Förster, Sibylle I. Ziegler,