کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
10691797 | 1019610 | 2014 | 6 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Selection of the Sub-noise Gain Level for Acquisition of VOCAL Data Sets: A Reliability Study
دانلود مقاله + سفارش ترجمه
دانلود مقاله ISI انگلیسی
رایگان برای ایرانیان
کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
فیزیک و نجوم
آکوستیک و فرا صوت
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
This study was aimed at assessing the intra-observer and inter-observer repeatability of selecting the sub-noise gain (SNG) level when acquiring placental volumes with 3-D power Doppler for analysis using virtual organ computer-aided analysis (VOCAL). Sixty women with uncomplicated singleton pregnancies between 20 and 38Â wk of gestation were recruited. Two women were excluded for flash artifact noted during image analysis. Two blinded observers independently adjusted gain to their perceived SNG level before acquiring a static 3-D volume of the placenta at the cord insertion; observers alternated after each acquisition until each had acquired two volumes. A single observer operated the probe at all times. During offline analysis, SNG levels were recorded and VOCAL indices were calculated. SNG exhibited excellent intra-observer and inter-observer reliability. Intra-observer intra-class correlation coefficients (95% confidence intervals) were 0.98 (0.97-0.99) and 0.98 (0.98-0.99) for observers 1 and 2, respectively. The inter-observer intra-class correlation coefficient was 0.96 (0.93-0.98). Despite its perceived inherent subjectivity, the excellent intra-class correlation coefficients obtained in this study support SNG as a promising tool for future research using 3-D power Doppler.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Ultrasound in Medicine & Biology - Volume 40, Issue 3, March 2014, Pages 562-567
Journal: Ultrasound in Medicine & Biology - Volume 40, Issue 3, March 2014, Pages 562-567
نویسندگان
Jennifer Sanderson, Linda Wu, Aditi Mahajan, Neama Meriki, Amanda Henry, Alec W. Welsh,