کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
1760476 | 1019606 | 2012 | 10 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Three-Dimensional Sonographic Examination of the Midbrain for Computer-Aided Diagnosis of Movement Disorders
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
فیزیک و نجوم
آکوستیک و فرا صوت
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: Three-Dimensional Sonographic Examination of the Midbrain for Computer-Aided Diagnosis of Movement Disorders Three-Dimensional Sonographic Examination of the Midbrain for Computer-Aided Diagnosis of Movement Disorders](/preview/png/1760476.png)
چکیده انگلیسی
We present a novel approach to transcranial B-mode sonography for Parkinson's disease (PD) diagnosis by using 3-D ultrasound (3-DUS). We reconstructed bilateral 3-DUS volumes of the midbrain and substantia nigra echogenicities (SNE) and report results of a more objective abnormality detection in (PD). For classification, we analyzed volumetric measurements of midbrain and SNE in subjects with PD and healthy controls (HC). After blinded segmentation of these structures in 22/23 subjects (11 PD, 11 HC) and by two observers with varying prior experience in this technique, the classification algorithm yielded up to 91% sensitivity and 64% specificity using the larger volume of both SNE as a single-dimensional features and up to 90.9% sensitivity and 72.7% specificity using a multidimensional feature set with midbrain and both SNE volumes. This pilot study indicates that our TC-3-D-US approach is technically feasible and less dependent on the investigator's experience and good bone windows. Our pilot study yielded a fairly high sensitivity and specificity in differentiating between subjects with PD and HC.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Ultrasound in Medicine & Biology - Volume 38, Issue 12, December 2012, Pages 2041-2050
Journal: Ultrasound in Medicine & Biology - Volume 38, Issue 12, December 2012, Pages 2041-2050
نویسندگان
Annika Plate, Seyed-Ahmad Ahmadi, Olivier Pauly, Tassilo Klein, Nassir Navab, Kai Bötzel,