کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
10712599 | 1025211 | 2014 | 9 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Computerized breast lesions detection using kinetic and morphologic analysis for dynamic contrast-enhanced MRI
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موضوعات مرتبط
مهندسی و علوم پایه
فیزیک و نجوم
فیزیک ماده چگال
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: Computerized breast lesions detection using kinetic and morphologic analysis for dynamic contrast-enhanced MRI Computerized breast lesions detection using kinetic and morphologic analysis for dynamic contrast-enhanced MRI](/preview/png/10712599.png)
چکیده انگلیسی
To facilitate rapid and accurate assessment, this study proposed a novel fully automatic method to detect and identify focal tumor breast lesions using both kinetic and morphologic features from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). After motion registration of all phases of the DCE-MRI study, three automatically generated lines were used to segment the whole breast region of each slice. The kinetic features extracted from the pixel-based time-signal intensity curve (TIC) by a two-stage detection algorithm was first used, and then three-dimensional (3-D) morphologic characteristics of the detected regions were applied to differentiate between tumor and non-tumor regions. In this study, 95 biopsy-confirmed lesions (28 benign and 67 malignant lesions) in 54 women were used to evaluate the detection efficacy of the proposed system. The detection performance was analyzed using the free-response operating characteristics (FROC) curve and detection rate. The proposed computer-aided detection (CADe) system had a detection rate of 92.63% (88/95) of all tumor lesions, with 6.15 false positives per case. Based on the results, kinetic features extracted by TIC can be used to detect tumor lesions and 3-D morphology can effectively reduce the false positives.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Magnetic Resonance Imaging - Volume 32, Issue 5, June 2014, Pages 514-522
Journal: Magnetic Resonance Imaging - Volume 32, Issue 5, June 2014, Pages 514-522
نویسندگان
Yeun-Chung Chang, Yan-Hao Huang, Chiun-Sheng Huang, Jeon-Hor Chen, Ruey-Feng Chang,