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Computerized breast lesions detection using kinetic and morphologic analysis for dynamic contrast-enhanced MRI
- Source :
- Magnetic Resonance Imaging. 32:514-522
- Publication Year :
- 2014
- Publisher :
- Elsevier BV, 2014.
-
Abstract
- 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.
- Subjects :
- Adult
Gadolinium DTPA
Biomedical Engineering
Biophysics
Contrast Media
Breast Neoplasms
Models, Biological
Sensitivity and Specificity
Pattern Recognition, Automated
Image Interpretation, Computer-Assisted
medicine
False positive paradox
Humans
Computer Simulation
Radiology, Nuclear Medicine and imaging
Whole breast
Aged
medicine.diagnostic_test
Pixel
business.industry
Reproducibility of Results
Magnetic resonance imaging
Middle Aged
Image Enhancement
Magnetic Resonance Imaging
Intensity (physics)
Kinetics
Dynamic contrast-enhanced MRI
Fully automatic
Detection performance
Female
Nuclear medicine
business
Subjects
Details
- ISSN :
- 0730725X
- Volume :
- 32
- Database :
- OpenAIRE
- Journal :
- Magnetic Resonance Imaging
- Accession number :
- edsair.doi.dedup.....e346678785a332e29cfb5f59dad4422b