Geng-Cheng Lin

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Magnetic resonance image (MRI) was harmless to the human body and used on the clinical trial extensively in recent years. In this study, we want to detect the tissues of breast form the multi-spectral MR image. Because multi-spectral MR image are scanning the same slice with various frequencies and parameters and it can obtain intact information. In the(More)
Magnetic resonance imaging (MRI) is a valuable instrument in medical science owing to its capabilities in soft tissue characterization and 3D visualization. A potential application of MRI in clinical practice is brain parenchyma classification. This work proposes a novel approach called "Unsupervised Linear Discriminant Analysis (ULDA)" to classify and(More)
Magnetic resonance imaging (MRI) is a valuable diagnostic tool in medical science due to its capability for soft-tissue characterization and three-dimensional visualization. One potential application of MRI in clinical practice is brain parenchyma classification and segmentation. Based on fuzzy knowledge and modified seeded region growing, this work(More)
Constrained energy minimization (CEM) has proven highly effective for hyperspectral (or multispectral) target detection and classification. It requires a complete knowledge of the desired target signature in images. This work presents "Unsupervised CEM (UCEM)," a novel approach to automatically target detection and classification in multispectral magnetic(More)
This study proposes a new unsupervised approach for targets detection and classification in multispectral Magnetic Resonance (MR) images. The proposed method comprises two processes, namely Target Generation Process (TGP) and Constrained Energy Minimization (CEM). TGP is a fuzzy-set process that generates a set of potential targets from unknown information,(More)
This paper proposed a system which is using smart phone to develop with a gyroscope sensor license plate location. For another part, it is also designed a flow chart of conditional iteration binarization, FCCIB. The way effectively improves the locating correct rate before the license plate location processing. The problem is that the binarization stage is(More)
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