Browsing by Author "Lin, S. F."

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A Method for Extracting Suspected Parotid Lesions in CT Images using Feature-based Segmentation and Active Contours based on Stationary Wavelet Transform
(2013)
Wu, T. Y.
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Lin, S. F.
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電機工程學系
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Department of Electrical and Computer Engineering
Automatic suspected lesion extraction is an important application in computer-aided diagnosis (CAD). In this paper, we propose a method to automatically extract the suspected parotid regions for clinical evaluation in head and neck CT images. The suspected lesion tissues in low contrast tissue regions can be localized with feature-based segmentation (FBS) based on local texture features, and can be delineated with accuracy by modified active contour models (ACM). At first, stationary wavelet transform (SWT) is introduced. The derived wavelet coefficients are applied to derive the local features for FBS, and to generate enhanced energy maps for ACM computation. Geometric shape features (GSFs) are proposed to analyze each soft tissue region segmented by FBS; the regions with higher similarity GSFs with the lesions are extracted and the information is also applied as the initial conditions for fine delineation computation. Consequently, the suspected lesions can be automatically localized and accurately delineated for aiding clinical diagnosis. The performance of the proposed method is evaluated by comparing with the results outlined by clinical experts. The experiments on 20 pathological CT data sets show that the true-positive (TP) rate on recognizing parotid lesions is about 94%, and the dimension accuracy of delineation results can also approach over 93%.
ELECTROPHYSIOLOGICAL MODELING OF THE RIGHT ATRIUM WITH THORACIC SLICES AND ITS NUMERICAL SOLUTION ON GPU
(2017-11-01)
Zhang, H.
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Liu, Y.
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Huang, X.
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Lin, S. F.
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分子醫學與生物工程研究所
Levosimendan shortens action potential duration, decreases alternans threshold and prevents ventricular arrhythmia during therapeutic hypothermia in isolated rabbit hearts
(2019-10-01)
Hsieh, Y. C.
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Li, C. H.
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Liao, Y. C.
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Lin, J. C.
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Weng, C. J.
Noninvasive current sensor for household appliances and compensation for installation variation
(2013-04-15)
Cheng, S. H.
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Lin, S. F.
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電控工程研究所
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Institute of Electrical and Control Engineering
The lack of natural resources requires a more efficient use of energy. This study proposes a noninvasive coil current sensor for energy efficiency in the home. The proposed sensor is used to detect current in two-wire power cords used by household appliances. Moreover, the proposed sensor has no contact with the conductors in the power cords, ensuring a safe measurement process. Mathematical models and experiments are conducted to verify the characteristics and performance of the proposed device. In addition, this study develops relevant algorithms and the method for reducing installation variation. Using the developed algorithms, the measurement errors caused by an installation gap were reduced to less than 3%. The information provided by the current sensor supports home energy management systems and encourages energy-saving behaviors for every household member, resulting in an increasingly efficient energy usage. (C) 2013 Elsevier B.V. All rights reserved.