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  4. Liver steatosis classification using high-frequency ultrasound
 
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Liver steatosis classification using high-frequency ultrasound

Journal
Ultrasound in Medicine and Biology
Journal Volume
31
Journal Issue
5
Pages
599-605
Date Issued
2005
Author(s)
Yeh W.-C.
YUNG-MING JENG  
Li C.-H.
PO-HUANG LEE  
PAI-CHI LI  
DOI
10.1016/j.ultrasmedbio.2005.01.009
URI
https://www.scopus.com/inward/record.uri?eid=2-s2.0-18144428327&doi=10.1016%2fj.ultrasmedbio.2005.01.009&partnerID=40&md5=46ca559f7a5661ce116d90a3d63a5a6d
https://scholars.lib.ntu.edu.tw/handle/123456789/521469
Abstract
High-frequency B-mode images of 19 fresh human liver samples were obtained to evaluate their usefulness in determining the steatosis grade. The images were acquired by a mechanically controlled single-crystal probe at 25 MHz. Image features derived from gray-level concurrence and nonseparable wavelet transform were extracted to classify steatosis grade using a classifier known as the support vector machine. A subsequent histologic examination of each liver sample graded the steatosis from 0 to 3. The four grades were then combined into two, three and four classes. The classification results were correlated with histology. The best classification accuracies of the two, three and four classes were 90.5%, 85.8% and 82.6%, respectively, which were markedly better than those at 7 MHz. These results indicate that liver steatosis can be more accurately characterized using high-frequency B-mode ultrasound. Limitations and their potential solutions of applying high-frequency ultrasound to liver imaging are also discussed. ? 2005 World Federation for Ultrasound in Medicine & Biology.
Subjects
Gray-level concurrence; High-frequency ultrasound; Liver pathology; Nonseparable wavelet transform; Steatosis; Support vector machine; Tissue characterization
SDGs

[SDGs]SDG3

Other Subjects
Correlation methods; Frequencies; Histology; Single crystals; Ultrasonics; Wavelet transforms; High-frequency ultrasound; Liver imaging; Liver steatosis classification; Support vector machine (SVM); Medical imaging; article; B scan; clinical feature; controlled study; correlation analysis; crystal; diagnostic accuracy; diagnostic value; disease classification; fatty liver; histopathology; human; human tissue; image analysis; intermethod comparison; liver; priority journal; tissue characterization
Publisher
Elsevier USA
Type
journal article

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