Yang, H.-C.H.-C.YangChang, C.-H.C.-H.ChangHuang, S.-W.S.-W.HuangChou, Y.I.-H.Y.I.-H.ChouPAI-CHI LI2020-04-162020-04-162008https://scholars.lib.ntu.edu.tw/handle/123456789/484582https://www.scopus.com/inward/record.uri?eid=2-s2.0-66749127388&doi=10.1177%2f016173460803000404&partnerID=40&md5=3f71c38438344c69753a732ae36034f301617346Acoustic, textural and morphological features of the breast in ultrasound imaging were extracted for computer-aided diagnosis. In addition, correlations among different categories of features were analyzed. Clinical data from 14 patients (7 malignant and 7 benign samples) were acquired. A custom-made experimental apparatus was used for simultaneous data acquisition of B-mode ultrasound and limited-angle tomography images. Textural features were extracted from B-mode images, including five parameters derived from the gray-level concurrence matrix and five parameters derived from a nonseparable wavelet transform. Morphological features were also extracted from B-mode images, including the depth-to-width ratio and normalized radial gradient. Acoustic features were estimated using limited-angle tomography, including the sound velocity and attenuation coefficient. Generally, the correlation coefficients for features within the textural feature group were relatively high (0.48-0.79), whereas those between different feature categories were relatively low (0.17-0.40). This suggests that combining different sets of features would improve the computer-aided diagnosis of breast cancer. Copyright 2008/2009 by Dynamedia, Inc. All rights of reproduction in any form reserved.Acoustic features; Attenuation; Breast ultrasound; Computer-aided diagnosis; Morphological features; Sound velocity; Texture features[SDGs]SDG3Acoustic wave velocity; Data acquisition; Medical imaging; Textures; Tomography; Ultrasonic imaging; Wavelet transforms; Acoustic features; Attenuation; Breast ultrasound; Morphological features; Texture features; Computer aided diagnosis; acoustics; article; attenuation; breast cancer; cancer diagnosis; clinical article; computer assisted diagnosis; computer assisted tomography; correlation analysis; correlation coefficient; diagnostic accuracy; echomammography; female; human; information processing; mathematical computing; morphology; parameter; receiver operating characteristic; sound intensityjournal article10.1177/016173460803000404195076762-s2.0-66749127388