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    Please use this identifier to cite or link to this item: http://nccur.lib.nccu.edu.tw/handle/140.119/126332

    Title: Intensity-Invariant Texture Analysis for Classification of BI-RADS Category 3 Breast Masses
    Authors: 羅崇銘
    Lo, Chung-Ming
    Moon, Woo Kyung
    Huang, Chiun-Sheng
    Chen, Jeon-Hor
    Yang, Min- Chun
    Chang*, Ruey-Feng
    Contributors: 圖檔所
    Keywords: Breast cancer;Breast imaging and reporting data system;Computer-aided diagnosis;Ranklet;Ultrasound
    Date: 2015-03
    Issue Date: 2019-09-19 09:54:16 (UTC+8)
    Abstract: Radiologists likely incorrectly classify benign masses as Breast Imaging Reporting and Data System (BIRADS) category 3. A computer-aided diagnosis (CAD) system was developed in this study as a second viewer to avoid misclassification of carcinomas. Sixty-nine biopsy-proven BI-RADS category 3 masses, including 21 malignant and 48 benign masses, were used to evaluate the CAD system. To improve the texture features, gray-scale variations between images were reduced by transforming pixels into intensity-invariant ranklet coefficients. The textures of the tumor and speckle pixels were extracted from the transformed ranklet images to provide more robust features than in conventionalCADsystems. As a result, tumor texture and speckle texture with ranklet transformation achieved significantly better areas under the receiver operating characteristic curve (Az) compared with those without ranklet transformation (Az = 0.83 vs. 0.58 and Az = 0.80 vs. 0.56, p value <0.05). The improved CAD system can be a second reader to confirm the classification of BI-RADS category 3 masses.
    Relation: Ultrasound in Medicine and Biology, Vol.41, No.7, pp.2039-2048
    Data Type: article
    DOI 連結: https://doi.org/10.1016/j.ultrasmedbio.2015.03.003
    DOI: 10.1016/j.ultrasmedbio.2015.03.003
    Appears in Collections:[圖書資訊與檔案學研究所] 期刊論文

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