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https://ah.lib.nccu.edu.tw/handle/140.119/126332
題名: | Intensity-Invariant Texture Analysis for Classification of BI-RADS Category 3 Breast Masses | 作者: | 羅崇銘 Lo, Chung-Ming Moon, Woo Kyung Huang, Chiun-Sheng Chen, Jeon-Hor Yang, Min- Chun Chang*, Ruey-Feng |
貢獻者: | 圖檔所 | 關鍵詞: | Breast cancer; Breast imaging and reporting data system; Computer-aided diagnosis; Ranklet; Ultrasound | 日期: | Mar-2015 | 上傳時間: | 19-Sep-2019 | 摘要: | 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. | 關聯: | Ultrasound in Medicine and Biology, Vol.41, No.7, pp.2039-2048 | 資料類型: | article | DOI: | https://doi.org/10.1016/j.ultrasmedbio.2015.03.003 |
Appears in Collections: | 期刊論文 |
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