Please use this identifier to cite or link to this item: 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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