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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 2015-03
上傳時間 19-Sep-2019 09:54:16 (UTC+8)
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
dc.contributor 圖檔所-
dc.creator (作者) 羅崇銘-
dc.creator (作者) Lo, Chung-Ming-
dc.creator (作者) Moon, Woo Kyung-
dc.creator (作者) Huang, Chiun-Sheng-
dc.creator (作者) Chen, Jeon-Hor-
dc.creator (作者) Yang, Min- Chun-
dc.creator (作者) Chang*, Ruey-Feng-
dc.date (日期) 2015-03-
dc.date.accessioned 19-Sep-2019 09:54:16 (UTC+8)-
dc.date.available 19-Sep-2019 09:54:16 (UTC+8)-
dc.date.issued (上傳時間) 19-Sep-2019 09:54:16 (UTC+8)-
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/126332-
dc.description.abstract (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.-
dc.relation (關聯) Ultrasound in Medicine and Biology, Vol.41, No.7, pp.2039-2048-
dc.subject (關鍵詞) Breast cancer; Breast imaging and reporting data system; Computer-aided diagnosis; Ranklet; Ultrasound-
dc.title (題名) Intensity-Invariant Texture Analysis for Classification of BI-RADS Category 3 Breast Masses-
dc.type (資料類型) article-
dc.identifier.doi (DOI) 10.1016/j.ultrasmedbio.2015.03.003-
dc.doi.uri (DOI) https://doi.org/10.1016/j.ultrasmedbio.2015.03.003-