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| 講演名 | 2009-01-19 13:45 Using Tumor Morphology to Classify Benign and Malignant Solid Breast Masses:Speckle Reduction Imaging (SRI) versus Non-SRI Ultrasound Imaging ○Hsien-Chang Chuang（Tunghai Univ.）・Dar-Ren Chen（Changhua Christian Hospital）・Yu-Len Huang（Tunghai Univ.）  MI2008-64 |
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| 抄録 | （和） | In this paper, we attempted to compare the diagnostic performance of speckle reduction imaging (SRI) ultrasound and non-SRI ultrasound using sonographic technique to classify benign and malignant breast tumors by morphology. This study evaluated 110 breast lesions. A total of 72 benign and 38 malignant breast tumor images with pathologic proven cases were analyzed. The suspicious tumor contours on both SRI and non-SRI ultrasound images were manually sketched by experienced physicians. Twenty practical morphologic features from the extracted contour were calculated and a support vector machine (SVM) classifier identified the breast tumor as benign or malignant. Conventional binormal receiver operating characteristics (ROC) curve analysis used overall morphologic features from the breast lesions in SRI and non-SRI ultrasound. The area under the ROC curve (Az) was 0.8105 and 0.8241, respectively. This difference was not statistically significant (p = 0.343). The sensitivity was 78.9% and 84.2% (p = 0.554), respectively; the specificity was 73.6% and 70.8% (p = 0.881), respectively; the difference were not statistically significant. According to our study, both non-SRI and SRI methods are helpful to classify benign and malignant breast tumors by morphology, and the diagnostic performance is almost identical without statistical significance. |
| （英） | In this paper, we attempted to compare the diagnostic performance of speckle reduction imaging (SRI) ultrasound and non-SRI ultrasound using sonographic technique to classify benign and malignant breast tumors by morphology. This study evaluated 110 breast lesions. A total of 72 benign and 38 malignant breast tumor images with pathologic proven cases were analyzed. The suspicious tumor contours on both SRI and non-SRI ultrasound images were manually sketched by experienced physicians. Twenty practical morphologic features from the extracted contour were calculated and a support vector machine (SVM) classifier identified the breast tumor as benign or malignant. Conventional binormal receiver operating characteristics (ROC) curve analysis used overall morphologic features from the breast lesions in SRI and non-SRI ultrasound. The area under the ROC curve (Az) was 0.8105 and 0.8241, respectively. This difference was not statistically significant (p = 0.343). The sensitivity was 78.9% and 84.2% (p = 0.554), respectively; the specificity was 73.6% and 70.8% (p = 0.881), respectively; the difference were not statistically significant. According to our study, both non-SRI and SRI methods are helpful to classify benign and malignant breast tumors by morphology, and the diagnostic performance is almost identical without statistical significance. | |
| キーワード | （和） | speckle reduction imaging / breast sonography / tumor classification / tumor segmentation / support vector machine / / / |
| （英） | speckle reduction imaging / breast sonography / tumor classification / tumor segmentation / support vector machine / / / | |
| 文献情報 | 信学技報, vol. 108, no. 385, MI2008-64, pp. 33-36, 2009年1月. | |
| 資料番号 | MI2008-64 | |
| 発行日 | 2009-01-12 (MI) | |
| ISSN | Print edition: ISSN 0913-5685 Online edition: ISSN 2432-6380 | |
| 著作権に ついて |
技術研究報告に掲載された論文の著作権は電子情報通信学会に帰属します．(許諾番号：10GA0019/12GB0052/13GB0056/17GB0034/18GB0034) | |
| PDFダウンロード | MI2008-64 |
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| 研究会情報 | |
| 研究会 | MI |
| 開催期間 | 2009-01-19 - 2009-01-21 |
| 開催地（和） | 国立台湾大学(台北市) |
| 開催地（英） | National Taiwan University |
| テーマ（和） | 医用画像一般 |
| テーマ（英） | Medical Imaging |
| 講演論文情報の詳細 | |
| 申込み研究会 | MI |
| 会議コード | 2009-01-MI |
| 本文の言語 | 英語 |
| タイトル（和） | |
| サブタイトル（和） | |
| タイトル（英） | Using Tumor Morphology to Classify Benign and Malignant Solid Breast Masses:Speckle Reduction Imaging (SRI) versus Non-SRI Ultrasound Imaging |
| サブタイトル（英） | |
| キーワード(1)（和/英） | speckle reduction imaging / speckle reduction imaging |
| キーワード(2)（和/英） | breast sonography / breast sonography |
| キーワード(3)（和/英） | tumor classification / tumor classification |
| キーワード(4)（和/英） | tumor segmentation / tumor segmentation |
| キーワード(5)（和/英） | support vector machine / support vector machine |
| キーワード(6)（和/英） | / |
| キーワード(7)（和/英） | / |
| キーワード(8)（和/英） | / |
| 第1著者 氏名（和/英/ヨミ） | Hsien-Chang Chuang / Hsien-Chang Chuang / |
| 第1著者 所属（和/英） | Tunghai University (略称： Tunghai Univ.) Tunghai University (略称： Tunghai Univ.) |
| 第2著者 氏名（和/英/ヨミ） | Dar-Ren Chen / Dar-Ren Chen / |
| 第2著者 所属（和/英） | Changhua Christian Hospital (略称： Changhua Christian Hospital) Changhua Christian Hospital (略称： Changhua Christian Hospital) |
| 第3著者 氏名（和/英/ヨミ） | Yu-Len Huang / Yu-Len Huang / |
| 第3著者 所属（和/英） | Tunghai University (略称： Tunghai Univ.) Tunghai University (略称： Tunghai Univ.) |
| 講演者 | 第1著者 |
| 発表日時 | 2009-01-19 13:45:00 |
| 発表時間 | 10分 |
| 申込先研究会 | MI |
| 資料番号 | MI2008-64 |
| 巻番号（vol） | vol.108 |
| 号番号（no） | no.385 |
| ページ範囲 | pp.33-36 |
| ページ数 | 4 |
| 発行日 | 2009-01-12 (MI) |
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