...
首页> 外文期刊>Journal of computer assisted tomography >New spatiotemporal features for improved discrimination of benign and malignant lesions in dynamic contrast-enhanced-magnetic resonance imaging of the breast.
【24h】

New spatiotemporal features for improved discrimination of benign and malignant lesions in dynamic contrast-enhanced-magnetic resonance imaging of the breast.

机译:新的时空特征可改善乳房动态对比增强磁共振成像中对良性和恶性病变的鉴别能力。

获取原文
获取原文并翻译 | 示例
   

获取外文期刊封面封底 >>

       

摘要

OBJECTIVES: The objective of this study was to measure the efficacy of 7 new spatiotemporal features for discriminating between benign and malignant lesions in dynamic contrast-enhanced-magnetic resonance imaging (MRI) of the breast. METHODS: A total of 48 breast lesions from 39 patients were used: 25 malignant and 23 benign. Lesions were acquired using 1.5-T MRI machines in 3 different protocols. Two experiments were performed: (i) selection of the most discriminatory subset of features drawn from the new features and features from the literature and (ii) validation of classification performance of the selected subset of features. RESULTS: Results of the feature selection experiment show that the subset comprising 2 of the new features is the most useful for automatic classification of suspicious lesions in the breast: (i) gradient correlation of maximum intensity and (ii) mean wash-in rate. Results of the validation experiment show that using these 2 features, unseen data can be classified with an area under the receiver operating characteristic curve of 0.91 +/- 0.06. CONCLUSIONS: Results of the experiments suggest that suspicious lesions in dynamic contrast-enhanced-MRI of the breast can be classified, with high accuracy, using only 2 of the proposed spatiotemporal features. The selected features indicate heterogeneity of enhancement and speed of enhancement in a tissue. High values of these indicators are likely to be correlated with malignancy.
机译:目的:本研究的目的是测量乳房动态对比增强磁共振成像(MRI)中7种新的时空特征在良性和恶性病变之间的区别。方法:总共使用了来自39例患者的48个乳腺病变:25例恶性和23例良性。使用3种不同方案的1.5-T MRI机器获取病变。进行了两个实验:(i)从新特征和文献中的特征中选择特征最具有区别的子集,以及(ii)验证所选特征子集的分类性能。结果:特征选择实验的结果表明,包含2个新特征的子集对于自动分类乳腺中的可疑病变最为有用:(i)最大强度的梯度相关性和(ii)平均清洗率。验证实验的结果表明,使用这两个功能,可以将接收器工作特性曲线下的面积为0.91 +/- 0.06的未分类数据分类。结论:实验结果表明,仅使用建议的时空特征中的2个,就可以对乳腺动态对比增强MRI中的可疑病变进行高精度分类。所选特征指示组织中增强的异质性和增强的速度。这些指标的高价值可能与恶性肿瘤相关。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号