Detection of high GS risk group prostate tumors by diffusion tensor imaging and logistic regression modelling

Ertas Gokhan

首页> 外文期刊>Magnetic resonance imaging: An International journal of basic research and clinical applications >Detection of high GS risk group prostate tumors by diffusion tensor imaging and logistic regression modelling

【24h】

Detection of high GS risk group prostate tumors by diffusion tensor imaging and logistic regression modelling

机译：通过扩散张测成像和逻辑回归建模检测高GS风险群前列腺肿瘤

获取原文

获取原文并翻译 | 示例

掌桥外文数据库（机构版） >>

开具论文收录证明 >>

文献代查 >>

页面导航

摘要
著录项
相似文献
相关主题

摘要

Purpose: To assess the value of joint evaluation of diffusion tensor imaging (DTI) measures by using logistic regression modelling to detect high GS risk group prostate tumors.

机译：目的：通过使用逻辑回归模型来评估扩散张量成像（DTI）测量的联合评估值，以检测高GS风险组前列腺肿瘤。

著录项

来源
《Magnetic resonance imaging: An International journal of basic research and clinical applications》 |2018年第2018期|共9页
作者
Ertas Gokhan;
展开▼
作者单位

Yeditepe Univ Dept Biomed Engn Istanbul Turkey;

展开▼
收录信息
原文格式 PDF
正文语种 eng
中图分类磁性弛豫及共振现象;
关键词
Prostate cancer; Diffusion tensor imaging; Fractional anisotropy; Mean diffusivity; Ratio; Logistic regression; Joint evaluation;

机译：前列腺癌;扩散张量成像;分数各向异性;平均扩散性;比率;逻辑回归;联合评估;

相似文献

外文文献
中文文献
专利

1. Detection of high GS risk group prostate tumors by diffusion tensor imaging and logistic regression modelling [J] . Ertas Gokhan Magnetic resonance imaging: An International journal of basic research and clinical applications . 2018,第期

机译：通过扩散张测成像和逻辑回归建模检测高GS风险群前列腺肿瘤
2. Prostate cancer detection with multi-parametric MRI: logistic regression analysis of quantitative T2, diffusion-weighted imaging, and dynamic contrast-enhanced MRI. [J] . Langer DL, van der Kwast TH, Evans AJ Journal of magnetic resonance imaging: JMRI . 2009,第2期

机译：多参数MRI检测前列腺癌：定量T2，扩散加权成像和动态对比增强MRI的逻辑回归分析。
3. A critical appraisal of logistic regression-based nomograms, artificial neural networks, classification and regression-tree models, look-up tables and risk-group stratification models for prostate cancer. [J] . Chun FK, Karakiewicz PI, Briganti A, BJU international . 2007,第4期

机译：对基于Logistic回归的列线图，人工神经网络，分类和回归树模型，查找表和前列腺癌风险组分层模型的重要评估。
4. Tumor segmentation with multi-modality image in Conditional Random Field framework with logistic regression models [C] . Hu Yu-chi, Grossberg Michael, Mageras Gig Annual International Conference of the IEEE Engineering in Medicine and Biology Society . 2014

机译：条件随机场框架中具有逻辑回归模型的多模态图像肿瘤分割
5. Using the multivariate multilevel logistic regression model to detect DIF: A comparison with HGLM and logistic regression DIF detection methods [D] . Pan, Tianshu. 2008

机译：使用多元多级Logistic回归模型检测DIF：与HGLM和Logistic回归DIF检测方法的比较
6. Predicting the outcome of prostate biopsy: comparison of a novel logistic regression-based model the prostate cancer risk calculator and prostate-specific antigen level alone [O] . David J. Hernandez, Misop Han, Elizabeth B. Humphreys, -1

机译：预测前列腺活检的结果：新型基于逻辑回归的模型前列腺癌风险计算器和单独的前列腺特异性抗原水平的比较
7. Early (72-Hour) detection of radiotherapy-induced changes in an experimental tumor model using diffusion-weighted imaging, diffusion tensor imaging, and Q-space imaging parameters : A comparative study. [O] . Peeters, Frank, Rommel, Denis, Abarca-Quinones, Jorge, 2012

机译：早期（72小时）使用扩散加权成像，扩散张量成像和Q空间成像参数在实验性肿瘤模型中检测放疗引起的变化：一项比较研究。

Detection of high GS risk group prostate tumors by diffusion tensor imaging and logistic regression modelling

摘要

著录项

相似文献

相关主题

期刊订阅