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Using Computer-extracted Image Phenotypes from Tumors on Breast MRI to Predict Breast Cancer Pathologic Stage

机译：使用计算机从乳腺癌MRI上提取的图像表型来预测乳腺癌的病理学阶段

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摘要

BackgroundTo demonstrate that computer-extracted image phenotypes (CEIPs) of biopsy-proven breast cancer on MRI can accurately predict pathologic stage.

机译：背景为了证明经MRI活检证实的乳腺癌的计算机提取图像表型（CEIP）可以准确预测病理分期。

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期刊名称 other
作者
Elizabeth S. Burnside; Karen Drukker; Hui Li; Ermelinda Bonaccio; Margarita Zuley; Marie Ganott; Jose M. Net; Elizabeth Sutton; Kathleen R. Brandt; Gary Whitman; Suzanne Conzen; Li Lan; Yuan Ji; Yitan Zhu; Carl Jaffe; Erich Huang; John Freymann; Justin Kirby; Elizabeth Morris; Maryellen Giger;
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年(卷),期 -1(122),5
年度 -1
页码 748–757
总页数 24
原文格式 PDF
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关键词
breast cancer stage prognosis quantitative image analysis MRI;

机译：乳腺癌分期;预后;定量图像分析;MRI;

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专利

1. Using computer-extracted image phenotypes from tumors on breast magnetic resonance imaging to predict breast cancer pathologic stage [J] . Burnside Elizabeth S., Drukker Karen, Li Hui, Cancer: A Journal of the American Cancer Society . 2016,第5期

机译：在乳腺磁共振成像上使用来自肿瘤的计算机提取的图像表型来预测乳腺癌的病理分期
2. Imaging Phenotypes of Breast Cancer Heterogeneity in Preoperative Breast Dynamic Contrast Enhanced Magnetic Resonance Imaging (DCE-MRI) Scans Predict 10-Year Recurrence [J] . Chitalia Rhea D., Rowland Jennifer, McDonald Elizabeth S., Clinical cancer research: an official journal of the American Association for Cancer Research . 2020,第4期

机译：术前乳房动态对比增强磁共振成像（DCE-MRI）扫描预测10年复发的乳腺癌异质性的成像表型
3. Triple-negative breast cancers: Associations between imaging and pathological findings for triple-negative tumors compared with hormone receptor-positive/human epidermal growth factor receptor-2-negative breast cancers [J] . Boisserie-LacroixM., MacGroganG., DebledM., The oncologist . 2013,第7期

机译：三阴性乳腺癌：与激素受体阳性/人表皮生长因子受体-2-阴性乳腺癌相比，三阴性肿瘤的影像学表现与病理结果之间的关联
4. Artificial neural networks in breast cancer diagnosis: merging of computer-extracted features from breast images [C] . Giger, M.L., Zhimin Huo . 1999

机译：人工神经网络在乳腺癌诊断中的作用：合并来自乳腺图像的计算机提取特征
5. Using Preoperative Mri-guided Biopsies to Predict Pathologic Complete Response after Neoadjuvant Chemotherapy in Breast Cancer [D] . Kim, Jiyoon. 2019

机译：在乳腺癌新辅助化疗后使用术前Mri引导的活检来预测病理完全缓解
6. Intra-tumor partitioning and texture analysis of DCE-MRI identifies relevant tumor subregions to predict pathological response of breast cancer to neoadjuvant chemotherapy [O] . Jia Wu, Guanghua Gong, Yi Cui, -1

机译：DCE-MRI的肿瘤内分区和纹理分析可确定相关的肿瘤子区域以预测乳腺癌对新辅助化疗的病理反应
7. Using computer-extracted image phenotypes from tumors on breast magnetic resonance imaging to predict breast cancer pathologic stage [O] . Elizabeth S. Burnside, Karen Drukker, Hui Li, 2015

机译：使用来自肿瘤的计算机提取的图像表型对乳房磁共振成像进行预测乳腺癌病理阶段

Using Computer-extracted Image Phenotypes from Tumors on Breast MRI to Predict Breast Cancer Pathologic Stage

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