Visualization of Suspicious Lesions in Breast MRI Based on Intelligent Neural Systems

机译：基于智能神经系统的乳腺MRI可疑病变的可视化

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Intelligent medical systems based on supervised and unsupervised artificial neural networks are applied to the automatic visualization and classification of suspicious lesions in breast MRI. These systems represent an important component of future sophisticated computer-aided diagnosis systems and enable the extraction of spatial and temporal features of dynamic MRI data stemming from patients with confirmed lesion diagnosis. By taking into account the heterogenity of the cancerous tissue, these techniques reveal the malignant, benign and normal kinetic signals and provide a regional subclassification of pathological breast tissue. Intelligent medical systems are expected to have substantial implications in healthcare politics by contributing to the diagnosis of indeterminate breast lesions by non-invasive imaging.

机译：基于监督和无监督的人工神经网络的智能医疗系统被应用于乳房MRI中可疑病变的自动可视化和分类。这些系统代表了未来复杂的计算机辅助诊断系统的重要组成部分，并能够提取出已确诊病变的患者的动态MRI数据的时空特征。通过考虑癌性组织的异质性，这些技术揭示了恶性，良性和正常的动力学信号，并提供了病理性乳腺组织的区域性亚分类。智能医疗系统有望通过无创成像有助于诊断不确定的乳腺病变，从而对医疗保健政治产生重大影响。

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来源
《Intelligent Computing: Theory and Applications IV》|2006年|P.62290K.1-62290K.11|共11页
会议地点 KissimmeeFL(US)
作者
Thorsten Twellmann; Oliver Lange; Tim Wilhelm Nattkemper; Anke Meyer-Baese;
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作者单位

Department of Electrical Computer Engineering, Florida State University, Tallahassee, Florida 32310-6046 USA;

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原文格式 PDF
正文语种 eng
中图分类自动化系统理论;
关键词
supervised and unsupervised learning; computer-aided diagnosis (CAD); breast magnetic resonance imaging;

机译：有监督和无监督学习；计算机辅助诊断（CAD）；乳房磁共振成像;

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专利

1. Model-free visualization of suspicious lesions in breast MRI based on supervised and unsupervised learning [J] . Thorsten Twellmann, Anke Meyer-Baese, Oliver Lange, Engineering Applications of Artificial Intelligence . 2008,第2期

机译：基于监督和无监督学习的乳房MRI可疑病变的无模型可视化
2. MRI-guided breast biopsy: influence of choice of vacuum biopsy system on the mode of biopsy of MRI-only suspicious breast lesions. [J] . Schrading S, Simon B, Braun M, AJR: American Journal of Roentgenology : Including Diagnostic Radiology, Radiation Oncology, Nuclear Medicine, Ultrasonography and Related Basic Sciences . 2010,第6期

机译：MRI引导的乳腺活检：真空活检系统的选择对仅MRI可疑乳腺病变的活检模式的影响。
3. Cancelation of MRI Guided Breast Biopsies for Suspicious Breast Lesions Identified at 3.0 T MRI. Reasons, Rates, and Outcomes [J] . JohnsonK.S., BakerJ.A., LeeS.S., Academic radiology . 2013,第5期

机译：MRI引导下可疑乳腺病变的MRI活检的取消在3.0 T MRI上已确认。原因，费率和结果
4. Visualization of Suspicious Lesions in Breast MRI Based on Intelligent Neural Systems [C] . Thorsten Twellmann, Oliver Lange, Tim Wilhelm Nattkemper, Conference on Intelligent Computing . 2006

机译：基于智能神经系统的乳房MRI可视化病变可视化
5. Interactive 3D GPU-based breast mass lesion segmentation method based on level sets for DCE-MRI images. [D] . Zavala-Romero, Olmo Sebastian. 2015

机译：基于水平集的DCE-MRI图像的基于交互式3D GPU的乳房肿块病变分割方法。
6. Model–Free Visualization of Suspicious Lesions in Breast MRI Based on Supervised and Unsupervised Learning [O] . Thorsten Twellmann, Anke Meyer-Baese, Oliver Lange, -1

机译：基于有监督和无监督学习的乳房MRI可疑病变的无模型可视化
7. Model–Free Visualization of Suspicious Lesions in Breast MRI Based on Supervised and Unsupervised Learning [O] . Twellmann, T Thorsten, Meyer-Bäse, A Anke, Lange, O, 2008

机译：基于有监督和无监督学习的乳房MRI可疑病变的无模型可视化

Visualization of Suspicious Lesions in Breast MRI Based on Intelligent Neural Systems

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