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Feasibility of Image Registration for Ultrasound-Guided Prostate RadiotherapyBased on Similarity Measurement by a Convolutional Neural Network

机译：超声引导的前列腺放射治疗中图像配准的可行性基于卷积神经网络的相似度度量

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Purpose:Registration of 3-dimensional ultrasound images poses a challenge for ultrasound-guided radiation therapy of the prostate since ultrasound image content changes significantly with anatomic motion and ultrasound probe position. The purpose of this work is to investigate the feasibility of using a pretrained deep convolutional neural network for similarity measurement in image registration of 3-dimensional transperineal ultrasound prostate images.

机译：目的：3维超声图像的配准对超声引导的前列腺放射治疗提出了挑战，因为超声图像的含量会随着解剖运动和超声探头位置的变化而显着变化。这项工作的目的是调查在三维经会阴超声前列腺图像的图像配准中使用预训练的深度卷积神经网络进行相似性测量的可行性。

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期刊名称 Technology in Cancer Research Treatment
作者
Ning Zhu; Mohammad Najafi; Bin Han; Steven Hancock; Dimitre Hristov;
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作者单位

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年(卷),期 2019(18),-1
年度 2019
页码 1533033818821964
总页数 11
原文格式 PDF
正文语种
中图分类肿瘤学;
关键词
ultrasound image registration prostate radiotherapy image-guided radiation therapy (IGRT) deep convolutional neural network;

机译：超声图像配准;前列腺癌;放射治疗;图像引导放射治疗（IGRT）;深度卷积神经网络;

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专利

1. Feasibility of Image Registration for Ultrasound-Guided Prostate Radiotherapy Based on Similarity Measurement by a Convolutional Neural Network [J] . Ning Zhu, Mohammad Najafi, Bin Han, Technology in cancer research & treatment. . 2019,第18期

机译：基于卷积神经网络相似度测量的超声引导前列腺放射治疗中图像配准的可行性
2. Automatic segmentation of prostate MRI using convolutional neural networks: Investigating the impact of network architecture on the accuracy of volume measurement and MRI-ultrasound registration [J] . Ghavami Nooshin, Hu Yipeng, Gibson Eli, Medical image analysis . 2019,第期

机译：使用卷积神经网络自动分割前列腺MRI：调查网络架构对体积测量准确性的影响和MRI超声登记
3. Three-Dimensional Convolutional Neural Network for Prostate MRI Segmentation and Comparison of Prostate Volume Measurements by Use of Artificial Neural Network and Ellipsoid Formula [J] . AJR: American Journal of Roentgenology : Including Diagnostic Radiology, Radiation Oncology, Nuclear Medicine, Ultrasonography and Related Basic Sciences . 2020,第6期

机译：用于使用人工神经网络和椭球体的前列腺MRI分割及前列腺体积测量的三维卷积神经网络
4. Image Registration for Interventional MRI Guided Procedures: Interpolation Methods, Similarity Measurements, and Applications to the Prostate [C] . Baowei Fei, Zhenghong Lee, Jeffery L. Duerk, Second International Workshop on Biomedical Image Registration WBIR 2003; Jun 23-24, 2003; Philadelphia, PA, USA . 2003

机译：介入MRI引导程序的图像配准：插值方法，相似性测量及其在前列腺中的应用
5. Multimodal image registration using multivariate information theoretic similarity measures: Applications to prostate cancer diagnosis and targeted treatment [D] . Chappelow, Jonathan 2011

机译：使用多变量信息理论相似性度量进行多峰图像配准：在前列腺癌诊断和靶向治疗中的应用
6. Error estimation of deformable image registration of pulmonary CT scans using convolutional neural networks [O] . Koen A. J. Eppenhof, Josien P. W. Pluim 2018

机译：利用卷积神经网络估计肺部CT扫描的可变形图像配准的误差
7. Automatic segmentation of prostate MRI using convolutional neural networks: Investigating the impact of network architecture on the accuracy of volume measurement and MRI-ultrasound registration [O] . Nooshin Ghavami, Yipeng Hu, Eli Gibson, 2019

机译：使用卷积神经网络自动分割前列腺MRI：研究网络架构对体积测量准确性的影响和MRI超声登记

Feasibility of Image Registration for Ultrasound-Guided Prostate RadiotherapyBased on Similarity Measurement by a Convolutional Neural Network

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