Quantifying the Dose to Functional Lung Regions Using Patient-Specific Elasticity Distributions Estimated From a Deep Learning Approach

Hasse K.; OConnell D.; Neylon J.; Min Y.; Lee P.; Low D.; Santhanam A.

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Quantifying the Dose to Functional Lung Regions Using Patient-Specific Elasticity Distributions Estimated From a Deep Learning Approach

机译：使用深度学习方法估计的患者特异性弹性分布量化剂量至功能性肺区

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来源
《Medical Physics》 |2018年第6期|共1页
作者
Hasse K.; OConnell D.; Neylon J.; Min Y.; Lee P.; Low D.; Santhanam A.;
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作者单位

Univ Calif Los Angeles Los Angeles CA USA;

Univ Calif Los Angeles Los Angeles CA USA;

Univ Calif Los Angeles Los Angeles CA USA;

Univ Calif Los Angeles Los Angeles CA USA;

Univ Calif Los Angeles Los Angeles CA USA;

Univ Calif Los Angeles Los Angeles CA USA;

Univ Calif Los Angeles Los Angeles CA USA;

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原文格式 PDF
正文语种 eng
中图分类基础医学;
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1. Quantifying the Dose to Functional Lung Regions Using Patient-Specific Elasticity Distributions Estimated From a Deep Learning Approach [J] . Hasse K., OConnell D., Neylon J., Medical Physics . 2018,第6期

机译：使用深度学习方法估计的患者特异性弹性分布量化剂量至功能性肺区
2. An Automated Method to Generate Patient-Specific Dose Distributions for Radiotherapy Using Deep Learning [J] . Chen X., Men K., Yi J., Medical Physics . 2018,第6期

机译：使用深度学习产生针对放射疗法的患者特异性剂量分布的自动化方法
3. Emphysema quantification on low-dose CT using percentage of low-attenuation volume and size distribution of low-attenuation lung regions: Effects of adaptive iterative dose reduction using 3D processing [J] . NishioM., MatsumotoS., SekiS., European Journal of Radiology . 2014,第12期

机译：低剂量CT的肺气肿定量使用低衰减肺区的低衰减容积和尺寸分布百分比：使用3D加工的自适应迭代剂量减少的影响
4. An automated technique for estimating patient-specific regional imparted energy and dose in TCM CT exams [C] . Jeremiah W. Sanders, Xiaoyu Tian, W. Paul Segars, Conference on physics of medical imaging . 2016

机译：一种自动技术，用于在中医CT检查中估计患者特定的区域传递的能量和剂量
5. Estimating the spatial distribution of snow water equivalent and snowmelt in mountainous watersheds of semi-arid regions. [D] . Molotch, Noah P. 2004

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6. A deep learning approach to estimate stress distribution: a fast and accurate surrogate of finite-element analysis [O] . Liang Liang, Minliang Liu, Caitlin Martin, 2018

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7. Deep Learning Method for Prediction of Patient-Specific Dose Distribution in Breast Cancer [O] . Sang Hee Ahn, EunSook Kim, Chankyu Kim, 2021

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Quantifying the Dose to Functional Lung Regions Using Patient-Specific Elasticity Distributions Estimated From a Deep Learning Approach

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