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Reliability-Driven, Spatially-Adaptive Regularization for Deformable Registration

机译：可靠性驱动，空间自适应正则化以实现可变形配准

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We propose a reliability measure that identifies informative image cues useful for registration, and present a novel, data-driven approach to spatially adapt regularization to the local image content via use of the proposed measure. We illustrate the generality of this adaptive regularization approach within a powerful discrete optimization framework and present various ways to construct a spatially varying regularization weight based on the proposed measure. We evaluate our approach within the registration process using synthetic experiments and demonstrate its utility in real applications. As our results demonstrate, our approach yielded higher registration accuracy than non-adaptive approaches and the proposed reliability measure performed robustly even in the presences of noise and intensity inhomogenity.

机译：我们提出了一种可靠性措施，该措施可识别可用于注册的信息图像线索，并提出一种新颖的数据驱动方法，以通过使用所提出的措施在空间上使正则化适应本地图像内容。我们在强大的离散优化框架内说明了这种自适应正则化方法的一般性，并提出了多种基于拟议措施构建空间变化的正则化权重的方法。我们使用合成实验在注册过程中评估我们的方法，并证明其在实际应用中的效用。正如我们的结果所示，与非自适应方法相比，我们的方法产生更高的配准精度，并且即使在存在噪声和强度不均匀性的情况下，所提出的可靠性措施也可以很好地执行。

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来源
《Biomedical image registration》|2010年|p.173-185|共13页
会议地点 Lubeck(DE);Lubeck(DE)
作者
Lisa Tang; Ghassan Hamarneh; Rafeef Abugharbieh;
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作者单位

Medical Image Analysis Lab., School Computing Science, Simon Eraser University;

Medical Image Analysis Lab., School Computing Science, Simon Eraser University;

Biomedical Signal and Image Computing Lab., Department of Electrical and Computer Engineering, University of British Columbia;

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原文格式 PDF
正文语种 eng
中图分类医用物理学;
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2. Estimation of Large Motion in Lung CT by Integrating Regularized Keypoint Correspondences into Dense Deformable Registration [J] . Jan Rühaak, Thomas Polzin, Stefan Heldmann, IEEE Transactions on Medical Imaging . 2017,第8期

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3. Regularization in deformable registration of biomedical images based on divergence and curl operators [J] . Riyahi-AlamS., PeroniM., BaroniG., Methods of information in medicine . 2014,第1期

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4. Reliability-Driven, Spatially-Adaptive Regularization for Deformable Registration [C] . Lisa Tang, Ghassan Hamarneh, Rafeef Abugharbieh International Workshop on Biomedical Image Registration . 2010

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5. Estimation of the Delivered Dose in Prostate Cancer Patients Treated With IMRT/VMAT Using Deformable Image Registration: Dosimetric and Clinical Considerations [D] . Hammers, Jacob Elliott. 2019

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7. Reliability-driven, spatially-adaptive regularization for deformable registration [O] . Lisa Tang, Ghassan Hamarneh, Rafeef Abugharbieh 2011

机译：可靠性驱动的空间自适应正则化，用于可变形配准

Reliability-Driven, Spatially-Adaptive Regularization for Deformable Registration

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