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首页> 外文会议>International Symposium on Medical Information Processing and Analysis >Intrapatient multimodal medical image registration of brain CT-MRI 3D: an approach based on metaheuristics
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Intrapatient multimodal medical image registration of brain CT-MRI 3D: an approach based on metaheuristics

机译：脑CT-MRI 3D的内裤多模式医学图像登记：一种基于殖民学的方法

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Medical Image Registration (MIR) is a challenge that arises in many image processing applications when multiple images must be aligned. We deal with the case of multi-modalities that is approached as an optimization problem. In MIR deterministic algorithms are used mainly, the disadvantage is that many of them get trapped in local optima, especially in multi-modal registration. This work aims to overcome this disadvantage using Scatter Search and Particle Swarm as optimization algorithms, with the mutual information approach proposed by Mattes et. al. The proposed optimizers were tested and contrasted with Reference Algorithms. A multi-modal rigid 3D / 3D of brain medical image registration scheme was implemented, and it was validated in RIRE project. The qualitative and quantitative validation of the results was satisfactory; the results demonstrated the accuracy and applicability of the proposed methods in comparison to conventional methods, as well as not being trapped in local optima.
机译：医学图像登记（MIR）是一种挑战，当必须对齐多个图像时，在许多图像处理应用中产生的挑战。我们处理与优化问题接近的多模态的情况。在MIR确定性算法主要使用的是，缺点是其中许多人被困在本地最优，特别是在多模态注册中。这项工作旨在克服散点搜索和粒子作为优化算法的这种缺点，具有Mattes et提出的相互信息方法。 al。将所提出的优化器与参考算法进行测试和对比。实现了大脑医学图像登记方案的多模态刚性3D / 3D，并在reire项目中验证。结果的定性和量化验证令人满意;结果表明，与常规方法相比，所提出的方法的准确性和适用性，以及不被捕获在局部最佳方法中。

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