重离子三维适形放疗中的图像处理关键技术研究
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摘要
放射治疗作为一种有效的肿瘤局部控制和治疗方式,与手术治疗、化疗组成了癌症治疗的三大最有效手段。相对于传统的χ,γ等放射线,重离子束以其对健康组织辐射损伤小、对肿瘤靶区杀伤力大、可准确定位和精确控制照射剂量,成为当今国际上最先进、最有效的放疗手段。基于医学图像处理的三维适形放疗计划系统是连接放疗硬件设备与临床治疗的纽带,是放疗专家赖以制定适形治疗方案必不可少的软件系统。论文重点针对重离子放疗中的相关医学图像处理关键算法进行了研究,并在此基础上研发了三维适形的重离子放疗计划系统。
在医学图像配准方面,论文针对乳房动态核磁共振成像(Dynamic Contrast Enhanced MRI, DCE MRI)数据量大、对配准算法速度要求高的问题,提出了将快速的Demons非刚性配准算法与图像强度校正相结合的乳房DCE MRI配准模型。该模型通过分析乳房内各组织在获取DCE MRI过程中信号增强的特点对图像强度校正,有效克服了乳房在核磁动态成像过程中由于组织强度发生变化而不适合用Demons算法进行配准的问题,为快速的乳房DCE MRI配准提供了一条新途径。
针对医学图像本质上具有模糊性和不均匀性的特点,尤其对于肿瘤靶区由于浸润健康组织使边缘模糊的问题,提出将神经网络与模糊推理方法相结合,并应用遗传算法对网络参数学习的多模医学图像融合算法。实验表明了该算法对于较为模糊图像融合的优越性。
论文从两个方面对Live-Wire交互式分割算法改进已提高Live-Wire算法的实时性：在最短路径的搜索过程中应用二叉堆排序,使算法的时间复杂度从原来的O[n2]降为O[nlog2 n]；在最短路径搜索中加入到达目标节点即停止的限制条件,可明显减少搜索节点数,使算法的时间复杂度小于O[nlog2 n]。经算法分析及实验表明,算法的改进显著提高了其运行效率。
在基于光线投射算法的医学图像体绘制算法中,将大的体数据分割成等大小的数据块,然后对每一数据块进行空白数据块的空间跳跃、提前数据块截止和提前光线截止等可见性测试来加快体绘制的速度,并使用体绘制预积分来提高体绘制的图像质量。实验结果表明,对大的体数据,可以在不损失图像质量的前提下,有效提高体绘制速度。
本文在放疗计划系统中,应用平行投影原理实现了二维坐标到世界坐标的转换。并提出以一测量端点为起始点的三维任意叠加旋转拾取第二个端点,实现了三维空间中两点间的交互式距离测量,取得了较高的测量精度,能够满足三维适形放疗要求。
在分析目前重离子放疗中使用的剂量计算模型的基础上,根据计算机断层扫描CT值和水等效深度的转换关系,在放疗计划系统中设计并实现了基于CT图像的重离子分层适形照射剂量分布计算及评估。通过定量分析呼吸运动对肺部重离子剂量分布的影响,说明由于重离子束的高生物学效应及高定位精度,重离子放疗比常规放疗更有必要采取呼吸控制措施以减少呼吸运动对精确放疗的影响。
在分析重离子放射治疗计划系统需求的基础上,对系统做了总体与详细设计,开发了基于医学图像处理的重离子放射治疗计划软件系统,为重离子放疗临床试验提供软件平台。医生可在该平台中导入病人各种模态的医学影像,最终自动生成临床放射治疗计划。
As an effective treatment measure to locally control and kill tumor, radiotherapy together with operationtherapy and chemotherapy are considered as most powerful remedy for tumor. Compared with conventional beam radiotherapy withχ,γand photons etc., heavy-ion radiotherapy introduces less damage on healthy tissues, more destruction on tumor, more accurate positioning on tumor volume and more precise controlling radiation dose. Therefore, heavy-ion has become most advanced and effective radiation beam for radiotherapy.3D conformal radiation treatment planning system(RTPS) based on the medical image processing is the key connection between the radiotherapy hardware device and clinical treatment. It is necessary for radiotherapist to make conformal treatment plan on the system. The dissertation focused on the key medical image processing algorithm for heavy-ion RTPS and development of the RTPS.
In order to improve the registration speed of breast dynamic contrast enhancement magnetic resonance images(DCE MRI), the dissertation presents a registration model for breast DCE MRI using fast Demons non-rigid registration algorithm with intensity correction. Original Demons is based on intensity change to get deformation parameters and unsuitable for breast DCE MRI. Intensity correction between pre and post contrast images based on polynomial is suggested to overcome the problem according to the signal enhancement of the breast model. The presented approach provides a novel method for the registration of DCE MRI.
Based on the method of Fuzzy inference and radial basis function neural networks (RBFNN), the dissertation puts forward a new method for multimodal medical image fusion. Medical images are inherently ambiguous and non-uniform, especially for tumor,the border of which is usually fuzzy because of the soakage from the tumor to healthy tissue. The superiority of intelligent algorithm of fuzzy inference and RBFNN is integrated to perform auto-adaptive image fusion. Global genetic algorithm (GA) is employed to train the networks. Experimental results show that the proposed approach is more superiorer for fusion of multimodal medical images, especially for blurry source images.
The paper improves interactive Live-Wire segmentation algorithm in two aspects: heap sort is used for searching the globally optimal path from the start node to the goal node, and the time complexity of the algorithm can be reduced from O[n2] to O[nlog2 n] by the algorithm, the restriction condition that the search stops immediately with the find of the destination node,is set up to greatly reduce searched nodes, thus the time complexity is reduced to less than O[nlog2 n]. Algorithm analysis and experiments indicate that the presented search strategy can evidently improve the speed of Live-Wire algorithm.
A fast volume rendering algorithm based on Ray Casting is presented in the dissertation. Firstly, the large medical volume data is divided into equal-size blocks, and then a set of visibility tests such as empty block space skipping, early block termination and early ray termination are used to speed up the whole rendering process. Finally, volume rendering pre-integration is utilized to improve the performance of volume rendering. The experiment results show that the proposed fast volume rendering has picked up the speed of rendering for a large medical volume data without loss of image quality.
The dissertation applies parallel projection theory to realize the coordinate transformation from 2-D to 3-D, and proposes a 3-D arbitrary superimposed rotation algorithm which uses one measurement extreme point as origin to pick another one. 3-D precise measurement is realized in heavy-ion RTPS. The algorithm is accurate enough to reach the requirement of 3D conformal radiation therapy.
By analyzing the model of heavy-ion dose calculation, based on the transformational relation between CT value and water-equivalent path length, this work designs and realizes the calculation and visualization of heavy dose distribution for 3D superimposed conformal irradiation and dose evaluation on CT image.By conducting how respiratory motion affects the dosimetric distribution on target and critical tissues during heavy ion radiotherapy, the work illuminates that because of the high RBE and positioning accuracy of heavy-ion beam, it is more necessary for heavy ion radiotherapy than traditional radiotherapy to take respiratory control measures to reduce the affect on exact radioation therapy.
Based on the systemical requirement analysis of heavy-ion radiotherapy TPS in Institute of Modern Physics, overall design of the TPS and detailed design is conducted in the dissertation. And heavy-ion TPS based on medical image processing has developed to provide a platform for heavy ion radiotherapy clinical trials. Radiotherapist can import multimodal medical images to the system to design conveniently a clinical treatment plan for patient.
在医学图像配准方面,论文针对乳房动态核磁共振成像(Dynamic Contrast Enhanced MRI, DCE MRI)数据量大、对配准算法速度要求高的问题,提出了将快速的Demons非刚性配准算法与图像强度校正相结合的乳房DCE MRI配准模型。该模型通过分析乳房内各组织在获取DCE MRI过程中信号增强的特点对图像强度校正,有效克服了乳房在核磁动态成像过程中由于组织强度发生变化而不适合用Demons算法进行配准的问题,为快速的乳房DCE MRI配准提供了一条新途径。
针对医学图像本质上具有模糊性和不均匀性的特点,尤其对于肿瘤靶区由于浸润健康组织使边缘模糊的问题,提出将神经网络与模糊推理方法相结合,并应用遗传算法对网络参数学习的多模医学图像融合算法。实验表明了该算法对于较为模糊图像融合的优越性。
论文从两个方面对Live-Wire交互式分割算法改进已提高Live-Wire算法的实时性：在最短路径的搜索过程中应用二叉堆排序,使算法的时间复杂度从原来的O[n2]降为O[nlog2 n]；在最短路径搜索中加入到达目标节点即停止的限制条件,可明显减少搜索节点数,使算法的时间复杂度小于O[nlog2 n]。经算法分析及实验表明,算法的改进显著提高了其运行效率。
在基于光线投射算法的医学图像体绘制算法中,将大的体数据分割成等大小的数据块,然后对每一数据块进行空白数据块的空间跳跃、提前数据块截止和提前光线截止等可见性测试来加快体绘制的速度,并使用体绘制预积分来提高体绘制的图像质量。实验结果表明,对大的体数据,可以在不损失图像质量的前提下,有效提高体绘制速度。
本文在放疗计划系统中,应用平行投影原理实现了二维坐标到世界坐标的转换。并提出以一测量端点为起始点的三维任意叠加旋转拾取第二个端点,实现了三维空间中两点间的交互式距离测量,取得了较高的测量精度,能够满足三维适形放疗要求。
在分析目前重离子放疗中使用的剂量计算模型的基础上,根据计算机断层扫描CT值和水等效深度的转换关系,在放疗计划系统中设计并实现了基于CT图像的重离子分层适形照射剂量分布计算及评估。通过定量分析呼吸运动对肺部重离子剂量分布的影响,说明由于重离子束的高生物学效应及高定位精度,重离子放疗比常规放疗更有必要采取呼吸控制措施以减少呼吸运动对精确放疗的影响。
在分析重离子放射治疗计划系统需求的基础上,对系统做了总体与详细设计,开发了基于医学图像处理的重离子放射治疗计划软件系统,为重离子放疗临床试验提供软件平台。医生可在该平台中导入病人各种模态的医学影像,最终自动生成临床放射治疗计划。
As an effective treatment measure to locally control and kill tumor, radiotherapy together with operationtherapy and chemotherapy are considered as most powerful remedy for tumor. Compared with conventional beam radiotherapy withχ,γand photons etc., heavy-ion radiotherapy introduces less damage on healthy tissues, more destruction on tumor, more accurate positioning on tumor volume and more precise controlling radiation dose. Therefore, heavy-ion has become most advanced and effective radiation beam for radiotherapy.3D conformal radiation treatment planning system(RTPS) based on the medical image processing is the key connection between the radiotherapy hardware device and clinical treatment. It is necessary for radiotherapist to make conformal treatment plan on the system. The dissertation focused on the key medical image processing algorithm for heavy-ion RTPS and development of the RTPS.
In order to improve the registration speed of breast dynamic contrast enhancement magnetic resonance images(DCE MRI), the dissertation presents a registration model for breast DCE MRI using fast Demons non-rigid registration algorithm with intensity correction. Original Demons is based on intensity change to get deformation parameters and unsuitable for breast DCE MRI. Intensity correction between pre and post contrast images based on polynomial is suggested to overcome the problem according to the signal enhancement of the breast model. The presented approach provides a novel method for the registration of DCE MRI.
Based on the method of Fuzzy inference and radial basis function neural networks (RBFNN), the dissertation puts forward a new method for multimodal medical image fusion. Medical images are inherently ambiguous and non-uniform, especially for tumor,the border of which is usually fuzzy because of the soakage from the tumor to healthy tissue. The superiority of intelligent algorithm of fuzzy inference and RBFNN is integrated to perform auto-adaptive image fusion. Global genetic algorithm (GA) is employed to train the networks. Experimental results show that the proposed approach is more superiorer for fusion of multimodal medical images, especially for blurry source images.
The paper improves interactive Live-Wire segmentation algorithm in two aspects: heap sort is used for searching the globally optimal path from the start node to the goal node, and the time complexity of the algorithm can be reduced from O[n2] to O[nlog2 n] by the algorithm, the restriction condition that the search stops immediately with the find of the destination node,is set up to greatly reduce searched nodes, thus the time complexity is reduced to less than O[nlog2 n]. Algorithm analysis and experiments indicate that the presented search strategy can evidently improve the speed of Live-Wire algorithm.
A fast volume rendering algorithm based on Ray Casting is presented in the dissertation. Firstly, the large medical volume data is divided into equal-size blocks, and then a set of visibility tests such as empty block space skipping, early block termination and early ray termination are used to speed up the whole rendering process. Finally, volume rendering pre-integration is utilized to improve the performance of volume rendering. The experiment results show that the proposed fast volume rendering has picked up the speed of rendering for a large medical volume data without loss of image quality.
The dissertation applies parallel projection theory to realize the coordinate transformation from 2-D to 3-D, and proposes a 3-D arbitrary superimposed rotation algorithm which uses one measurement extreme point as origin to pick another one. 3-D precise measurement is realized in heavy-ion RTPS. The algorithm is accurate enough to reach the requirement of 3D conformal radiation therapy.
By analyzing the model of heavy-ion dose calculation, based on the transformational relation between CT value and water-equivalent path length, this work designs and realizes the calculation and visualization of heavy dose distribution for 3D superimposed conformal irradiation and dose evaluation on CT image.By conducting how respiratory motion affects the dosimetric distribution on target and critical tissues during heavy ion radiotherapy, the work illuminates that because of the high RBE and positioning accuracy of heavy-ion beam, it is more necessary for heavy ion radiotherapy than traditional radiotherapy to take respiratory control measures to reduce the affect on exact radioation therapy.
Based on the systemical requirement analysis of heavy-ion radiotherapy TPS in Institute of Modern Physics, overall design of the TPS and detailed design is conducted in the dissertation. And heavy-ion TPS based on medical image processing has developed to provide a platform for heavy ion radiotherapy clinical trials. Radiotherapist can import multimodal medical images to the system to design conveniently a clinical treatment plan for patient.
引文
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