首页> 外文会议>Hellenic Conference on AI(Artificial Intellignece)(SENTN 2004); 20040505-20040508; Samos; GR >Automated Medical Image Registration Using the Simulated Annealing Algorithm
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Automated Medical Image Registration Using the Simulated Annealing Algorithm

机译:使用模拟退火算法自动进行医学图像配准

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This paper presents a robust, automated registration algorithm, which may be applied to several types of medical images, including CTs, MRIs, X-rays, Ultrasounds and dermatological images. The proposed algorithm is intended for imaging modalities depicting primarily morphology of objects i.e. tumors, bones, cysts and lesions that are characterized by translation, scaling and rotation. An efficient deterministic algorithm is used in order to decouple these effects by transforming images into the log-polar Fourier domain. Then, the correlation coefficient function criterion is employed and the corresponding values of scaling and rotation are detected. Due to the non-linearity of the correlation coefficient function criterion and the heavy computational effort required for its full enumeration, this optimization problem is solved using an efficient simulated annealing algorithm. After the images alignment in scaling and rotation, the simulated annealing algorithm is employed again, in order to detect the remaining values of the horizontal and vertical shifting. The proposed algorithm was tested using different initialization schemes and resulted in fast convergence to the optimal solutions independently of the initial points.
机译:本文提出了一种鲁棒的,自动的配准算法,该算法可应用于多种类型的医学图像,包括CT,MRI,X射线,超声和皮肤病学图像。提出的算法旨在用于成像模态,其主要描绘对象的形态,即以平移,缩放和旋转为特征的肿瘤,骨骼,囊肿和病变。使用有效的确定性算法,以通过将图像转换为对数极性傅里叶域来消除这些影响。然后,采用相关系数函数准则,并检测缩放和旋转的相应值。由于相关系数函数准则的非线性以及对其进行完整枚举所需的繁重计算工作,因此,使用有效的模拟退火算法可以解决此优化问题。在按比例缩放和旋转图像对齐之后,再次使用模拟退火算法,以检测水平和垂直偏移的剩余值。使用不同的初始化方案对提出的算法进行了测试,并导致与初始点无关的快速收敛到最优解。

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