Bai Wenjia, Brady Michael
Wolfson Medical Vision Laboratory, Department of Engineering Science, University of Oxford, Oxford, OX1 3PJ, UK.
Phys Med Biol. 2009 May 7;54(9):2719-36. doi: 10.1088/0031-9155/54/9/008. Epub 2009 Apr 8.
A major challenge in thoracic PET imaging is respiratory motion, which degrades image quality to the extent that it can affect subsequent diagnosis and patient management. This paper presents an approach to overcoming this problem using a deformable registration algorithm for respiratory gated PET images. Registration is based entirely on PET images without increasing the radiation burden. A Markov random field regularizer is introduced to the registration, which penalizes noisy deformation fields. Experimental results on both simulated and real data show that regularized registration effectively suppresses the noise in images, yielding satisfactory deformation fields. In addition, motion correction using the registration algorithm significantly improves the quality of PET images.
胸部正电子发射断层显像（PET）成像中的一个主要挑战是呼吸运动，它会降低图像质量，进而影响后续诊断和患者管理。本文提出了一种使用可变形配准算法处理呼吸门控PET图像来克服这一问题的方法。配准完全基于PET图像，而不会增加辐射负担。在配准中引入了马尔可夫随机场正则化器，它会抑制有噪声的变形场。在模拟数据和真实数据上的实验结果表明，正则化配准有效地抑制了图像中的噪声，产生了令人满意的变形场。此外，使用该配准算法进行运动校正可显著提高PET图像的质量。
