+ Site Statistics
+ Search Articles
+ Subscribe to Site Feeds
Most Shared
PDF Full Text
+ PDF Full Text
Request PDF Full Text
+ Follow Us
Follow on Facebook
Follow on Twitter
Follow on LinkedIn
+ Translate
+ Recently Requested

Registration of PET and CT images based on multiresolution gradient of mutual information demons algorithm for positioning esophageal cancer patients

Registration of PET and CT images based on multiresolution gradient of mutual information demons algorithm for positioning esophageal cancer patients

Journal of Applied Clinical Medical Physics 14(1): 3931

Accurate registration of 18F-FDG PET (positron emission tomography) and CT (computed tomography) images has important clinical significance in radiation oncology. PET and CT images are acquired from (18)F-FDG PET/CT scanner, but the two acquisition processes are separate and take a long time. As a result, there are position errors in global and deformable errors in local caused by respiratory movement or organ peristalsis. The purpose of this work was to implement and validate a deformable CT to PET image registration method in esophageal cancer to eventually facilitate accurate positioning the tumor target on CT, and improve the accuracy of radiation therapy. Global registration was firstly utilized to preprocess position errors between PET and CT images, achieving the purpose of aligning these two images on the whole. Demons algorithm, based on optical flow field, has the features of fast process speed and high accuracy, and the gradient of mutual information-based demons (GMI demons) algorithm adds an additional external force based on the gradient of mutual information (GMI) between two images, which is suitable for multimodality images registration. In this paper, GMI demons algorithm was used to achieve local deformable registration of PET and CT images, which can effectively reduce errors between internal organs. In addition, to speed up the registration process, maintain its robustness, and avoid the local extremum, multiresolution image pyramid structure was used before deformable registration. By quantitatively and qualitatively analyzing cases with esophageal cancer, the registration scheme proposed in this paper can improve registration accuracy and speed, which is helpful for precisely positioning tumor target and developing the radiation treatment planning in clinical radiation therapy application.

(PDF emailed within 0-6 h: $19.90)

Accession: 055446326

Download citation: RISBibTeXText

PMID: 23318381

DOI: 10.1120/jacmp.v14i1.3931

Related references

Multiresolution registration of remote sensing imagery by optimization of mutual information using a stochastic gradient. IEEE Transactions on Image Processing 12(12): 1495-1511, 2008

Registration of Brain MRI/PET Images Based on Adaptive Combination of Intensity and Gradient Field Mutual Information. International Journal of Biomedical Imaging 2007: 93479, 2007

Accuracy and reproducibility of co-registration techniques based on mutual information and normalized mutual information for MRI and SPECT brain images. Annals of Nuclear Medicine 18(8): 659-667, 2005

Effective incorporation of spatial information in a mutual information based 3D-2D registration of a CT volume to X-ray images. Medical Image Computing and Computer-Assisted Intervention 11(Pt 2): 922-929, 2008

Effective incorporating spatial information in a mutual information based 3D-2D registration of a CT volume to X-ray images. Computerized Medical Imaging and Graphics 34(7): 553-562, 2010

Optimization of mutual information for multiresolution image registration. IEEE Transactions on Image Processing 9(12): 2083-2099, 2008

Mutual-information-based registration of medical images: a survey. IEEE Transactions on Medical Imaging 22(8): 986-1004, 2003

Mutual information-based registration of temporal and stereo retinal images using constrained optimization. Computer Methods and Programs in Biomedicine 86(3): 210-215, 2007

Improved Demons Technique with Orthogonal Gradient Information for Medical Image Registration. Ieice Transactions on Information and Systems E93-D(12): 3414-3417, 2010

Comparative evaluation of multiresolution optimization strategies for multimodality image registration by maximization of mutual information. Medical Image Analysis 3(4): 373-386, 2000

Validation of mutual information-based registration of CT and bone SPECT images in dual-isotope studies. Computer Methods and Programs in Biomedicine 92(2): 173-185, 2008

Mutual information-based multimodality registration of cardiac ultrasound and SPECT images: a preliminary investigation. International Journal of Cardiovascular Imaging 19(6): 483-494, 2003

Multi-dimensional mutual information based robust image registration using maximum distance-gradient-magnitude. Information Processing in Medical Imaging 19: 210-221, 2007

Multimodality medical image registration and fusion techniques using mutual information and genetic algorithm-based approaches. Advances in Experimental Medicine and Biology 696: 441-449, 2011

Multi-modal medical image registration based on adaptive combination of intensity and gradient field mutual information. Conference Proceedings 1: 1429-1432, 2007