PET-CT image registration in the chest using free-form deformations

• Published in: IEEE transactions on medical imaging Vol. 22; no. 1; pp. 120 - 128
• Main Authors: Mattes, D., Haynor, D.R., Vesselle, H., Lewellen, T.K., Eubank, W.
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.01.2003; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Biological and medical sciences; Carcinoma, Non-Small-Cell Lung - diagnostic imaging; Closed-form solution; Deformable models; Deformation; Fluorodeoxyglucose F18; Histograms; Humans; Image registration; Image resolution; Lung Neoplasms - diagnostic imaging; Lungs; Medical sciences; Motion; Mutual information; Optimization algorithms; Positron emission tomography; Protocols; Radiography, Thoracic - methods; Radiopharmaceuticals; Spline; Subtraction Technique; Thorax - diagnostic imaging; Tomography, Emission-Computed - methods; Validation studies
• ISSN: 0278-0062; 1558-254X
• DOI: 10.1109/TMI.2003.809072

We have implemented and validated an algorithm for three-dimensional positron emission tomography transmission-to-computed tomography registration in the chest, using mutual information as a similarity criterion. Inherent differences in the two imaging protocols produce significant nonrigid motion between the two acquisitions. A rigid body deformation combined with localized cubic B-splines is used to capture this motion. The deformation is defined on a regular grid and is parameterized by potentially several thousand coefficients. Together with a spline-based continuous representation of images and Parzen histogram estimates, our deformation model allows closed-form expressions for the criterion and its gradient. A limited-memory quasi-Newton optimization algorithm is used in a hierarchical multiresolution framework to automatically align the images. To characterize the performance of the method, 27 scans from patients involved in routine lung cancer staging were used in a validation study. The registrations were assessed visually by two expert observers in specific anatomic locations using a split window validation technique. The visually reported errors are in the 0- to 6-mm range and the average computation time is 100 min on a moderate-performance workstation.