An enhanced block matching algorithm for fast elastic registration in adaptive radiotherapy.
Image registration has many medical applications in diagnosis, therapy planning and therapy. Especially for time-adaptive radiotherapy, an efficient and accurate elastic registration of images acquired for treatment planning, and at the time of the actual treatment, is highly desirable. Therefore, we developed a fully automatic and fast block matching algorithm which identifies a set of anatomical landmarks in a 3D CT dataset and relocates them in another CT dataset by maximization of local correlation coefficients in the frequency domain. To transform the complete dataset, a smooth interpolation between the landmarks is calculated by modified thin-plate splines with local impact. The concept of the algorithm allows separate processing of image discontinuities like temporally changing air cavities in the intestinal track or rectum. The result is a fully transformed 3D planning dataset (planning CT as well as delineations of tumour and organs at risk) to a verification CT, allowing evaluation and, if necessary, changes of the treatment plan based on the current patient anatomy without time-consuming manual re-contouring. Typically the total calculation time is less than 5 min, which allows the use of the registration tool between acquiring the verification images and delivering the dose fraction for online corrections. We present verifications of the algorithm for five different patient datasets with different tumour locations (prostate, paraspinal and head-and-neck) by comparing the results with manually selected landmarks, visual assessment and consistency testing. It turns out that the mean error of the registration is better than the voxel resolution (2 x 2 x 3 mm(3)). In conclusion, we present an algorithm for fully automatic elastic image registration that is precise and fast enough for online corrections in an adaptive fractionated radiation treatment course.
Malsch
U
U
Department of Medical Physics in Radiation Therapy, Deutsches Krebsforschungszentrum, DKFZ, Im Neuenheimer Feld 280, 69210 Heidelberg, Germany. u.malsch@dkfz.de
Thieke
C
C
Huber
P E
PE
Bendl
R
R
D000465:Algorithms; D005583:Fourier Analysis; D006258:Head and Neck Neoplasms / Q000175:diagnosis / Q000473:pathology; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008297:Male; D015233:Models, Statistical; D011471:Prostatic Neoplasms / Q000175:diagnosis / Q000473:pathology; D011874:Radiometry; D011878:Radiotherapy / Q000379:methods*; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods*; D013382:Subtraction Technique; D014057:Tomography, X-Ray Computed