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Autoadaptive phase‐correlated (AAPC) reconstruction for 4D CBCT
Author(s) -
Bergner Frank,
Berkus Timo,
Oelhafen Markus,
Kunz Patrik,
Pan Tinsu,
Kachelrieß Marc
Publication year - 2009
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.3260919
Subject(s) - artificial intelligence , iterative reconstruction , computer vision , computer science , rotation (mathematics) , image quality , noise (video) , image resolution , noise reduction , cone beam computed tomography , phase (matter) , optical flow , segmentation , motion estimation , motion (physics) , image (mathematics) , computed tomography , physics , medicine , radiology , quantum mechanics
Purpose: Kilovoltage cone‐beam computed tomography (CBCT) is widely used in image‐guided radiation therapy for exact patient positioning prior to the treatment. However, producing time series of volumetric images (4D CBCT) of moving anatomical structures remains challenging. The presented work introduces a novel method, combining high temporal resolution inside anatomical regions with strong motion and image quality improvement in regions with little motion. Methods: In the proposed method, the projections are divided into regions that are subject to motion and regions at rest. The latter ones will be shared among phase bins, leading thus to an overall reduction in artifacts and noise. An algorithm based on the concept of optical flow was developed to analyze motion‐induced changes between projections. The technique was optimized to distinguish patient motion and motion deriving from gantry rotation. The effectiveness of the method is shown in numerical simulations and patient data. Results: The images reconstructed from the presented method yield an almost the same temporal resolution in the moving volume segments as a conventional phase‐correlated reconstruction, while reducing the noise in the motionless regions down to the level of a standard reconstruction without phase correlation. The proposed simple motion segmentation scheme is yet limited to rotation speeds of less than 3 ° ∕ s . Conclusions: The method reduces the noise in the reconstruction and increases the image quality. More data are introduced for each phase‐correlated reconstruction, and therefore the applied dose is used more efficiently.