#RISK OF RAIN ARTIFACTS PATTERNS REGISTRATION#

The authors report on the application of a respiratory motion model to produce an RCCT image set with reduced artifacts and without missing data. Sorting based on the displacement of the respiratory signal yields slices at more consistent respiratory motion states and hence reduces artifacts, but missing image data (gaps) may occur.

Respiration-correlated CT (RCCT) images produced with commonly used phase-based sorting of CT slices often exhibit discontinuity artifacts between CT slices, caused by cycle-to-cycle amplitude variations in respiration. Hertanto, Agung Zhang, Qinghui Hu, Yu-Chi Dzyubak, Oleksandr Rimner, Andreas Mageras, Gig S Reduction of irregular breathing artifacts in respiration-correlated CT images using a respiratory motion model. The proposed motion model was quantitatively validated on 4D CT images of a phantom and a The initial large discrepancies across the landmark pairs were significantly reduced after deformable registration, and the accuracy was similar to or better than that reported by state-of-the-art methods.

#RISK OF RAIN ARTIFACTS PATTERNS REGISTRATION#

The authors evaluated the performance of the in-house deformable image registration method using benchmark datasets consisting of ten 4D CT sets annotated with 300 landmark pairs that were approved by physicians. Finally, the displacement vector fields were used to deform the reference CT image to synthesize CT images at the selected phase with much reduced image artifacts.

These projections were parameterized using a spline model to allow the reconstruction of the displacement vector fields at any given phase in a respiratory cycle. The authors have demonstrated that the regular respiratory motion of a patient can be accurately represented by a subspace spanned by three principal motion bases and their projections. The authors then used PCA to decompose each of the displacement vector fields into linear combinations of principal motion bases. For a 4D CT image set of a specific patient, the authors calculated displacement vector fields relative to a reference phase, using an in-house deformable image registration method. In this study, the authors present a patient-specific respiratory motion model, based on principal component analysis (PCA) of motion vectors obtained from deformable image registration, with the main goal of reducing image artifacts caused by irregular motion during 4D CT acquisition. However, significant image distortions ( artifacts) exist in 4D CT images that may affect accurate tumor delineation and the shape representation of normal anatomy. Zhang, Yongbin Yang, Jinzhong Zhang, Lifei Court, Laurence E Balter, Peter A Dong, Leiįour-dimensional computed tomography (4D CT) images have been recently adopted in radiation treatment planning for thoracic and abdominal cancers to explicitly define respiratory motion and anatomy deformation. Modeling respiratory motion for reducing motion artifacts in 4D CT images.

Risk of rain artifacts patterns