Title :
Organ motion detection in CT images using opposite rays in fan-beam projection systems
Author :
Linney, N.C. ; Gregson, P.H.
Author_Institution :
Dept. of Math. & Comput. Sci., St. Mary´´s Univ., Halifax, NS, Canada
Abstract :
Motion artifacts have been identified as a problem in medical tomography systems. While computed tomography (CT) imaging has been getting faster, there remains a need to detect and compensate for motions in clinical follow-up of neurological patients (multiple sclerosis, tumors, stroke, etc.), in cardiac imaging, and in any area in which failing to detect a motion artifact may lead to misdiagnosis. The authors have developed a novel algorithm to detect motion in brain images. The algorithm deals with detecting and isolating motion in the object domain using only the information available in the sinogram domain. The new "opposite ray algorithm" (ORA) addresses the issue of motion in the interior elements of the object. The ORA combines information from projections that are opposite in space and separated in time to isolate and identify the motion. A sinogram of motion is created, integrated and reconstructed to isolate the moving component. The algorithm can be used with conventional clinical scanners employing quarter-detector offset. The significant effect of quarter-detector offset on the ORA is investigated. The effects that a finite beamwidth and noise have on the ORA are also investigated. Both the similarity index and a correlation coefficient are used to evaluate the algorithm. The algorithm is successful when applied to cases exhibiting translational and translational-rotational motion. A similarity index of 0.88 is obtained in a typical case with both translational and rotational motion. Further development is recommended in the deformation case.
Keywords :
biomechanics; brain; computerised tomography; image motion analysis; medical image processing; CT images; biomedical signal processing; cardiac imaging; deformation case; fan-beam projection systems; medical diagnostic imaging; motion sinogram; multiple sclerosis; neurological patients; opposite ray algorithm; opposite rays; organ motion detection; rotational motion; similarity index; stroke; translational motion; tumors; Biomedical imaging; Computed tomography; Geometry; Medical diagnostic imaging; Motion detection; Multiple sclerosis; Neoplasms; Object detection; Signal processing algorithms; X-ray imaging; Algorithms; Artifacts; Brain; Equipment Design; Fourier Analysis; Heart; Humans; Image Processing, Computer-Assisted; Lung; Models, Theoretical; Movement; Phantoms, Imaging; Rotation; Tomography, X-Ray Computed;
Journal_Title :
Medical Imaging, IEEE Transactions on