A Linogram/Sinogram Cross-Correlation Method for Motion Correction in Planar and SPECT Imaging

Abstract

In this work, a correlation function based on linograms and sinograms of the projection data was introduced, implemented and evaluated in order to estimate and compensate for the patient motion. Parabolic fitting of the peak of the correlation function was utilized to improve in the motion-estimation task. In dynamic planar imaging, the method checked for motion via its separate frames similar to the SPECT work; on the other hand, in static planar imaging, the data acquisition protocol was first exchanged from static to the dynamic modality, followed by application of the motion-correction scheme, and a final combination via summation of the motion-compensated frames. The method was successfully evaluated in many cases. Our tests showed that in SPECT imaging, the time of motion starting in a specific projection and the duration of motion are very important in the motion detection process. Measuring relative error showed that the error in the images with presence of motion along the axis of patient bed was 21.1%, being reduced to 1.4% while the 24.4% error along the perpendicular axis to the patient bed was reduced to 1.5% with the inclusion of our motion correction scheme. Experimental results in planar imaging also demonstrated the ability of this method to reduce error in the maximum count from 40.7% to 9.7%, wherein intended sudden motion was introduced in static planar acquisition. Similarly, the error produced by gradual simulated motion was reduced from 37% to 1.6%. This method was clinically examined in the bone scan (static planar data) of an old man for an Osteomyelitis study, as well as in a kidney washout study (dynamic planar data) for a child. As a result, the motion artifacts shown in the images were reduced considerably.

Computer Assisted Radiology-25th International Congress and Exhibition

“…They did this by estimating 6-DOF (degrees of freedom) parameters of the movement using the scaled sum squared-difference method. Other motion correction techniques Linogram-Sinogram Cross-Correlation method is suggested for SPECT imaging to counter the effects of rigid motion by Saeed Sarkar et al [10]. They used filtered-back projection to reconstruct the acquired data.…”

Real-time axial motion detection and correction for single photon emission computed tomography using a linear prediction filter

“…9 Sarkar et al proposed a method in which patient motions are estimated and compensated for using a correlation function based on linograms and sinograms of the projection data. 10 Gating, utilized for both computed tomography (CT) and magnetic resonance imaging (MRI) to reduce artifacts caused by cardiac and respiratory motion, uses a secondary source of information to measure the cardiac or respiratory cycle. 11 Attempts to reduce the image sequence scan time so motion becomes insignifi cant have fallen short of the goal.…”

Evaluation of Motion Correction Processing in Equine Bone Scintigraphy by Scheffé’s Method of Paired Comparisons

“…In addition, accumulation of radioisotopes is difficult to evaluate quantitatively; thus, scintigrams are often evaluated subjectively [1]. A motion correction (MC) processing system (MiE, Hamburg, Germany), which corrects for swaying motion immediately, was recently developed to obtain better images without increasing AT and without excessive dosage of radioisotopes [5]. A re-registration algorithm revealed corrected images for viewing simultaneously with the current acquisition, without the need of special hardware devices.…”

“…Overall scores of all the 5 observers were as follows: MC (−) AT 100% (lowest), MC (+) AT 25%, MC (+) AT 50%, MC (+) AT 75% and MC (+) AT 100% (highest). MC processing provides clear bone scintigrams, because it involves adjustment of the X-axis, Y-axis and rotation movement of each frame [5]. As a result, even MC (+) AT 25% resulted in higher scores compared with the scores MC (−) AT 100%.…”