Generalized inter-frame and intra-frame motion correction in PET imaging - a simulation study

Author(s):  
Hassan Mohy-ud-Din ◽  
Nicolas A. Karakatsanis ◽  
Mohammed R. Ay ◽  
Christopher J. Endres ◽  
Dean F. Wong ◽  
...  
Author(s):  
Tao Sun ◽  
Yaping Wu ◽  
Yan Bai ◽  
Zhenguo Wang ◽  
Chushu Shen ◽  
...  

Abstract As a non-invasive imaging tool, Positron Emission Tomography (PET) plays an important role in brain science and disease research. Dynamic acquisition is one way of brain PET imaging. Its wide application in clinical research has often been hindered by practical challenges, such as patient involuntary movement, which could degrade both image quality and the accuracy of the quantification. This is even more obvious in scans of patients with neurodegeneration or mental disorders. Conventional motion compensation methods were either based on images or raw measured data, were shown to be able to reduce the effect of motion on the image quality. As for a dynamic PET scan, motion compensation can be challenging as tracer kinetics and relatively high noise can be present in dynamic frames. In this work, we propose an image-based inter-frame motion compensation approach specifically designed for dynamic brain PET imaging. Our method has an iterative implementation that only requires reconstructed images, based on which the inter-frame subject movement can be estimated and compensated. The method utilized tracer-specific kinetic modelling and can deal with simple and complex movement patterns. The synthesized phantom study showed that the proposed method can compensate for the simulated motion in scans with 18F-FDG, 18F-Fallypride and 18F-AV45. Fifteen dynamic 18F-FDG patient scans with motion artifacts were also processed. The quality of the recovered image was superior to the one of the non-corrected images and the corrected images with other image-based methods. The proposed method enables retrospective image quality control for dynamic brain PET imaging, hence facilitates the applications of dynamic PET in clinics and research.


2013 ◽  
Vol 40 (10) ◽  
pp. 102503 ◽  
Author(s):  
Xiao Jin ◽  
Tim Mulnix ◽  
Jean-Dominique Gallezot ◽  
Richard E. Carson

Author(s):  
Daniel Eiland ◽  
Debasis Mitra ◽  
Mahmoud Abdalah ◽  
Rostyslav Buchko ◽  
Grant T. Gullberg

Author(s):  
S. Suprijanto ◽  
M. W. Vogel ◽  
F. M. Vos ◽  
H. A. Vrooman ◽  
A. M. Vossepoel

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2608
Author(s):  
Héctor Espinós-Morató ◽  
David Cascales-Picó ◽  
Marina Vergara ◽  
Ángel Hernández-Martínez ◽  
José María Benlloch Baviera ◽  
...  

Positron emission tomography (PET) is a functional non-invasive imaging modality that uses radioactive substances (radiotracers) to measure changes in metabolic processes. Advances in scanner technology and data acquisition in the last decade have led to the development of more sophisticated PET devices with good spatial resolution (1–3 mm of full width at half maximum (FWHM)). However, there are involuntary motions produced by the patient inside the scanner that lead to image degradation and potentially to a misdiagnosis. The adverse effect of the motion in the reconstructed image increases as the spatial resolution of the current scanners continues improving. In order to correct this effect, motion correction techniques are becoming increasingly popular and further studied. This work presents a simulation study of an image motion correction using a frame-based algorithm. The method is able to cut the acquired data from the scanner in frames, taking into account the size of the object of study. This approach allows working with low statistical information without losing image quality. The frames are later registered using spatio-temporal registration developed in a multi-level way. To validate these results, several performance tests are applied to a set of simulated moving phantoms. The results obtained show that the method minimizes the intra-frame motion, improves the signal intensity over the background in comparison with other literature methods, produces excellent values of similarity with the ground-truth (static) image and is able to find a limit in the patient-injected dose when some prior knowledge of the lesion is present.


2020 ◽  
Author(s):  
Kailash Ramlaul ◽  
Alister Burt ◽  
Natàlia de Martín Garrido ◽  
James T. MacDonald ◽  
Colin M. Palmer ◽  
...  

AbstractWhile cryo-EM with modern direct electron detectors has proven incredibly powerful, becoming a dominant technique in structural biology, the analysis of cryo-EM images is significantly complicated by their exceptionally low signal-to-noise ratio, limiting the accuracy of the parameterisation of the physical models required for successful classification and reconstruction.Micrographs from modern direct electron detectors are typically collected as dose-fractionated multi-frame movies to allow the recording of separated individual electron impacts. These detectors improve electron detection and allow for both inter-frame motion correction, and dose-dependent image filtering, lessening the overall impact of effects deleterious to the recovery of high-resolution information.In this study we measured the information content at each spatial frequency in cryo-EM movies as it accrues during the course of an exposure. We show that, as well as correction for motion and radiation damage, the use of the information within movies allows substantially improved direct estimation of the remaining key image parameters required for accurate 3D reconstruction: the image CTF and spectral SNR.We are developing “CARYON” {insert contrived acronym here}, as a LAFTER-family filter for cryo-EM movies based upon such measurements. CARYON is intended to provide the best parameter estimation and filtration possible for a single complete, or large sub-section from a, movie micrograph without the use of a previously refined density. We demonstrate its utility in both single-particle and tomographic cryo-EM data processing.


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