Generalized dynamic PET inter-frame and intra-frame motion correction - Phantom and human validation studies

Author(s):  
Hassan Mohy-ud-Din ◽  
Nicolas A. Karakatsanis ◽  
James S. Goddard ◽  
Justin Baba ◽  
William Wills ◽  
...  
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.


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

Author(s):  
Hassan Mohy-ud-Din ◽  
Nicolas A. Karakatsanis ◽  
Mohammed R. Ay ◽  
Christopher J. Endres ◽  
Dean F. Wong ◽  
...  

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

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.


2019 ◽  
Vol 78 ◽  
pp. 22-31 ◽  
Author(s):  
Peng Liu ◽  
Guoyu Wang ◽  
Zhibin Yu ◽  
Xinchang Guo ◽  
Weigang Lu

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Sagi Monin ◽  
Evgeny Hahamovich ◽  
Amir Rosenthal

AbstractSingle-pixel imaging (SPI) enables the visualization of objects with a single detector by using a sequence of spatially modulated illumination patterns. For natural images, the number of illumination patterns may be smaller than the number of pixels when compressed-sensing algorithms are used. Nonetheless, the sequential nature of the SPI measurement requires that the object remains static until the signals from all the required patterns have been collected. In this paper, we present a new approach to SPI that enables imaging scenarios in which the imaged object, or parts thereof, moves within the imaging plane during data acquisition. Our algorithms estimate the motion direction from inter-frame cross-correlations and incorporate it in the reconstruction model. Moreover, when the illumination pattern is cyclic, the motion may be estimated directly from the raw data, further increasing the numerical efficiency of the algorithm. A demonstration of our approach is presented for both numerically simulated and measured data.


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