scholarly journals Motion estimation and correction for simultaneous PET/MR using SIRF and CIL

2021 ◽  
Vol 379 (2204) ◽  
pp. 20200208 ◽  
Author(s):  
Richard Brown ◽  
Christoph Kolbitsch ◽  
Claire Delplancke ◽  
Evangelos Papoutsellis ◽  
Johannes Mayer ◽  
...  
Keyword(s):  
Image Reconstruction ◽  
Motion Estimation ◽  
Motion Correction ◽  
Mr Image ◽  
New Developments ◽  
Tomographic Image Reconstruction ◽  
Processing Data ◽  
Novel Algorithms ◽  
New Algorithms ◽  
Estimation And Correction

SIRF is a powerful PET/MR image reconstruction research tool for processing data and developing new algorithms. In this research, new developments to SIRF are presented, with focus on motion estimation and correction. SIRF’s recent inclusion of the adjoint of the resampling operator allows gradient propagation through resampling, enabling the MCIR technique. Another enhancement enabled registering and resampling of complex images, suitable for MRI. Furthermore, SIRF’s integration with the optimization library CIL enables the use of novel algorithms. Finally, SPM is now supported, in addition to NiftyReg, for registration. Results of MR and PET MCIR reconstructions are presented, using FISTA and PDHG, respectively. These demonstrate the advantages of incorporating motion correction and variational and structural priors. This article is part of the theme issue ‘Synergistic tomographic image reconstruction: part 2’.

scholarly journals Axial motion estimation and correction for simultaneous multi-plane two-photon calcium imaging

2021 ◽  
Author(s):  
Andres Flores-Valle ◽  
Johannes D Seelig
Keyword(s):  
Motion Estimation ◽  
Fluorescence Intensity ◽  
Neural Activity ◽  
Focal Plane ◽  
Motion Correction ◽  
Axial Motion ◽  
Two Photon ◽  
Brain Motion ◽  
Calcium Indicators ◽  
Estimation And Correction

Two-photon imaging in behaving animals is typically accompanied by brain motion. For functional imaging experiments, for example with genetically encoded calcium indicators, such brain motion induces changes in fluorescence intensity. These motion related intensity changes or motion artifacts cannot easily be separated from neural activity induced signals. While lateral motion within the focal plane can be corrected by computationally aligning images, axial motion, out of the focal plane, cannot easily be corrected. Here, we develop an algorithm for axial motion correction for non-ratiometric calcium indicators taking advantage of simultaneous multi-plane imaging. Using at least two simultaneously recorded focal planes, the algorithm separates motion related and neural activity induced changes in fluorescence intensity. The developed motion correction approach allows axial motion estimation and correction at high frame rates for isolated structures in the imaging volume in vivo, such as sparse expression patterns in the fruit fly brain.

Zero-filling Technique in Fresnel Transfrom Image Reconstruction for MR Image Denoising

PIERS Online ◽  
2005 ◽  
Vol 1 (4) ◽  
pp. 473-477
Author(s):  
Bin-Rong Wu ◽  
Satoshi Ito ◽  
Yoshitsugu Kamimura ◽  
Yoshifumi Yamada
Keyword(s):  
Image Reconstruction ◽  
Image Denoising ◽  
Mr Image

scholarly journals Results of the 2020 fastMRI Challenge for Machine Learning MR Image Reconstruction

2021 ◽  
pp. 1-1
Author(s):  
Matthew J. Muckley ◽  
Bruno Riemenschneider ◽  
Alireza Radmanesh ◽  
Sunwoo Kim ◽  
Geunu Jeong ◽  
...  
Keyword(s):  
Machine Learning ◽  
Image Reconstruction ◽  
Mr Image ◽  
Mr Image Reconstruction

scholarly journals Efficient feature-based motion estimation in neurosurgery using non-maximum suppression

2018 ◽  
Vol 4 (1) ◽  
pp. 555-558 ◽  
Author(s):  
Fang Chen ◽  
Jan Müller ◽  
Jens Müller ◽  
Ronald Tetzlaff
Keyword(s):  
Motion Estimation ◽  
Thermal Imaging ◽  
Motion Correction ◽  
Processing Time ◽  
Feature Detection ◽  
Detection Efficiency ◽  
Adaptive Method ◽  
Time Performance ◽  
Key Points ◽  
Feature Based

AbstractIn this contribution we propose a feature-based method for motion estimation and correction in intraoperative thermal imaging during brain surgery. The motion is estimated from co-registered white-light images in order to perform a robust motion correction on the thermographic data. To ensure real-time performance of an intraoperative application, we optimise the processing time which essentially depends on the number of key points found by our algorithm. For this purpose we evaluate the effect of applying an non-maximum suppression (NMS) to improve the feature detection efficiency. Furthermore we propose an adaptive method to determine the size of the suppression area, resulting in a trade-off between accuracy and processing time.

Sign in / Sign up

Export Citation Format

Share Document