Results 21 to 30 of about 1,184,230 (332)
Sensors, 2021 In this paper, we use Frame Theory to develop a generalized OCT image reconstruction method using redundant and non-uniformly spaced frequency domain samples that includes using non-redundant and uniformly spaced samples as special cases. We also correct
Karim Nagib +4 more
doaj +1 more source
Sparse Image Reconstruction for Molecular Imaging [PDF]
IEEE Transactions on Image Processing, 2009 12 pages, 8 ...
Raviv Raich +2 more
openaire +3 more sources
On Hallucinations in Tomographic Image Reconstruction
IEEE Transactions on Medical Imaging, 2021 Tomographic image reconstruction is generally an ill-posed linear inverse problem. Such ill-posed inverse problems are typically regularized using prior knowledge of the sought-after object property. Recently, deep neural networks have been actively investigated for regularizing image reconstruction problems by learning a prior for the object ...
Sayantan Bhadra +3 more
openaire +5 more sources
Journal of Applied Clinical Medical Physics, Volume 23, Issue 12, December 2022., 2022 Abstract Background and purpose For postoperative breast cancer patients, deformable image registration (DIR) is challenged due to the large deformations and non‐correspondence caused by tumor resection and clip insertion. To deal with it, three metrics (fiducial‐, region‐, and intensity‐based) were jointly used in DIR algorithm for improved accuracy ...
Xin Xie +6 more
wiley +1 more source
Computational Imaging for VLBI Image Reconstruction [PDF]
2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016 Accepted for publication at CVPR 2016, Project Website: http://vlbiimaging.csail.mit.edu/, Video of Oral Presentation at CVPR June 2016: https://www.youtube.com/watch?v ...
Bouman, Katherine L. +5 more
openaire +6 more sources
Stability of Image-Reconstruction Algorithms
IEEE Transactions on Computational Imaging, 2023 Robustness and stability of image-reconstruction algorithms have recently come under scrutiny. Their importance to medical imaging cannot be overstated. We review the known results for the topical variational regularization strategies ($\ell_2$ and $\ell_1$ regularization) and present novel stability results for $\ell_p$-regularized linear inverse ...
Pol del Aguila Pla +2 more
openaire +3 more sources
Image quality improvement in low‐dose chest CT with deep learning image reconstruction
Journal of Applied Clinical Medical Physics, Volume 23, Issue 12, December 2022., 2022 Abstract Objectives To investigate the clinical utility of deep learning image reconstruction (DLIR) for improving image quality in low‐dose chest CT in comparison with 40% adaptive statistical iterative reconstruction‐Veo (ASiR‐V40%) algorithm. Methods This retrospective study included 86 patients who underwent low‐dose CT for lung cancer screening ...
Qian Tian +7 more
wiley +1 more source
Artificial Intelligence-Based Image Reconstruction in Cardiac Magnetic Resonance [PDF]
, 2022 Artificial intelligence (AI) and Machine Learning (ML) have shown great potential in improving the medical imaging workflow, from image acquisition and reconstruction to disease diagnosis and treatment. Particularly, in recent years, there has been a significant growth in the use of AI and ML algorithms, especially Deep Learning (DL) based methods, for
arxiv +1 more source
Journal of Applied Clinical Medical Physics, Volume 23, Issue 12, December 2022., 2022 Abstract Purpose To assess whether the joint application of hybrid iterative reconstruction (HIR) and an adaptive filter (AF) could reduce streak artifacts and improve image quality of neck‐and‐shoulder computed tomography (CT). Methods This study included 96 patients with suspicious neck lesions who underwent a routine nonenhanced scan on a 64‐slice ...
Wenfeng Jin +6 more
wiley +1 more source
Journal of Applied Clinical Medical Physics, Volume 23, Issue 12, December 2022., 2022 Abstract Purpose The aim of this work was to evaluate the SunCHECK PerFRACTION, the software for in vivo monitoring using EPID images. Materials/Methods First, the PerFRACTION ability to detect errors was investigated simulating two situations: (1) variation of LINAC output and (2) variation of the phantom thickness.
Samuel Ramalho Avelino +3 more
wiley +1 more source