Truncation effect reduction for fast iterative reconstruction in cone-beam CT
BMC Medical Imaging, 2022 Background Iterative reconstruction for cone-beam computed tomography (CBCT) has been applied to improve image quality and reduce radiation dose. In a case where an object’s actual projection is larger than a flat panel detector, CBCT images contain ...
Sorapong Aootaphao +3 more
doaj +1 more source
Discrete Imaging Models for Three-Dimensional Optoacoustic Tomography using Radially Symmetric Expansion Functions [PDF]
, 2014 Optoacoustic tomography (OAT), also known as photoacoustic tomography, is an emerging computed biomedical imaging modality that exploits optical contrast and ultrasonic detection principles.
Er Oraevsky +5 more
core +1 more source
Approximate k-space models and Deep Learning for fast photoacoustic reconstruction [PDF]
, 2018 We present a framework for accelerated iterative reconstructions using a fast and approximate forward model that is based on k-space methods for photoacoustic tomography. The approximate model introduces aliasing artefacts in the gradient information for
Arridge, Simon +6 more
core +2 more sources
Increasing the Performance of the Iterative Computed Tomography Image Reconstruction Algorithms
مجلة النهرين للعلوم الهندسية, 2020 Computed tomography (CT) imaging is an important diagnostic tool. CT imaging facilitates the internal rendering of a scanned object by measuring the attenuation of beams of X-ray radiation.
Shimaa Abdulsalam Khazal +1 more
doaj +1 more source
Stabilizing deep tomographic reconstruction: Part A. Hybrid framework and experimental results
Patterns, 2022 Summary: A recent PNAS paper reveals that several popular deep reconstruction networks are unstable. Specifically, three kinds of instabilities were reported: (1) strong image artefacts from tiny perturbations, (2) small features missed in a deeply ...
Weiwen Wu +9 more
doaj +1 more source
A Multi-Grid Iterative Method for Photoacoustic Tomography [PDF]
, 2016 Inspired by the recent advances on minimizing nonsmooth or bound-constrained convex functions on models using varying degrees of fidelity, we propose a line search multigrid (MG) method for full-wave iterative image reconstruction in photoacoustic ...
Holman, Sean, Javaherian, Ashkan
core +3 more sources
Deep iterative reconstruction for phase retrieval [PDF]
Applied Optics, 2019 Classical phase retrieval problem is the recovery of a constrained image from the magnitude of its Fourier transform. Although there are several well-known phase retrieval algorithms including the hybrid input-output (HIO) method, the reconstruction performance is generally sensitive to initialization and measurement noise.
Çağatay Işıl +2 more
openaire +3 more sources
An Accelerated Iterative Cone Beam Computed Tomography Image Reconstruction Approach
مجلة النهرين للعلوم الهندسية, 2019 Cone-beam computed tomography (CBCT) is an indispensable method that reconstructs three dimensional (3D) images. CBCT employs a mathematical technique of reconstruction, which reveals the anatomy of the patient’s body through the measurements of ...
Shimaa Abdulsalam Khazal +1 more
doaj +1 more source
Model-Driven Enhanced Analytic Learned Iterative Shrinkage Threshold Algorithm
IEEE Access, 2022 The application of deep learning in compressed sensing reconstruction has achieved some excellent results. The deep neural network based on iterative algorithm can not only reflect the excellent performance of deep learning, but also reflect the ...
Jun Li +4 more
doaj +1 more source
Iterative Reconstruction of Signals on Graph [PDF]
IEEE Signal Processing Letters, 2020 We propose an iterative algorithm to interpolate graph signals from only a partial set of samples. Our method is derived from the well known Papoulis-Gerchberg algorithm by considering the optimal value of a constant involved in the iteration step. Compared with existing graph signal reconstruction algorithms, the proposed method achieves similar or ...
Emanuele Brugnoli +2 more
openaire +3 more sources