A review of GPU-based medical image reconstruction

P Després, X Jia - Physica Medica, 2017 - Elsevier
Tomographic image reconstruction is a computationally demanding task, even more so
when advanced models are used to describe a more complete and accurate picture of the …

TIGRE: a MATLAB-GPU toolbox for CBCT image reconstruction

A Biguri, M Dosanjh, S Hancock… - Biomedical Physics & …, 2016 - iopscience.iop.org
In this article the Tomographic Iterative GPU-based Reconstruction (TIGRE) Toolbox, a
MATLAB/CUDA toolbox for fast and accurate 3D x-ray image reconstruction, is presented …

Compressed-sensing-inspired reconstruction algorithms in low-dose computed tomography: A review

AB Konovalov - Physica Medica, 2024 - Elsevier
Background Optimization of the dose the patient receives during scanning is an important
problem in modern medical X-ray computed tomography (CT). One of the basic ways to its …

Fast compressed sensing‐based CBCT reconstruction using Barzilai‐Borwein formulation for application to on‐line IGRT

JC Park, B Song, JS Kim, SH Park, HK Kim… - Medical …, 2012 - Wiley Online Library
Purpose: Compressed sensing theory has enabled an accurate, low‐dose cone‐beam
computed tomography (CBCT) reconstruction using a minimal number of noisy projections …

Deep learning-based real-time volumetric imaging for lung stereotactic body radiation therapy: a proof of concept study

Y Lei, Z Tian, T Wang, K Higgins… - Physics in Medicine …, 2020 - iopscience.iop.org
Due to the inter-and intra-variation of respiratory motion, it is highly desired to provide real-
time volumetric images during the treatment delivery of lung stereotactic body radiation …

Arbitrarily large tomography with iterative algorithms on multiple GPUs using the TIGRE toolbox

A Biguri, R Lindroos, R Bryll, H Towsyfyan… - Journal of Parallel and …, 2020 - Elsevier
Abstract 3D tomographic imaging requires the computation of solutions to very large inverse
problems. In many applications, iterative algorithms provide superior results, however …

Accelerated barrier optimization compressed sensing (ABOCS) reconstruction for cone‐beam CT: phantom studies

T Niu, L Zhu - Medical physics, 2012 - Wiley Online Library
Purpose: Recent advances in compressed sensing (CS) enable accurate CT image
reconstruction from highly undersampled and noisy projection measurements, due to the …

A few-view reweighted sparsity hunting (FRESH) method for CT image reconstruction

M Chang, L Li, Z Chen, Y **ao… - Journal of X-ray …, 2013 - content.iospress.com
In recent years, the total variation (TV) minimization method has been widely used for
compressed sensing (CS) based CT image reconstruction. In this paper, we propose a few …

Statistical iterative CBCT reconstruction based on neural network

B Chen, K **ang, Z Gong, J Wang… - IEEE transactions on …, 2018 - ieeexplore.ieee.org
Cone-beam computed tomography (CBCT) plays an important role in radiation therapy.
Statistical iterative reconstruction (SIR) algorithms with specially designed penalty terms …

Evaluation and clinical application of a commercially available iterative reconstruction algorithm for CBCT-based IGRT

W Mao, C Liu, SJ Gardner, F Siddiqui… - … in cancer research …, 2019 - journals.sagepub.com
Purpose: We have quantitatively evaluated the image quality of a new commercially
available iterative cone-beam computed tomography reconstruction algorithm over standard …