Cargando…

Low-dose CBCT reconstruction via joint non-local total variation denoising and cubic B-spline interpolation

This study develops an improved Feldkamp–Davis–Kress (FDK) reconstruction algorithm using non-local total variation (NLTV) denoising and a cubic B-spline interpolation-based backprojector to enhance the image quality of low-dose cone-beam computed tomography (CBCT). The NLTV objective function is mi...

Descripción completa

Detalles Bibliográficos
Autores principales:	Lee, Ho, Park, Jiyoung, Choi, Yeonho, Park, Kyung Ran, Min, Byung Jun, Lee, Ik Jae
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Nature Publishing Group UK 2021
Materias:	Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7878746/ https://www.ncbi.nlm.nih.gov/pubmed/33574477 http://dx.doi.org/10.1038/s41598-021-83266-1

Ejemplares similares

Interpolating cubic splines
por: Knott, Gary D
Publicado: (2000)

On maximum error and boundary conditions in cubic spline interpolation at equidistant knots
por: Melinder, I
Publicado: (1979)

Cubic-Spline Interpolation for Sparse-View CT Image Reconstruction With Filtered Backprojection in Dynamic Myocardial Perfusion Imaging
por: Enjilela, Esmaeil, et al.
Publicado: (2019)

Cardinal spline interpolation
por: Schönberg, Isaac J
Publicado: (1973)

Cubic-spline interpolation to estimate effects of inbreeding on milk yield in first lactation Holstein cows
por: Geha, Makram J., et al.
Publicado: (2011)

Classifying marine mammals signal using cubic splines interpolation combining with triple loss variational auto-encoder
por: Bach, Nhat Hoang, et al.
Publicado: (2023)

Spline functions and multivariate interpolations
por: Bojanov, B D, et al.
Publicado: (1993)

One dimensional spline interpolation algorithms
por: SpÃ¤th, Helmuth
Publicado: (1995)

Two dimensional spline interpolation algorithms
por: Spath, Helmuth
Publicado: (1993)

On best cubature formulas and spline interpolation
por: El-Tom, M E A
Publicado: (1975)

Pretreatment of Ultra-Weak Fiber Bragg Grating Hydrophone Array Based on Cubic Spline Interpolation Using Intensity Compensation
por: Pang, Yandong, et al.
Publicado: (2022)

Mutual Information-Based Non-Local Total Variation Denoiser for Low-Dose Cone-Beam Computed Tomography
por: Lee, Ho, et al.
Publicado: (2021)

Planar interpolation by second order spiral splines
por: Noakes, Lyle
Publicado: (2020)

Restricted cubic splines for modelling periodic data
por: Lusa, Lara, et al.
Publicado: (2020)

Bundle Block Adjustment with 3D Natural Cubic Splines
por: Lee, Won Hee, et al.
Publicado: (2009)

Flexible Utility Function Approximation via Cubic Bezier Splines
por: Lee, Sangil, et al.
Publicado: (2020)

Spline-Interpolation Solution of One Elasticity Theory Problem
por: Shirakova, Elena A
Publicado: (2011)

Monte-Carlo Feineinstellung mittels Interpolation durch kubische Splines
por: Schwickerath, Ulrich
Publicado: (1995)

Monotone Data Visualization Using Rational Trigonometric Spline Interpolation
por: Ibraheem, Farheen, et al.
Publicado: (2014)

Quadratic trigonometric B-spline for image interpolation using GA
por: Hussain, Malik Zawwar, et al.
Publicado: (2017)

Analyzing Single Molecule Localization Microscopy Data Using Cubic Splines
por: Babcock, Hazen P., et al.
Publicado: (2017)

Estimated breeding values and association mapping for persistency and total milk yield using natural cubic smoothing splines
por: Verbyla, Klara L, et al.
Publicado: (2009)

Local Convexity-Preserving C (2) Rational Cubic Spline for Convex Data
por: Abbas, Muhammad, et al.
Publicado: (2014)

An Automatic Method for Nucleus Boundary Segmentation Based on a Closed Cubic Spline
por: Feng, Zhao, et al.
Publicado: (2016)

Orthogonal cubic splines for the numerical solution of nonlinear parabolic partial differential equations
por: Alavi, Javad, et al.
Publicado: (2023)

An Improved DOA Estimation Approach Using Coarray Interpolation and Matrix Denoising
por: Guo, Muran, et al.
Publicado: (2017)

V-Spline: An Adaptive Smoothing Spline for Trajectory Reconstruction
por: Cao, Zhanglong, et al.
Publicado: (2021)

White matter fiber tracking directed by interpolating splines and a methodological framework for evaluation
por: Losnegård, Are, et al.
Publicado: (2013)

Impact of Denoising on Deep-Learning-Based Automatic Segmentation Framework for Breast Cancer Radiotherapy Planning
por: Im, Jung Ho, et al.
Publicado: (2022)

Gradient Profile Estimation Using Exponential Cubic Spline Smoothing in a Bayesian Framework
por: De Silva, Kushani, et al.
Publicado: (2021)

Proposal for a spline function interpolation option at the graphic interface of the function generators GFAS and GFAD
por: Schneider, G C
Publicado: (1993)

Application of the Spline Interpolation in Simulating the Distribution of Phytoplankton in a Marine NPZD Type Ecosystem Model
por: Li, Xiaona, et al.
Publicado: (2019)

Joint Demosaicing and Denoising Based on a Variational Deep Image Prior Neural Network
por: Park, Yunjin, et al.
Publicado: (2020)

The Cubic Functions for Spline Smoothed L, S and M Values for BMI Reference Data of Japanese Children
por: Kato, Noriko, et al.
Publicado: (2013)

Numerical Method Using Cubic B-Spline for a Strongly Coupled Reaction-Diffusion System
por: Abbas, Muhammad, et al.
Publicado: (2014)

The Cubic Functions for Spline Smoothed L, S and M Values for BMI Reference Data of Japanese Children
por: Kato, Noriko, et al.
Publicado: (2011)

A numerical investigation of the GRLW equation using lumped Galerkin approach with cubic B-spline
por: Zeybek, Halil, et al.
Publicado: (2016)

A Bayesian natural cubic B-spline varying coefficient method for non-ignorable dropout
por: Moore, Camille M., et al.
Publicado: (2020)

Using Restricted Cubic Splines to Study the Duration of Antibiotic Use in the Prognosis of Ventilator-Associated Pneumonia
por: Xu, Yixian, et al.
Publicado: (2022)

Analytical Low-Dose CBCT Reconstruction Using Non-local Total Variation Regularization for Image Guided Radiation Therapy
por: Sohn, James J., et al.
Publicado: (2020)

Cannot write session to /tmp/vufind_sessions/sess_12c67t6uu7cmpc2dvs6bti78a9