Cargando…

Assessment of Iterative Closest Point Registration Accuracy for Different Phantom Surfaces Captured by an Optical 3D Sensor in Radiotherapy

An optical 3D sensor provides an additional tool for verification of correct patient settlement on a Tomotherapy treatment machine. The patient's position in the actual treatment is compared with the intended position defined in treatment planning. A commercially available optical 3D sensor mea...

Descripción completa

Detalles Bibliográficos
Autores principales:	Krell, Gerald, Saeid Nezhad, Nazila, Walke, Mathias, Al-Hamadi, Ayoub, Gademann, Günther
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Hindawi Publishing Corporation 2017
Materias:	Research Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5253513/ https://www.ncbi.nlm.nih.gov/pubmed/28163773 http://dx.doi.org/10.1155/2017/2938504

Ejemplares similares

Iterative K-Closest Point Algorithms for Colored Point Cloud Registration
por: Choi, Ouk, et al.
Publicado: (2020)

Body surface registration considering individual differences with non-rigid iterative closest point
por: Tsumura, Ryosuke, et al.
Publicado: (2023)

Robust iterative closest point algorithm based on global reference point for rotation invariant registration
por: Du, Shaoyi, et al.
Publicado: (2017)

An Iterative Closest Points Algorithm for Registration of 3D Laser Scanner Point Clouds with Geometric Features
por: He, Ying, et al.
Publicado: (2017)

Affine Iterative Closest Point Algorithm Based on Color Information and Correntropy for Precise Point Set Registration
por: Liang, Lexian, et al.
Publicado: (2023)

Computational Analysis of Distance Operators for the Iterative Closest Point Algorithm
por: Mora, Higinio, et al.
Publicado: (2016)

Accuracy of registration algorithms in subtraction CT of the lungs: A digital phantom study
por: Grob, Dagmar, et al.
Publicado: (2019)

Estimating intrafraction tumor motion during fiducial-based liver stereotactic radiotherapy via an iterative closest point (ICP) algorithm
por: Li, Wu-zhou, et al.
Publicado: (2019)

LiDAR-IMU Time Delay Calibration Based on Iterative Closest Point and Iterated Sigma Point Kalman Filter
por: Liu, Wanli
Publicado: (2017)

A Robust and Accurate Two-Step Auto-Labeling Conditional Iterative Closest Points (TACICP) Algorithm for Three-Dimensional Multi-Modal Carotid Image Registration
por: Guo, Hengkai, et al.
Publicado: (2016)

A 6-DOF Navigation Method based on Iterative Closest Imaging Point Algorithm
por: Shi, Shuai, et al.
Publicado: (2017)

Evaluation of the accuracy of deformable image registration on MRI with a physical phantom
por: Wu, Richard Y., et al.
Publicado: (2019)

Anisotropic non-rigid Iterative Closest Point Algorithm for respiratory motion abdominal surface matching
por: Spinczyk, Dominik, et al.
Publicado: (2019)

Accuracy evaluation of surface registration algorithm using normal distribution transform in stereotactic body radiotherapy/radiosurgery: A phantom study
por: Lee, Haenghwa, et al.
Publicado: (2022)

An Efficient Rank Based Approach for Closest String and Closest Substring
por: Dinu, Liviu P., et al.
Publicado: (2012)

Accuracy between virtual surgical planning and actual outcomes in orthognathic surgery by iterative closest point algorithm and color maps: A retrospective cohort study
por: Marlière, Daniel-Amaral-Alves, et al.
Publicado: (2019)

An Augmented Reality System Using Improved-Iterative Closest Point Algorithm for On-Patient Medical Image Visualization
por: Wu, Ming-Long, et al.
Publicado: (2018)

Methodology for a reverse engineering process chain with focus on customized segmentation and iterative closest point algorithms
por: Mönchinger, Stephan, et al.
Publicado: (2022)

A Structure-Based Iterative Closest Point Using Anderson Acceleration for Point Clouds with Low Overlap
por: Zeng, Chao, et al.
Publicado: (2023)

Registration accuracy with the low dose kilovoltage cone-beam CT: A phantom study
por: Takei, Yoshiki, et al.
Publicado: (2019)

Registration of Aerial Optical Images with LiDAR Data Using the Closest Point Principle and Collinearity Equations
por: Huang, Rongyong, et al.
Publicado: (2018)

LiDAR-IMU Time Delay Calibration Based on Iterative Closest Point and Iterated Sigma Point Kalman Filter. Sensors 2017, 17, 539
por: Liu, Wanli
Publicado: (2017)

Closest string with outliers
por: Boucher, Christina, et al.
Publicado: (2011)

Quantifying the accuracy of deformable image registration for cone‐beam computed tomography with a physical phantom
por: Wu, Richard Y., et al.
Publicado: (2019)

Impact of CT scan parameters on deformable image registration accuracy using deformable thorax phantom
por: Ikeda, Ryutaro, et al.
Publicado: (2023)

Registration of Feature-Poor 3D Measurements from Fringe Projection
por: von Enzberg, Sebastian, et al.
Publicado: (2016)

Accuracy of 3D volumetric image registration based on CT, MR and PET/CT phantom experiments
por: Li, Guang, et al.
Publicado: (2008)

Measuring geometric accuracy in magnetic resonance imaging with 3D-printed phantom and nonrigid image registration
por: Nousiainen, Katri, et al.
Publicado: (2019)

Aerotaxis in the closest relatives of animals
por: Kirkegaard, Julius B, et al.
Publicado: (2016)

Accuracy of MRI-CT registration in brain stereotactic radiotherapy: Impact of MRI acquisition setup and registration method
por: Masitho, Siti, et al.
Publicado: (2022)

Evaluation of Subtalar Joint’s Compensatory Function in Varus Ankle Osteoarthritis Using Globally Optimal Iterative Closest Points (Go-ICP)
por: Kurokawa, Hiroaki, et al.
Publicado: (2022)

Accuracy of deformable image registration for contour propagation in adaptive lung radiotherapy
por: Hardcastle, Nicholas, et al.
Publicado: (2013)

An Iterative Image Registration Algorithm by Optimizing Similarity Measurement
por: Chu, Wei, et al.
Publicado: (2010)

Accuracy of registration techniques and vascular imaging modalities in fusion imaging for aortic endovascular interventions: a phantom study
por: Sieren, M. M., et al.
Publicado: (2021)

Validation of accuracy deformable image registration contour propagation using a benchmark virtual HN phantom dataset
por: Boyd, Robert, et al.
Publicado: (2021)

Development of a physical geometric phantom for deformable image registration credentialing of radiotherapy centers for a clinical trial
por: Kadoya, Noriyuki, et al.
Publicado: (2021)

Measurement accuracy of lung nodule volumetry in a phantom study: Effect of axial-volume scan and iterative reconstruction algorithm
por: Lee, Han Na, et al.
Publicado: (2020)

Accuracy and Feasibility of Synthetic CT for Lung Adaptive Radiotherapy: A Phantom Study
por: Zhao, Ruifeng, et al.
Publicado: (2023)

Amplitude dependent closest tune approach
por: Tomas Garcia, Rogelio, et al.
Publicado: (2016)

Polycomb Targets Seek Closest Neighbours
por: Chotalia, Mita, et al.
Publicado: (2011)

Cannot write session to /tmp/vufind_sessions/sess_dt0f523d3p378ol6mdqc4ebq82