Fetching the paper…
Reading the bibliography…
X-ray, known for its ability to reveal internal structures of objects, is expected to provide richer information for 3D reconstruction than visible light.
Representation of a function by its line integrals, with some radiological applications
Allan Macleod Cormack · 1963
Earlier work this paper cites.
Representation of a function by its line integrals, with some radiological applications. ii
Allan Macleod Cormack · 1964
Earlier work this paper cites.
Computerized transverse axial scanning (tomography): Part 1. description of system
Godfrey N Hounsfield · 1973
Earlier work this paper cites.
Computed medical imaging
Godfrey N Hounsfield · 1980
Earlier work this paper cites.
Simultaneous algebraic reconstruction technique (sart): a superior implementation of the art algorithm
Anders H Andersen and Avinash C Kak · 1984
Earlier work this paper cites.
Practical cone-beam algorithm
Lee A Feldkamp, Lloyd C Davis, and James W Kress · 1984
Earlier work this paper cites.
A local update strategy for iterative reconstruction from projections
Ken Sauer and Charles Bouman · 1993
Earlier work this paper cites.
Transmission maximum-likelihood reconstruction with ordered subsets for cone beam ct
Stephen H Manglos, George M Gagne, Andrzej Krol, F Deaver Thomas, and Rammohan Narayanaswamy · 1995
Earlier work this paper cites.
Dedicated breast ct: radiation dose and image quality evaluation
John M Boone, Thomas R Nelson, Karen K Lindfors, and J Anthony Seibert · 2001
Earlier work this paper cites.
Cone-beam volume ct breast imaging: Feasibility study
Biao Chen and Ruola Ning · 2002
Earlier work this paper cites.
Segmentation-free statistical image reconstruction for polyenergetic x-ray computed tomography with experimental validation
Idris A Elbakri and Jeffrey A Fessler · 2003
Earlier work this paper cites.
A comprehensive analysis of coefficients for pendant-geometry cone-beam breast computed tomography
JM Boone, N Shah, and TR Nelson · 2004
Earlier work this paper cites.
Image quality assessment: from error visibility to structural similarity
Zhou Wang, Alan C Bovik, Hamid R Sheikh, and Eero P Simoncell · 2004
Earlier work this paper cites.
1.1 über die bestimmung von funktionen durch ihre integralwerte längs gewisser mannigfaltigkeiten
Johann Radon · 2005
Earlier work this paper cites.
Variable weighted ordered subset image reconstruction algorithm
Jinxiao Pan, Tie Zhou, Yan Han, Ming Jiang, et al · 2006
Earlier work this paper cites.
D2vr: High-quality volume rendering of projection-based volumetric data
Peter Rautek, Balázs Csébfalvi, Sören Grimm, Stefan Bruckner, and Meister Eduard Gröller · 2006
Earlier work this paper cites.
Clinical applications of cone-beam computed tomography in dental practice
William C Scarfe, Allan G Farman, Predag Sukovic, et al · 2006
Earlier work this paper cites.
Region of interest reconstruction from truncated data in circular cone-beam ct
Lifeng Yu, Yu Zou, Emil Y Sidky, Charles A Pelizzari, Peter Munro, and Xiaochuan Pan · 2006
Earlier work this paper cites.
Statistical reconstruction for x-ray ct systems with non-continuous detectors
Wojciech Zbijewski, Michel Defrise, Max A Viergever, and Freek J Beekman · 2006
Earlier work this paper cites.
Image reconstruction in circular cone-beam computed tomography by constrained, total-variation minimization
Emil Y Sidky and Xiaochuan Pan · 2008
Cited alongside, same era.
Instant volume visualization using maximum intensity difference accumulation
Stefan Bruckner and M Eduard Gröller · 2009
Cited alongside, same era.
The lung image database consortium (lidc) and image database resource initiative (idri): a completed reference database of lung nodules on ct scans
Samuel G Armato III, Geoffrey McLennan, Luc Bidaut, Michael F McNitt-Gray, Charles R Meyer, Anthony P Reeves, Binsheng Zhao, Denise R Aberle, Claudia I Henschke, Eric A Hoffman, et al · 2011
Cited alongside, same era.
Adam: A method for stochastic optimization
Diederik P. Kingma and Jimmy Lei Ba · 2015
Cited alongside, same era.
Deeporgan: Multi-level deep convolutional networks for automated pancreas segmentation
Holger R Roth, Le Lu, Amal Farag, Hoo-Chang Shin, Jiamin Liu, Evrim B Turkbey, and Ronald M Summers · 2015
Cited alongside, same era.
Training data-efficient image transformers & distillation through attention
Hugo Touvron, Matthieu Cord, Matthijs Douze, Francisco Massa, Alexandre Sablayrolles, and Herve Jegou · 2021
Later among the works it cites.
Segformer: Simple and efficient design for semantic segmentation with transformers
Enze Xie, Wenhai Wang, Zhiding Yu, Anima Anandkumar, Jose M Alvarez, and Ping Luo · 2021
Later among the works it cites.
Intratomo: self-supervised learning-based tomography via sinogram synthesis and prediction
Guangming Zang, Ramzi Idoughi, Rui Li, Peter Wonka, and Wolfgang Heidrich · 2021
Later among the works it cites.
Deformable detr: Deformable transformers for end-to-end object detection
Xizhou Zhu, Weijie Su, Lewei Lu, Bin Li, Xiaogang Wang, and Jifeng Dai · 2021
Later among the works it cites.
Mip-nerf 360: Unbounded anti-aliased neural radiance fields
Jonathan T. Barron, Ben Mildenhall, Dor Verbin, Pratul P. Srinivasan, and Peter Hedman · 2022
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Tigre: a matlab-gpu toolbox for cbct image reconstruction
Ander Biguri, Manjit Dosanjh, Steven Hancock, and Manuchehr Soleimani · 2016
Cited alongside, same era.
Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
Cited alongside, same era.
Lose the views: Limited angle ct reconstruction via implicit sinogram completion
Rushil Anirudh, Hyojin Kim, Jayaraman J Thiagarajan, K Aditya Mohan, Kyle Champley, and Timo Bremer · 2018
Cited alongside, same era.
Pytorch: An imperative style, high-performance deep learning library
Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, et al · 2019
Cited alongside, same era.
X2ct-gan: reconstructing ct from biplanar x-rays with generative adversarial networks
Xingde Ying, Heng Guo, Kai Ma, Jian Wu, Zhengxin Weng, and Yefeng Zheng · 2019
Cited alongside, same era.
End-to-end convolutional neural network for 3d reconstruction of knee bones from bi-planar x-ray images
Yoni Kasten, Daniel Doktofsky, and Ilya Kovler · 2020
Cited alongside, same era.
Nerf: Representing scenes as neural radiance fields for view synthesis
B Mildenhall, PP Srinivasan, M Tancik, JT Barron, R Ramamoorthi, and R Ng · 2020
Cited alongside, same era.
Mednerf: Medical neural radiance fields for reconstructing 3d-aware ct-projections from a single x-ray
Abril Corona-Figueroa, Jonathan Frawley, Sam Bond-Taylor, Sarath Bethapudi, Hubert PH Shum, and Chris G Willcocks · 2022
Later among the works it cites.
Scientific visualization datasets, 2022
Pavol Klacansky · 2022
Later among the works it cites.
Instant neural graphics primitives with a multiresolution hash encoding
Thomas Müller, Alex Evans, Christoph Schied, and Alexander Keller · 2022
Later among the works it cites.
Philips research, hamburg, germany
Philips · 2022
Later among the works it cites.
Neat: Neural adaptive tomography
Darius Rückert, Yuanhao Wang, Rui Li, Ramzi Idoughi, and Wolfgang Heidrich · 2022
Later among the works it cites.
Light field neural rendering
Mohammed Suhail, Carlos Esteves, Leonid Sigal, and Ameesh Makadia · 2022
Later among the works it cites.
Restormer: Efficient transformer for high-resolution image restoration
Syed Waqas Zamir, Aditya Arora, Salman Khan, Munawar Hayat, Fahad Shahbaz Khan, and Ming-Hsuan Yang · 2022
Later among the works it cites.
Naf: neural attenuation fields for sparse-view cbct reconstruction
Ruyi Zha, Yanhao Zhang, and Hongdong Li · 2022
Later among the works it cites.
Styleswin: Transformer-based gan for high-resolution image generation
Bowen Zhang, Shuyang Gu, Bo Zhang, Jianmin Bao, Dong Chen, Fang Wen, Yong Wang, and Baining Guo · 2022
Later among the works it cites.
Retinexformer: One-stage retinex-based transformer for low-light image enhancement
Yuanhao Cai, Hao Bian, Jing Lin, Haoqian Wang, Radu Timofte, and Yulun Zhang · 2023
Closest in time.
Neurbf: A neural fields representation with adaptive radial basis functions
Zhang Chen, Zhong Li, Liangchen Song, Lele Chen, Jingyi Yu, Junsong Yuan, and Yi Xu · 2023
Closest in time.
Solving 3d inverse problems using pre-trained 2d diffusion models
Hyungjin Chung, Dohoon Ryu, Michael T McCann, Marc L Klasky, and Jong Chul Ye · 2023
Closest in time.
Learning deep intensity field for extremely sparse-view cbct reconstruction
Yiqun Lin, Zhongjin Luo, Wei Zhao, and Xiaomeng Li · 2023
Closest in time.
Rodin: A generative model for sculpting 3d digital avatars using diffusion
Tengfei Wang, Bo Zhang, Ting Zhang, Shuyang Gu, Jianmin Bao, Tadas Baltrusaitis, Jingjing Shen, Dong Chen, Fang Wen, Qifeng Chen, and Baining Guo · 2023
Closest in time.