Fast, accurate and reliable software for algebraic CT reconstruction

Related tags

Deep LearningKCT_cbct
Overview

KCT CBCT

Fast, accurate and reliable software for algebraic CT reconstruction.

This set of software tools includes OpenCL implementation of modern CT and CBCT reconstruction algorithms including unpublished algorithms by the author. Initially, the focus was on CT reconstruction using Krylov LSQR and CGLS methods. Gradually, other widely used methods such as OS-SIRT are added. Initially, the software was based on the idea of a projector that directly computes the projections of individual voxels onto pixels using the volume integrals of the voxel cuts. The author intends to publish a paper on this cutting voxel projector (CVP) in late 2021. However, the package also includes implementations of the TT projector and the Siddon projector the DD and TR projectors will be implemented in the near future. The code for the CVP projector is optimized using OpenCL local memory and is probably one of the fastest projector implementations ever for algebraic reconstruction.

The package has been tested and is compatible with the AMD Radeon VII Vega 20 GPU and NVIDIA GeForce RTX 2080 Ti GPU. Some routines have been optimized specifically for these GPU architectures. OpenCL code conforms to the OpenCL 1.2 specification and the implementation uses C++ wrappers from OpenCL 1.2. OpenCL 2.0 is not supported due to lack of support from NVidia.

Algorithms

Cutting voxel projector yet to be published.

LSQR algorithm was implemented according to https://doi.org/10.1002/nla.611

CGLS algorithm with delayed residual computation as described in the proceedings of Fully3D conference 2021 Software Implementation of the Krylov Methods Based Reconstruction for the 3D Cone Beam CT Operator Poster and extendend absract can be found in the publications directory

Repositories

The KCT package is hosted on Bitbucket and GitHub

GitHub public repository

git clone https://github.com/kulvait/KCT_cbct.git

Bitbucket public repository

git clone https://bitbucket.org/kulvait/kct_cbct.git

Submodules

Submodules lives in the submodules directory. To clone project including submodules one have to use the following commands

git submodule init
git submodule update

or use the following command when cloning repository

git clone --recurse-submodules

CTIOL

Input output routines for asynchronous thread safe reading/writing CT data. The DEN format read/write is implemented.

CTMAL

Mathematic/Algebraic algorithms for supporting CT data manipulation.

Plog logger

Logger Plog is used for logging. It is licensed under the Mozilla Public License Version 2.0.

CLI11

Comand line parser CLI11. It is licensed under 3 Clause BSD License.

Catch2

Testing framework. Licensed under Boost Software License 1.0.

CTPL

Threadpool library.

Documentation

Documentation is generated using doxygen and lives in doc directory. First the config file for doxygen was prepared runing doxygen -g. Doc files and this file can be written using Markdown syntax, JAVADOC_AUTOBRIEF is set to yes to treat first line of the doc comment as a brief description, comments are of the format

/**Brief description.
*
*Long description
*thay might span multiple lines.
*/

.

Licensing

When there is no other licensing and/or copyright information in the source files of this project, the following apply for the source files in the directories include and src and for CMakeLists.txt file:

Copyright (C) 2018-2021 Vojtěch Kulvait

This program is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, version 3 of the License.

This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
GNU General Public License for more details.

You should have received a copy of the GNU General Public License
along with this program.  If not, see <https://www.gnu.org/licenses/>.

This licensing applies to the direct source files in the directories include and src of this project and not for submodules.

Owner
Vojtěch Kulvait
2018-2021 PostDoc at Magdeburg University, CT reconstruction
Vojtěch Kulvait
Repository aimed at compiling code, papers, demos etc.. related to my PhD on 3D vision and machine learning for fruit detection and shape estimation at the university of Lincoln

PhD_3DPerception Repository aimed at compiling code, papers, demos etc.. related to my PhD on 3D vision and machine learning for fruit detection and s

lelouedec 2 Oct 06, 2022
Small-bets - Ergodic Experiment With Python

Ergodic Experiment Based on this video. Run this experiment with this command: p

Michael Brant 3 Jan 11, 2022
Garbage Detection system which will detect objects based on whether it is plastic waste or plastics or just garbage.

Garbage Detection using Yolov5 on Jetson Nano 2gb Developer Kit. Garbage detection system which will detect objects based on whether it is plastic was

Rishikesh A. Bondade 2 May 13, 2022
PyToch implementation of A Novel Self-supervised Learning Task Designed for Anomaly Segmentation

Self-Supervised Anomaly Segmentation Intorduction This is a PyToch implementation of A Novel Self-supervised Learning Task Designed for Anomaly Segmen

WuFan 2 Jan 27, 2022
Zero-shot Synthesis with Group-Supervised Learning (ICLR 2021 paper)

GSL - Zero-shot Synthesis with Group-Supervised Learning Figure: Zero-shot synthesis performance of our method with different dataset (iLab-20M, RaFD,

Andy_Ge 62 Dec 21, 2022
GAN encoders in PyTorch that could match PGGAN, StyleGAN v1/v2, and BigGAN. Code also integrates the implementation of these GANs.

MTV-TSA: Adaptable GAN Encoders for Image Reconstruction via Multi-type Latent Vectors with Two-scale Attentions. This is the official code release fo

owl 37 Dec 24, 2022
ANEA: Distant Supervision for Low-Resource Named Entity Recognition

ANEA: Distant Supervision for Low-Resource Named Entity Recognition ANEA is a tool to automatically annotate named entities in unlabeled text based on

Saarland University Spoken Language Systems Group 15 Mar 30, 2022
Pytorch implementation of Straight Sampling Network For Point Cloud Learning (ICIP2021).

Pytorch code for SS-Net This is a pytorch implementation of Straight Sampling Network For Point Cloud Learning (ICIP2021). Environment Code is tested

Sun Ran 1 May 18, 2022
SemiNAS: Semi-Supervised Neural Architecture Search

SemiNAS: Semi-Supervised Neural Architecture Search This repository contains the code used for Semi-Supervised Neural Architecture Search, by Renqian

Renqian Luo 21 Aug 31, 2022
Depth-Aware Video Frame Interpolation (CVPR 2019)

DAIN (Depth-Aware Video Frame Interpolation) Project | Paper Wenbo Bao, Wei-Sheng Lai, Chao Ma, Xiaoyun Zhang, Zhiyong Gao, and Ming-Hsuan Yang IEEE C

Wenbo Bao 7.7k Dec 31, 2022
Supplementary code for TISMIR paper "Sliding-Window Pitch-Class Histograms as a Means of Modeling Musical Form"

Sliding-Window Pitch-Class Histograms as a Means of Modeling Musical Form This is supplementary code for the TISMIR paper Sliding-Window Pitch-Class H

1 Nov 27, 2021
A PyTorch Implementation of Neural IMage Assessment

NIMA: Neural IMage Assessment This is a PyTorch implementation of the paper NIMA: Neural IMage Assessment (accepted at IEEE Transactions on Image Proc

yunxiaos 418 Dec 29, 2022
Gif-caption - A straightforward GIF Captioner written in Python

Broksy's GIF Captioner Have you ever wanted to easily caption a GIF without havi

3 Apr 09, 2022
Hierarchical Aggregation for 3D Instance Segmentation (ICCV 2021)

HAIS Hierarchical Aggregation for 3D Instance Segmentation (ICCV 2021) by Shaoyu Chen, Jiemin Fang, Qian Zhang, Wenyu Liu, Xinggang Wang*. (*) Corresp

Hust Visual Learning Team 145 Jan 05, 2023
Code for Pose-Controllable Talking Face Generation by Implicitly Modularized Audio-Visual Representation (CVPR 2021)

Pose-Controllable Talking Face Generation by Implicitly Modularized Audio-Visual Representation (CVPR 2021) Hang Zhou, Yasheng Sun, Wayne Wu, Chen Cha

Hang_Zhou 628 Dec 28, 2022
Functional TensorFlow Implementation of Singular Value Decomposition for paper Fast Graph Learning

tf-fsvd TensorFlow Implementation of Functional Singular Value Decomposition for paper Fast Graph Learning with Unique Optimal Solutions Cite If you f

Sami Abu-El-Haija 14 Nov 25, 2021
Metric learning algorithms in Python

metric-learn: Metric Learning in Python metric-learn contains efficient Python implementations of several popular supervised and weakly-supervised met

1.3k Jan 02, 2023
Julia and Matlab codes to simulated all problems in El-Hachem, McCue and Simpson (2021)

Substrate_Mediated_Invasion Julia and Matlab codes to simulated all problems in El-Hachem, McCue and Simpson (2021) 2DSolver.jl reproduces the simulat

Matthew Simpson 0 Nov 09, 2021
Pytorch code for our paper "Feedback Network for Image Super-Resolution" (CVPR2019)

Feedback Network for Image Super-Resolution [arXiv] [CVF] [Poster] Update: Our proposed Gated Multiple Feedback Network (GMFN) will appear in BMVC2019

Zhen Li 539 Jan 06, 2023
Implementation of Deformable Attention in Pytorch from the paper "Vision Transformer with Deformable Attention"

Deformable Attention Implementation of Deformable Attention from this paper in Pytorch, which appears to be an improvement to what was proposed in DET

Phil Wang 128 Dec 24, 2022