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This set of software tools includes OpenCL implementation of modern CT and CBCT reconstruction algorithms including unpublished algorithms by the author.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
Beyond Image to Depth: Improving Depth Prediction using Echoes (CVPR 2021)

Beyond Image to Depth: Improving Depth Prediction using Echoes (CVPR 2021) Kranti Kumar Parida, Siddharth Srivastava, Gaurav Sharma. We address the pr

Kranti Kumar Parida 33 Jun 27, 2022
GBK-GNN: Gated Bi-Kernel Graph Neural Networks for Modeling Both Homophily and Heterophily

GBK-GNN: Gated Bi-Kernel Graph Neural Networks for Modeling Both Homophily and Heterophily Abstract Graph Neural Networks (GNNs) are widely used on a

10 Dec 20, 2022
This Artificial Intelligence program can take a black and white/grayscale image and generate a realistic or plausible colorized version of the same picture.

Colorizer The point of this project is to write a program capable of taking a black and white / grayscale image, and generating a realistic or plausib

Maitri Shah 1 Jan 06, 2022
Implementation of Diverse Semantic Image Synthesis via Probability Distribution Modeling

Diverse Semantic Image Synthesis via Probability Distribution Modeling (CVPR 2021) Paper Zhentao Tan, Menglei Chai, Dongdong Chen, Jing Liao, Qi Chu,

tzt 45 Nov 17, 2022
Deployment of PyTorch chatbot with Flask

Chatbot Deployment with Flask and JavaScript In this tutorial we deploy the chatbot I created in this tutorial with Flask and JavaScript. This gives 2

Patrick Loeber (Python Engineer) 107 Dec 29, 2022
A toy project using OpenCV and PyMunk

A toy project using OpenCV, PyMunk and Mediapipe the source code for my LindkedIn post It's just a toy project and I didn't write a documentation yet,

Amirabbas Asadi 82 Oct 28, 2022
classification task on dataset-CIFAR10,by using Tensorflow/keras

CIFAR10-Tensorflow classification task on dataset-CIFAR10,by using Tensorflow/keras 在这一个库中,我使用Tensorflow与keras框架搭建了几个卷积神经网络模型,针对CIFAR10数据集进行了训练与测试。分别使

3 Oct 17, 2021
Code for the Active Speakers in Context Paper (CVPR2020)

Active Speakers in Context This repo contains the official code and models for the "Active Speakers in Context" CVPR 2020 paper. Before Training The c

43 Oct 14, 2022
The code for SAG-DTA: Prediction of Drug–Target Affinity Using Self-Attention Graph Network.

SAG-DTA The code is the implementation for the paper 'SAG-DTA: Prediction of Drug–Target Affinity Using Self-Attention Graph Network'. Requirements py

Shugang Zhang 7 Aug 02, 2022
Multi-Joint dynamics with Contact. A general purpose physics simulator.

MuJoCo Physics MuJoCo stands for Multi-Joint dynamics with Contact. It is a general purpose physics engine that aims to facilitate research and develo

DeepMind 5.2k Jan 02, 2023
BARF: Bundle-Adjusting Neural Radiance Fields 🤮 (ICCV 2021 oral)

BARF 🤮 : Bundle-Adjusting Neural Radiance Fields Chen-Hsuan Lin, Wei-Chiu Ma, Antonio Torralba, and Simon Lucey IEEE International Conference on Comp

Chen-Hsuan Lin 539 Dec 28, 2022
A curated list of awesome Active Learning

Awesome Active Learning 🤩 A curated list of awesome Active Learning ! 🤩 Background (image source: Settles, Burr) What is Active Learning? Active lea

BAI Fan 431 Jan 03, 2023
sequitur is a library that lets you create and train an autoencoder for sequential data in just two lines of code

sequitur sequitur is a library that lets you create and train an autoencoder for sequential data in just two lines of code. It implements three differ

Jonathan Shobrook 305 Dec 21, 2022
The official repository for "Score Transformer: Generating Musical Scores from Note-level Representation" (MMAsia '21)

Score Transformer This is the official repository for "Score Transformer": Score Transformer: Generating Musical Scores from Note-level Representation

22 Dec 22, 2022
PRIN/SPRIN: On Extracting Point-wise Rotation Invariant Features

PRIN/SPRIN: On Extracting Point-wise Rotation Invariant Features Overview This repository is the Pytorch implementation of PRIN/SPRIN: On Extracting P

Yang You 17 Mar 02, 2022
Repo for our ICML21 paper Unsupervised Learning of Visual 3D Keypoints for Control

Unsupervised Learning of Visual 3D Keypoints for Control [Project Website] [Paper] Boyuan Chen1, Pieter Abbeel1, Deepak Pathak2 1UC Berkeley 2Carnegie

Boyuan Chen 34 Jul 22, 2022
Code for Reciprocal Adversarial Learning for Brain Tumor Segmentation: A Solution to BraTS Challenge 2021 Segmentation Task

BRATS 2021 Solution For Segmentation Task This repo contains the supported pytorch code and configuration files to reproduce 3D medical image segmenta

Himashi Amanda Peiris 6 Sep 15, 2022
OCTIS: Comparing Topic Models is Simple! A python package to optimize and evaluate topic models (accepted at EACL2021 demo track)

OCTIS : Optimizing and Comparing Topic Models is Simple! OCTIS (Optimizing and Comparing Topic models Is Simple) aims at training, analyzing and compa

MIND 478 Jan 01, 2023
PromptDet: Expand Your Detector Vocabulary with Uncurated Images

PromptDet: Expand Your Detector Vocabulary with Uncurated Images Paper Website Introduction The goal of this work is to establish a scalable pipeline

103 Dec 20, 2022
Deep Anomaly Detection with Outlier Exposure (ICLR 2019)

Outlier Exposure This repository contains the essential code for the paper Deep Anomaly Detection with Outlier Exposure (ICLR 2019). Requires Python 3

Dan Hendrycks 464 Dec 27, 2022