PAN Blend tomography packages

CTSim впроваджує інтерактивну симуляцію комп’ютерного томографа. Комп’ютерна томографія дозволяє отримати уяву про внутрішню будову об’єкта по вимірюванню ступеня поглинання x-променів, що проходять крізь об’єкт.

CTSim має як графічний інтерфейс так і можливість керування з командного рядка. CTSim має дуже добрий навчальний режим для перегляду даних отриманих в ході симуляції, а також для реконструкції.

This package provides HTML and PDF documentation files for the ctsim package. CTSim is a graphical computed tomography simulator. This documentation file is included in a separate package so it will not have to be include in the binary ctsim package for every architecture.

This package provides the online help file for the ctsim package. CTSim is a graphical computed tomography simulator. This help file is included in a separate package so it will not have to be include in the binary ctsim package for every architecture.

Geomview — інтерактивна геометрична програма, яка призначена для математичних досліджень та освіти. Зокрема, geomview може показувати предмети у гіперболічному та сферичному просторі не гірш аніж у Евклідовому.

Geomview підтримує велику кількість незалежно контрольованих об'єктів і камер. Можливий інтерактивний контроль за рухом, зовнішніми факторами (включаючи освітлення, затемнення і матеріали), вибір рівня редагування — об'єкта, ребра або вершини, збереження зображення у форматі SGI або Renderman RIB, додавання і вилучення об'єктів безпосередньо за допомогою миші, панелі управління і клавіатурних комбінацій. Зовнішні програми можуть керувати потрібними аспектами перегляду (включаючи завантажувану змінну геометрію або контролювання руху певних об'єктів) одночасно з інтерактивним контролем усього іншого.

The UFO data processing framework is a C library suited to build general purpose streams data processing on heterogeneous architectures such as CPUs, GPUs or clusters. It is extensively used at the Karlsruhe Institute of Technology for Ultra-fast X-ray Imaging (radiography, tomography and laminography).

A gobject-instrospection binding is also provided to write scripts or user interfaces.

This package can be used by other packages using the GIRepository format to generate dynamic bindings.

MayaVi2 — багатоплатформовий інструмент для візуалізації наукових даних у 2-D та 3-D. Серед його можливостей:

• візуалізація скалярних, векторних і тензорних даних у 2-х та 3-х вимірах;

• просте використання сценаріїв за допомогою Python;

• легка розширюваність за допомогою додаткових джерел користувача, модулів та фільтрів даних;

• читання кількох форматів: VTK (старий та XML), PLOT3D і т.д.;

• збереження візуалізації;
• збереження візуалізацій в різних графічних форматах.

MayaVi2 був створений з думкою про розширюваність та використання сценаріїв. Але MayaVi2 є корисним застосунком сам по собі, він також може бути використаний як Передбачальний (Envisage) втулок, який дозволяє вбудовувати MayaVi2 безпосередньо у застосунки користувача. Крім того, він може бути використаний в якості рушія візуалізації для будь-якого застосунка.

Цей пакунок також впроваджує TVTK, який обертає об’єкти VTK для забезпечення зручності використання, API для мови Python, підтримуючи при цьому атрибути Traits та масиви NumPy/SciPy. TVTK реалізується в основному на чистому Python, за винятком невеликих модулів розширення.

Meshio can read from and write to various data formats representing unstructured meshes, such as DOLFIN, Gmsh, H5M or VTK.

This package provides the command-line tools, and a plugin for paraview.

This package also provides Flavien Loiseau's msh2xdmf tool to convert from MSH to XDMF mesh formats.

ParaView — багатоплатформний застосунок з відкритими джерельними кодами, розроблений для візуалізації наборів даних як великих розмірів так і малих. Метою проекту ParaView є:

• розробка застосунку для візуалізації, багатоплатформного з відкритими джерельними кодами

• підтримка розподіленої моделі обчислень, що оперують великими обсягами даних

• створення відкритого, гнучкого та інтуїтивно зрозумілого інтерфейсу користувача

• розробка гнучкої архітектури на основі відкритих стандартів

ParaView працює на системах із розділюваною та спільною пам’яттю, а також на однопроцесорних системах, її також було успішно протестовано у Windows, Linux, MacOS та різних робочих станціях Unix, а також кластерах й суперкомп’ютерах. ParaView використовує Visualization Toolkit в якості рушія для обробки та візуалізації даних; інтерфейс користувача написаний з використанням бібліотеки Qt.

ParaView is an open-source, multi-platform application designed to visualize data sets of size varying from small to very large. The goals of the ParaView project include the following:

* Develop an open-source, multi-platform visualization application.
* Support distributed computation models to process large data sets.
* Create an open, flexible, and intuitive user interface.
* Develop an extensible architecture based on open standards.

ParaView runs on distributed and shared memory parallel as well as single processor systems and has been successfully tested on Windows, Mac OS X, Linux and various Unix workstations, clusters and supercomputers. Under the hood, ParaView uses the Visualization Toolkit as the data processing and rendering engine and has a user interface written using Qt. Development header files

ParaView is an open-source, multi-platform application designed to visualize data sets of size varying from small to very large. The goals of the ParaView project include the following:

* Develop an open-source, multi-platform visualization application.
* Support distributed computation models to process large data sets.
* Create an open, flexible, and intuitive user interface.
* Develop an extensible architecture based on open standards.

ParaView runs on distributed and shared memory parallel as well as single processor systems and has been successfully tested on Windows, Mac OS X, Linux and various Unix workstations, clusters and supercomputers. Under the hood, ParaView uses the Visualization Toolkit as the data processing and rendering engine and has a user interface written using Qt. Comprehensive documentation.

Plastimatch is an open source software for deformable image registration. It is designed for high-performance volumetric registration of medical images, such as X-ray computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography(PET). Software features include:

• B-spline method for deformable image registration (GPU and multicore accelerated), including support for image masking, landmark penalties, and regularization
• Demons method for deformable image registration (GPU accelerated)
• Multi-atlas segmentation
• ITK-based algorithms for translation, rigid, affine, multiple demons methods, and B-spline registration
• Pipelined, multi-stage registration framework with seamless conversion between most algorithms and transform types
• Landmark-based deformable registration using thinplate splines for global registration
• Landmark-based deformable registration using radial basis functions for local corrections
• Broad support for 3D image file formats (using ITK), including DICOM, Nifti, NRRD, MetaImage, and Analyze

• Extensive toolchain for radiotherapy research, including support for DICOM, DICOM-RT, DICOM SRO, XiO file format, gamma analysis, contour manipulation, contour overlap analysis, and vector field analysis Plastimatch also features two handy utilities which are not directly related to image registration:

• FDK cone-beam CT reconstruction (GPU and multicore accelerated)

• Digitally reconstructed radiograph (DRR) generation (GPU and multicore accelerated)

Freeart is a tomographic image reconstruction library using Algebraic Reconstruction Technique (ART). It is able to deal with absorption and emission sinograms. Freeart core is written in C++ using template classes to have simple or double precision. A python interface is provided to access the core functionalities. A set of utils such as configuration files, interpreter to run reconstruction from configuration files are provided in python.

Nabu can be used in several ways:

• As a Python library, by features like Backprojector, FlatField, etc
• As a standalone application with the command line interface
• From Tomwer (https://gitlab.esrf.fr/tomotools/tomwer/)

ParaView is an open-source, multi-platform application designed to visualize data sets of size varying from small to very large. The goals of the ParaView project include the following:

* Develop an open-source, multi-platform visualization application.
* Support distributed computation models to process large data sets.
* Create an open, flexible, and intuitive user interface.
* Develop an extensible architecture based on open standards.

ParaView runs on distributed and shared memory parallel as well as single processor systems and has been successfully tested on Windows, Mac OS X, Linux and various Unix workstations, clusters and supercomputers. Under the hood, ParaView uses the Visualization Toolkit as the data processing and rendering engine and has a user interface written using Qt. Enables python support.

scikit-image is a collection of image processing algorithms for Python. It performs tasks such as image loading, filtering, morphology, segmentation, color conversions, and transformations.

This package provides the Python 3 module.

Tomogui offers a Graphical User Interface to run tomographic reconstruction based on freeart and silx algorithms

Tomogui contains two main applications:

• tomogui project : to create a new project from scratch
• tomogui recons : to run reconstruction from a configuration file created by 'tomogui project'

This library is offering an abstraction to access tomography data from various file formats.

It can read:

• acquisitions from spec (.edf) and bliss (.hdf5)
• volumes:
• single frame file: EDF, JP2K, tiff
• multi frame: HDF5, multitiff

This repository contains Python data processing scripts to be used with the UFO framework. At the moment they are targeted at high-performance reconstruction of tomographic data sets.

Vispy is a high-performance interactive 2D/3D data visualization library.

Vispy leverages the computational power of modern Graphics Processing Units (GPUs) through the OpenGL library to display very large datasets.

This package provides VisPy for the Python 3 interpreter.

Rheolef is a computer environment that serves as a convenient laboratory for computations in applied mathematics involving finite element-like methods. It provides a set of commands and C++ algorithms and containers.

Most basically, containers cover the classic graph data structure for sparse matrix formats and finite element meshes. At a higher level of abstraction, they can handle approximate finite element spaces, discrete fields. Flexible and powerful expressions are used to specify bilinear forms.

Current applications include:

• massively distributed memory finite element environment, based on MPI;
• elasticity, Stokes and Navier-Stokes problems in 2D and 3D;
• complex fluids applications: viscoplasticity, viscoelasticity, wall slip;
• nonlinear problems with fixed-point, Newton and continuation methods;
• high order polynomials, mixed elements and discontinuous Galerkin methods;
• auto-adaptive mesh approaches;
• axisymmetric problems;
• multi-regions and variable coefficient problems.

This package provides the rheolef commands. These support input and output in various file formats for mesh-generators and numerical data visualization systems such as paraview, and gnuplot.

The UFO data processing framework is a C library suited to build general purpose streams data processing on heterogeneous architectures such as CPUs, GPUs or clusters. It is extensively used at the Karlsruhe Institute of Technology for Ultra-fast X-ray Imaging (radiography, tomography and laminography).

A gobject-instrospection binding is also provided to write scripts or user interfaces.

This package provides the documentation for libufo.

The UFO data processing framework is a C library suited to build general purpose streams data processing on heterogeneous architectures such as CPUs, GPUs or clusters. It is extensively used at the Karlsruhe Institute of Technology for Ultra-fast X-ray Imaging (radiography, tomography and laminography).

This package contains average',backproject', bin',blur', buffer',calculate', camera',clip', contrast',crop', denoise',duplicate', fftmult',fft', filter',flatten', flip',forwardproject', gemm',ifft', interpolate',loop', measure',merge', metaballs',monitor', null',opencl', ordfilt',pad', read',reduce', refeed',replicate', rescale',ringwriter', sleep',slice', stack',stdin', stdout',subtract', transpose',write' and `zeropad' plugins

The UFO data processing framework is a C library suited to build general purpose streams data processing on heterogeneous architectures such as CPUs, GPUs or clusters. It is extensively used at the Karlsruhe Institute of Technology for Ultra-fast X-ray Imaging (radiography, tomography and laminography).

This package provides the documentation for the plugins

It supports 2D parallel and fan beam geometries, and 3D parallel and cone beam. All of them have highly flexible source/detector positioning.

A large number of 2D and 3D algorithms are available, including FBP, SIRT, SART, CGLS.

The basic forward and backward projection operations are GPU-accelerated, and directly callable from Octave and Python to enable building new algorithms.

This is the Octave library.

It supports 2D parallel and fan beam geometries, and 3D parallel and cone beam. All of them have highly flexible source/detector positioning.

A large number of 2D and 3D algorithms are available, including FBP, SIRT, SART, CGLS.

The basic forward and backward projection operations are GPU-accelerated, and directly callable from Octave and Python to enable building new algorithms.

This is the Python3 library.

PyHST is a Python program for Tomographic data reconstruction based on direct filtered back-projection algorithm

This is the CUDA version

Features:

• Image reconstruction algorithms for tomography.
• Various filters, ring removal algorithms, phase retrieval algorithms.
• Forward projection operator for absorption and wave propagation.

RabbitCT provides an open platform for worldwide performance-comparison of backprojection implementations on different architectures using one specific, clinical, high resolution C-arm CT dataset of a rabbit. This includes a sophisticated benchmark interface, a prototype implementation in C++, and image quality measures.

provided prior to the tomography experiment.