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Open-source multi-dimensional tomographic reconstruction software (OMEGA)

Home Page: https://omega-doc.readthedocs.io/en/latest/index.html

License: GNU General Public License v3.0

MATLAB 47.43% C++ 27.59% C 3.37% Python 21.62%

emission-tomography reconstruction gate medical-imaging pet opengate opencl gpu gpgpu matlab

omega's Introduction

OMEGA

Open-source multi-dimensional tomographic reconstruction software for MATLAB, GNU Octave and Python.

Purpose

The purpose of OMEGA is twofold. First it is designed to allow easy, fast and efficient reconstruction of any ray-tracing based tomographic imaging. Secondly, it is intended for easy algorithmic development as it allows easy matrix-free implementation of the forward (A * x) and backward (A^T * y) projections. While OMEGA allows the use of any ray-tracing based tomographic data, it is optimized for positron emission tomography (PET), computed tomography (CT) and single emission computed tomography (SPECT).

Introduction

OMEGA is a software for MATLAB, GNU Octave and Python to reconstruct tomographic data. See Features for more information on available features. See Known Issues and Limitations below for software limitations. If you wish to add your own code (e.g. reconstruction algorithm) see Contributing code to OMEGA.

Documentation for the current version is available at https://omega-doc.readthedocs.io/en/latest/index.html

The algorithms implemented so far are:

Improved Siddon's ray tracer algorithm for the system matrix creation (code for regular Siddon available, but not used) [1,2]
Orthogonal distance-based ray tracer [3]
Volume of intersection ray tracer (THOR) [28].
Interpolation-based ray tracer [31]
Branchless distance-driven ray tracer [32,33]
Rotation-based projector [34]
Maximum Likelihood Expectation Maximization (MLEM) [4,5]
Ordered Subsets Expectation Maximization (OSEM) [6]
Complete-data Ordered Subsets Expectation Maximization (COSEM) [7]
Enhanced COSEM (ECOSEM) [8]
Accelerated COSEM (ACOSEM) [9]
Row-Action Maximum Likelihood Algorithm (RAMLA) [10]
Relaxed OSEM (ROSEM)
Rescaled Block-Iterative EM (RBI) [11]
Dynamic RAMLA (DRAMA) [12]
Modified RAMLA (MRAMLA), aka modified BSREM-2 [13]
Block Sequential Regularized Expectation Maximization (BSREM) [14]
One-step-late algorithm (OSL) [15]
Preconditioned Krasnoselskii-Mann algorithm (PKMA) [29]
Primal-dual hybrid gradient [35]
Condat-Vu [36,37]
Primal-dual Davis-Yin [38]
FISTA [39]
FDK [40]
LSQR [46]
CGLS [47]
Quadratic prior (Gibbs prior with quadratic potential function)
Huber prior [45]
Median Root Prior (MRP) [16]
L-filter (MRP-L) prior [17]
Finite Impulse Response Median Hybrid (MRP-FMH) prior [17,18]
Weighted mean prior [19,20]
Total variation (TV) [21, 22, 23]
Weighted TV [42]
Total generalized variation (TGV) [24]
Anisotropic diffusion (AD) Median Root Prior
Asymmetric parallel levels sets prior (APLS) [22]
Non-local means prior (NLM), including non-local TV [25,26,27]
Relative difference prior [30]
Generalized Gaussian Markov random field prior [41]
Modified hyperbolic prior [23,43]
Modified Lange prior [29,44]

Installation

For additional install help, see installation help.

Pre-built libraries are supplied in the releases, however, you can also manually compile everything.

For manual compilation you're going to need a C++ compiler in order to compile the MEX-files/libraries and use this software. Visual Studio and GCC have been tested to work and are recommended depending on your platform (Visual Studio on Windows, GCC on Linux, clang should work on MacOS). Specifically, Visual Studio 2019 and 2022 have been tested to work on Windows 10 and as well as g++ 9.3 and g++ 10.5 on Ubuntu 22.04. MinGW++ also works though it is unable to compile ArrayFire OpenCL reconstructions (implementation 2) on Windows by default. Octave supports only MinGW++ on Windows and as such implementation 2 on Windows is only supported if you manually compile ArrayFire from source with MinGW (for instructions, see here).

MinGW++ for MATLAB can be downloaded from here.

Visual studio can be downloaded from here. For Visual studio you'll only need "Desktop development with C++".

On Ubuntu you can install g++ with sudo apt install build-essential.

To install the OMEGA software, either simply extract the release/master package, download the MATLAB toolbox file from releases (OMEGA.-.Open-source.MATLAB.emission.tomography.software.mltbx) or obtain the source code through git:
git clone https://github.com/villekf/OMEGA and then add the OMEGA folder and subfolders to MATLAB/Octave path (this is done automatically if you install with the mltbx-file) or /path/to/OMEGA/source/Python to PYTHONPATH. Finally, run install_mex in the source folder to build the necessary MEX-files or compile.py with Python. ROOT, OpenCL and CUDA support will be installed, if the corresponding files are found. Possible compilation errors can be seen with install_mex(1). OpenCL include and library paths, ArrayFire path and ROOT path can also be set manually with install_mex(0, OpenCL_include_path, OpenCL_lib_path, AF_PATH, ROOT_PATH). OpenCL_include_path should be the folder where cl.h is located, OpenCL_lib_path the folder where OpenCL.lib/libOpenCL.so (Windows/Linux) is located, AF_PATH the path to ArrayFire installation location and ROOT_PATH to ROOT installation location. For Python the paths can be input with "python compile.py -R /path/to/ROOT -A /path/to/arrayfire -O /path/to/OpenCL".

Certain features on Octave (such as normalization calculation) require packages io and statistics. You can install them from the Octave user interface with the following commands (io has to be installed first):

pkg install -forge io

pkg install -forge statistics

and then you need to load the statistics package:

pkg load statistics

Python only requires NumPy, though to load mat-files you need pymatreader and for multi-resolution reconstruction scikit-image.

In order to enable OpenCL support (implementations 2 and 3), you're going to need an OpenCL SDK/library and (for implementation 2) ArrayFire (see below). On Linux you can alternatively just install the OpenCL headers and library. Below examples are for Ubuntu, but the packages should exist for other distros as well.

Headers (required only when manually building): sudo apt-get install opencl-headers

and then the library:
sudo apt-get install ocl-icd-opencl-dev

Alternative libraries in case the above one fails: sudo apt-get install nvidia-opencl-dev or sudo apt-get install intel-opencl-icd

In case the above doesn't work or you use Windows then you need to obtain an OpenCL SDK. The SDK can be any (or all) of the following: CUDA Toolkit, Intel OpenCL SDK, OCL-SDK, AMD APP SDK. On all cases, the OpenCL library and header files (only when manually building) need to be on your system's PATH. By default, the install_mex-file assumes that you have installed CUDA toolkit (Linux and Windows), AMD APP SDK v3.0 (Linux and Windows), OCL-SDK (Windows), AMD GPU Pro drivers (Linux) or Intel SDK (Linux and Windows). If you get an error message like "CL/cl.h: No such file or directory", the headers could not be found. You can manually add custom OpenCL paths with install_mex(0, '/path/to/cl.h', '/path/to/libOpenCL.so'). On Ubuntu you can use command find / -iname cl.h 2>/dev/null to find the required cl.h file and find / -iname libOpenCL.so 2>/dev/null to find the required library file. See install_mex.m for further details. compile.py functions similarly.

CUDA functionality requires CUDA toolkit.

All library paths needs to be on system path when running the mex-files or otherwise the required libraries will not be found.

Links:
https://software.intel.com/en-us/intel-opencl
https://developer.nvidia.com/cuda-toolkit
https://github.com/GPUOpen-LibrariesAndSDKs/OCL-SDK/releases

Once you have the header and library files, you need drivers/OpenCL runtimes for your device(s). If you have GPUs/APUs then simply having the vendor drivers should be enough. For Intel CPUs without an integrated GPU you need CPU runtimes (see the link below).

For AMD CPUs it seems that the AMD drivers released around the summer 2018 and after no longer support CPUs so you need an older driver in order to get CPU support or use an alternative runtime. One possibility is to use PoCL http://portablecl.org/ and another is to try the Intel runtimes (link below).

Intel runtimes can be found here: https://software.intel.com/en-us/articles/opencl-drivers

This software also uses ArrayFire library for the GPU/OpenCL implementation. You can find AF binaries from here:
https://arrayfire.com/binaries and the source code from here:
https://github.com/arrayfire/arrayfire

Installing/building ArrayFire to the default location (C:\Program Files\ArrayFire on Windows, /opt/arrayfire/ on Linux/MacOS) should cause install_mex and compile.py to automatically locate everything. However, in both cases you need to add the library paths to the system PATH. On Windows you will be prompted for this during the installation, for Linux you need to add /opt/arrayfire/lib or /opt/arrayfire/lib64 (depending which exists) to the library path (e.g. sudo ldconfig /opt/arrayfire/lib64/ or export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/opt/arrayfire/lib64 if you don't have sudo permissions). Alternatively, on Linux, you can also build/install ArrayFire directly into the /usr/local/ folder.

Using CUDA code instead of OpenCL requires the CUDA toolkit. On both cases the CUDA folder should be on the system path. install_mex and compile.py always attempts to build the CUDA code as well so no additional input is required from the user if all the header and library data is found. By default install_mex and compile.py looks for CUDA in /usr/local/cuda/ on Linux. On Windows, CUDA location is determined from the environmental variables (PATH).

For additional install help, see installation help.

Getting Started

For detailed installation instructions, see https://omega-doc.readthedocs.io/en/latest/installation.html

Precompiled libraries are included in releases. However, in case those do not work you can also manually compile all the necessary files. When using MATLAB or GNU Octave, run install_mex first. For Python, you need run compile.py located in /path/to/OMEGA/source/Python.

For basic usage, see https://omega-doc.readthedocs.io/en/latest/usage.html

Examples for MATLAB/GNU Octave are in main-files folder, while for Python in the aforementioned Python-folder.

Features

See Features for more information on available features

Additional features

These features can be used as independent functions without any input needed from any other OMEGA files

Save images (matrices) in MATLAB/Octave in NIfTI, MetaImage, Interfile, Analyze 7.5, DICOM and raw binary formats (saveImage.m)
Import NIfTI, MetaImage, Interfile, Analyze 7.5, DICOM and raw binary formats into MATLAB/Octave (importData.m)
Save images (matrices) in MATLAB/Octave in Interfile (saveInterfile.m) or MetaImage formats (saveMetaimage.m)
Convert CT-attenuation coefficients into 511 keV attenuation coefficients (attenuationCT_to_511.m)
(Experimental) Convert CT-attenuation coefficients directly from CT DICOM images into 511 keV attenuation coefficients (create_atten_matrix_CT.m)
Convert COO (Coordinate list) sparse matrix row indices into CSR (Compressed sparse row) indices (coo_to_csr.m)
Convert voxelized phantoms/sources into GATE compatible files (Voxelized_phantom_handle.m, Voxelized_source_handle.m)

System Requirements

MATLAB R2009a or later is mandatory. Following versions are guaranteed to work: 2022a and 2023b.

For Octave, any version above 5.0 should be fine. io, statistics and image packages are required for some features.

For Python 3.8 and above should work, though most likely earlier versions will work too.

C++11 compiler is required when manually compiling.

For Windows Visual Studio 2022 or 2019 is recommended with "Desktop development with C++", no other options are required. https://visualstudio.microsoft.com/

For Linux it is recommended to use g++ which usually comes bundled with the system.

On MacOS Xcode should be used https://apps.apple.com/us/app/xcode/id497799835?mt=12.

OpenCL library is required for OpenCL functionality.

ArrayFire is required for implementation 2.

For OpenCL, an OpenCL 1.2 compatible device is required. For CUDA, compute capability of 2.0 or higher is required.

The following third-party MATLAB codes are NOT required, but can be useful in certain specialized cases as they can be optionally used:
https://se.mathworks.com/matlabcentral/fileexchange/27076-shuffle (Shuffle, used by random subset sampling) https://se.mathworks.com/matlabcentral/fileexchange/22940-vol3d-v2 (vol3d v2, used for 3D visualization)
https://www.mathworks.com/matlabcentral/fileexchange/8797-tools-for-nifti-and-analyze-image (Tools for NIfTI and ANALYZE image, to load/save Analyze files and also NIfTI files in absence of image processing toolbox).

Known Issues and Limitations

MATLAB & Octave

LMF output currently has to contain the time stamp (cannot be removed in GATE) and detector indices. The source location needs to be included if it was selected in the main-file, same goes for the scatter data. If you have any other options selected in the LMF output in GATE, then you will not get any sensible detector data. Source locations and/or scatter data can be deselected. LMF data, with different format than in GATE, are not supported.

LMF source information is a lot more unreliable than the ASCII or ROOT version. LMF support has been deprecated in version 2.0.

Moving bed is not supported at the moment (needs to be step-and-shoot and the different bed positions need to be handled as separate cases).

Only cylindrical symmetric scanners are supported inherently, for other types of scanners the user has to input the detector coordinates or use index-based reconstruction.

For CT, only cone beam flat panel scanners are supported. For other types of scanners, the user has to input the detector coordinates or modify the data such that it is approximately flat panel.

ROOT or ASCII data is not yet supported with GATE CT data.

ECAT geometry is supported only with ASCII data. ROOT data might also work (untested).

If you are experiencing crashes when using implementation 2, it might be caused by the graphics features of ArrayFire. In this case I recommend renaming/removing the libforge.so files from the ArrayFire library folder (e.g. /opt/arrayfire/lib64/). Alternatively you can install the no-gl AF:
http://arrayfire.s3.amazonaws.com/index.html (3.6.2 is the latest). Finally, you can also simply build AF from source, preferably without building Forge. This seems to apply only to Linux and affects both MATLAB and Octave. Python is unaffected!

MATLAB

If you get GLIBCXX_3.4.XX/CXXABI_1.3.XX not found error (or similar with a different version number) or an error about "undefined reference to dlopen/dlclose/dlsomethingelse" when building or running files, this should be fixed with one of the methods presented here:
https://se.mathworks.com/matlabcentral/answers/329796-issue-with-libstdc-so-6

Or see the solutions in installation help.

If you are using ROOT data with ROOT 6.16.00 or newer you might receive the following error message: "undefined symbol: _ZN3tbb10interface78internal20isolate_within_arenaERNS1_13delegate_baseEl". This is caused by the libtbb.so.2 used by MATLAB (located in /matlabroot/bin/glnxa64). Same solutions apply as with the above case (e.g. renaming the file). See installation help for details.

ROOT data import is unstable in MATLAB R2018b and earlier versions due to a library incompatibility between the Java virtual machine in MATLAB and ROOT. On Linux you will experience MATLAB crashes when importing ROOT data. There is a workaround for this by using MATLAB in the no Java mode (e.g matlab -nojvm), though you won't have any GUI or graphic features. MATLAB R2019a and up are unaffected. It is recommended to use nojvm for data load only (set options.only_sinos = true to load only the data). The new desktop might not have this issue, but this is currently untested.

Octave

When using Windows implementation 2 (ArrayFire matrix free OpenCL) can only be enabled by manually building ArrayFire with Mingw. Instructions are provided here. Note that CUDA won't work even with manual building.

Almost all MATLAB-based code runs significantly slower compared to MATLAB (this is due to the slowness of loops in Octave). Reconstructions are unaffected.

MAT-files that are over 2 GB are not supported by Octave and such large data sets cannot be saved in Octave at the moment.

Python

Only implementation 2 is supported.

Status messages, such as the current iteration number, might be displayed only after the computation is already done.

Upcoming Features

Here is a list of features that should appear in future releases:

New SPECT projector
PET scatter correction based on SSS
Improved dual-layer PET support

Reporting Bugs and Feature Requests

For any bug reports I recommend posting an issue on GitHub. For proper analysis I need the main-file that you have used and if you have used GATE data then also the macros. Preferably also all possible .mat files created, especially if the problem occurs in the reconstruction phase.

For feature requests, post an issue on GitHub. I do not guarantee that a specific feature will be added in the future.

Citations

If you wish to use this software in your work, cite this paper: V-V Wettenhovi et al 2021 Phys. Med. Biol. 66 065010. The peer reviewed (open access) paper on OMEGA can be found from https://doi.org/10.1088/1361-6560/abe65f.

If you use some of the specific algorithm or prior, please cite one of references here or some other original paper.

Acknowledgments

Original versions of COSEM, ACOSEM, ECOSEM, RAMLA, MRAMLA, MRP, L-filter, FMH, weighted mean, quadratic prior, sinogram coordinate and sinogram creation codes were written by Samuli Summala. Normalization coefficient and variance reduction codes were written by Anssi Manninen. Initial work on TOF was done by Jonna Kangasniemi. Initial work on SPECT was done by Matti Kortelainen and Akuroma George. All other codes were written by Ville-Veikko Wettenhovi. Some pieces of code were copied from various websites (Stack Overflow, MATLAB Answers), the original sources of these codes can be found in the source files.

This work was supported by a grant from Jane and Aatos Erkko foundation, Instrumentarium Science Foundation, Jenny and Antti Wihuri Foundation and The Finnish Research Impact Foundation. This work has been supported by University of Eastern Finland and Academy of Finland.

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Christopher C. Paige and Michael A. Saunders. 1982. "LSQR: An Algorithm for Sparse Linear Equations and Sparse Least Squares," ACM Trans. Math. Softw. 8, 1 (March 1982), 43–71. https://doi.org/10.1145/355984.355989
Hestenes, Magnus R. and Eduard Stiefel. "Methods of conjugate gradients for solving linear systems," Journal of research of the National Bureau of Standards 49 (1952): 409-435. https://doi.org/10.6028/jres.049.044

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omega's Issues

Compulsory to convert raw data to mat format?

Hi villekf/OMEGA,

If I have PET raw data, is it compulsory to convert it to mat format to run using main_Pet.m?

error when run install mex in matlab

Dear all,

want to ask, I was run install mex in matlab. but have error like below

Error using mex
C:\Users\Akmal\Documents\MATLAB\Add-Ons\Toolboxes\OMEGA - Open-source MATLAB emission tomography
software\code\source\gate_lmf_matlab.cpp: In function 'void histogram(uint16_t*, uint16_t*,
uint64_t*, char*, double, double, double, size_t, uint32_t, int, int, int, int, int, int, int,
int, int, int, int, double, bool, uint32_t, uint32_t, uint32_t, uint32_t, int16_t*, size_t,
uint64_t*, double, int*, const double*, bool, bool, bool, uint16_t*, uint16_t*, uint16_t*,
uint8_t*, uint32_t, uint32_t, uint32_t, uint64_t, uint32_t, uint32_t, uint32_t, uint32_t, const
uint32_t*, uint64_t, uint64_t, int32_t, bool, uint16_t*, uint16_t*, uint16_t*, uint16_t*,
int32_t, int32_t)':
C:\Users\Akmal\Documents\MATLAB\Add-Ons\Toolboxes\OMEGA - Open-source MATLAB emission tomography
software\code\source\gate_lmf_matlab.cpp:50:30: error: 'fopen_s' was not declared in this scope
  fopen_s(&streami, argv, "rb");
                              ^


Error in install_mex (line 350)
    mex('-largeArrayDims', '-outdir', folder, [folder '/gate_lmf_matlab.cpp'])

can someone help me solve this problem?

OMEGA- gcc compiler versions

Hi,
I am the newset member to be working on the OMEGA software, I have started a week ago and I am currently in the installation proccess. I would like to ask about the gcc compiler please, and running the mex.m file. I have tried to run the install_mex.m file and I had many errors, one of the errors was with the compiler's version. The current gcc is v 7.4.0 would it be possible to get the older version 5.4.0 without removing nor overlapping the current version? If yes, how? and would it maybe fix the error of not being able to run install_mex.m file? If it wouldn't matter, what would be the optimal solution from your point of view? I can send the full error report if needed.

Thank you!

Invenon PET data issue

hello Ville,

Greetings from USTC, China.,
My name is Qianxue, a Master student under the supervision of Prof.Dong Liu.
Currently we are trying to apply the well established PET softerware-OMEGA in our project, however, we face few questions, which we would like to get your help on this purpose.

Q1: When I was attemping to use the Inveon PET data provided by the OMEGA, which obtained from https://doi.org/10.5281/zenodo.3528056.
I found some apparent ARTIFACTS in the sinogram. What's the reason lies behind it?

Q2: I want to get more raw data to test on the OMEGA, but most of the data I get is in DICOM format. I was wondering whether this kind of data can be used to perform the reconstrucion. And where can I get more raw data?

Best wishes,
Qianxue

about voxel size in the reconstruction image

Dear villekf,

I'm sorry to trouble you so many times.
I want to know how to modify or decision the voxel size in the reconstructed image?
And I also want to know why the list-mode reconstructed image arise too much noise and artifacts?(The example in Inveon_PET_main_listmode_example.m, and I don't modify anything.)

Best wishes.

Issue when running Inveon_PET_main.m

Dear sir,
Hello. In Inveon_PET_main.m ,when I run the code in MATLAB, an error occurs:

Inveon_PET_main
Unrecognized function or variable 'OMEGA_error_check'.

Error in Inveon_PET_main (line 1739)
options = OMEGA_error_check(options);

How do I solve this problem？
Thanks.

About gate_CT_main.m

Dear villekf,

I think OMEGA is a great work, but I encountered some problems when I ran gate_CT_main.m. I had run the classic CT example of GATE. And I used the "ACQUISITION with 360 projections" in the acquisition.mac of the example. But when I ran the gate_CT_main.m in MATLAB and select one CTimage dat file of 360, I got some errors:

Error using .*
Matrix dimensions must agree.

Error in CTDetectorCoordinates (line 88)
XY = squeeze(sum(R .* [detCoordX,detCoordY],2))';

Error in reconstructions_mainCT (line 110)
[options.x,options.y,options.z] = CTDetectorCoordinates(options.angles,options.sourceToDetector,options.sourceToCRot,options.dPitch,options.xSize,...

Error in gate_CT_main (line 1031)
pz = reconstructions_mainCT(options);

How to fix it?

best wishes,
Parsons

Compiling cpp source code as standalone shared library

Hi!
It's kind of a weird question, I guess, but I will try, nontheless.
This software is really nice, I just discovered it between the abstracts for ISBI 2020.

I am also in the "job" of developing PET reconstruction softwares, but in Python, not in Matlab (you can check https://github.com/TomographyLab/TomoLab, if you are interested). I would really like to test the projectors code you wrote for OMEGA (the one to be compiled as a mex file) within my library, to compare it with the one I am currently using.

The problem is that I am not really familiar with writing source code for Mex files, and I don't know if it is unrealistic to think to separate the C++ code from the Mex wrapper. I mean, avoiding including mex.h, etc...

Two questions:

would you be OK with me trying such an 'improper' use of your code?
do you have any idea how hard would it be to adapt the source of the mex files, so that it could be compiled as a shared library, with no need for Matlab to run these functions?

Thanks a lot for the attention.

How to see the image have done reconstruction

Hi villekf/OMEGA,

I have run main.PET.m using below data that you giving in your website as below

Cylindrical_PET_example_cylpet_example_sinograms_combined_static_200x168x703_span3.mat

but the final command it just write Reconstruction process took 327.4303 seconds

NO IMAGE appear.

How to see the image have done reconstruction?

output reconstruction direction

Hello. Thank you so much for this great app. I have reconstructed the output of a GATE CT scan simulation with this program. But I could not find the output direction of the final reconstruction. Where to save the reconstructed file? thanks a lot

Some error when using attenuation_correction in Inveon_PET_main.m

Dear sir,
Hello. In Inveon_PET_main.m ,when I set options.attenuation_correction = true,there will appear a mistake in command window:The function or variable 'tStart' is not recognized.How do I solve this problem？
Thanks.

ROOT issue

Hi sir,
I was using OMEGA on MacOS.
When I run install_mex
some warning pomp up as below

warning: Unable to build ROOT support! If you do not need ROOT support ignore this warning.
Otherwise make sure that ROOT was compiled with the same compiler you are using to
compile this mex-file and provide the path to ROOT install folder with install_mex(0, [],
[], [], '/path/to/ROOT'). Compiler error is shown with install_mex(1) 
> In install_mex (line 456)

warning: CUDA support not enabled 
> In install_mex (line 587)

How to solve this problem?

about normalization correction

Hello,I ran benchPET.mac and benchPET_norm.mac and got the corresponding ascii data.but I am not sure how to normaliza the sinogram data generated by using the benchPET.mac.can you give me some advice?Thank you very much.

main_PET.m issue

Dear villekf,
When I using main_PET.m for my own scanner and my own data ,it appears some mistakes.The command window as follow:

My data format is contain the crystal number only:

What can i do to handle this error?
Best wishes

Add support for gaps between detector rings

Currently the only way to add gaps between detector rings is to either add pseudo rings or manually adjust the coordinates. It would be better if the user could add information on the gaps in the main-files which would then be automatically taken into account when computing the detector coordinates.

Self-designed CT reconstruction using OMEGA

Dear villekf,
I am using OMEGA for my self-designed CT image reconstruction, but the output image is inconsistent with the phantoml I designed, is there any way to solve it?
The following are the parameters set during reconstruction, the projection image obtained from CT, and the reconstructed image, and the phantom image.

options.binning = 1;
options.xSize = 1536/options.binning;
options.ySize = 1536/options.binning;
options.nProjections = 360;
options.angles = -linspace(0, 359, options.nProjections);
options.dPitch = 0.139*options.binning;
options.sourceToDetector = 389.4;
options.sourceToCRot = 254;
options.name = 'OURSELF_CT_data';
options.only_reconstructions = false;
options.verbose = true;
options.FOVa_x = 102.4;
options.FOVa_y = options.FOVa_x;
options.axial_fov = 102.4;

Projection image:

Reconstructed image:

Phantom image:

best wishes

Unrecognized function or variable 'vol3d'.

Dear villekf,

i run the code for visualize_pet.m

but the error pop up below. How to solve it?

Unrecognized function or variable 'vol3d'.

Error in visualize_pet (line 371)
figure;vol3d('CData', permute(img(:,:,:,end), [3 2 1 4]), 'Alpha', alpha);

WHICH THE BEST ALGORITHM FOR SPECT IMAGE

Dear villekf/OMEGA,

For SPECT images, which one of the best algorithm can be applied to produce best image quality?

Improved Siddon's ray tracer algorithm for the system matrix creation (code for regular Siddon available, but not used) [1,2]
Orthogonal distance-based ray tracer [3]
Volume of intersection ray tracer (THOR) [28].
Maximum Likelihood Expectation Maximization (MLEM) [4,5]
Ordered Subsets Expectation Maximization (OSEM) [6]
data Ordered Subsets Expectation Maximization (COSEM) [7]
Enhanced COSEM (ECOSEM) [8]
Accelerated COSEM (ACOSEM) [9]
Row-Action Maximum Likelihood Algorithm (RAMLA) [10]
Relaxed OSEM (ROSEM)
Rescaled Block-Iterative EM (RBI) [11]
Dynamic RAMLA (DRAMA) [12]
Modified RAMLA (MRAMLA), aka modified BSREM-2 [13]
Block Sequential Regularized Expectation Maximization (BSREM) [14]
One-step-late algorithm (OSL) [15]
Quadratic prior (Gibbs prior with quadratic potential function)
Median Root Prior (MRP) [16]
L-filter (MRP-L) prior [17]
Finite Impulse Response Median Hybrid (MRP-FMH) prior [17,18]
Weighted mean prior [19,20]
Total variation (TV) [21, 22, 23]
Total generalized variation (TGV) [24]
Anisotropic diffusion (AD) Median Root Prior
Asymmetric parallel levels sets prior (APLS) [22]
Non-local means prior (NLM), including non-local TV [25,26,27]

Try this recon method ACOSEM

Hi sir,

i done run main_PET.m

and I try this recon method ACOSEM. i changed to true.

%%% Accelerated COSEM (ACOSEM)
% Supported by implementations 1, 2 and 4
options.acosem = true;

It work. but when i run visualize_pet.m the error pop up as below.

visualize_pet
Warning: The current selected algorithm does not contain any estimes! 
> In check_algorithms (line 15)
In visualize_pet (line 83) 
The following are contained in the input array:
Element 10: ACOSEM



CAN SOMEONE HELP ME?

About Multi-layer PET

dear villekf,

OMEGA is a great work, and thank you so much.
What I want to ask is about PET reconstruction with DOI information.
Does it support DOI reconstruction?

best wishes,
galadriel

gate_main.m issue

Hi,
When I run gate_main.m on Mac, the error pop up as below:

Error using save
Cannot create 'Cylindrical_PET_example_lor_pixel_count_128x128x63_sino_200x168x703.mat'
because '/Users/shanqianxue/Library/Application Support/MathWorks/MATLAB
Add-Ons/Toolboxes/OMEGA - Open-mat-files/ MATLAB emission tomography
software/mat-files' does not exist.

Error in lor_pixel_count_prepass (line 455)
                    save(file_string,'lor','-v7.3')

Error in precompute_data (line 46)
    lor_pixel_count_prepass(options);

Error in gate_main (line 1639)
   precompute_data(options);

Because there is a space before the file name MATLAB emission tomography software.
But I didn't find the way to correct it in inlor_pixel_count_prepass.m.
How can I change the save path?

About gate_CT_main.m

Dear villekf,

Error using .*
Matrix dimensions must agree.

Error in CTDetectorCoordinates (line 88)
XY = squeeze(sum(R .* [detCoordX,detCoordY],2))';

Error in reconstructions_mainCT (line 110)
[options.x,options.y,options.z] = CTDetectorCoordinates(options.angles,options.sourceToDetector,options.sourceToCRot,options.dPitch,options.xSize,...

Error in gate_CT_main (line 1031)
pz = reconstructions_mainCT(options);

How to fix it?

best wishes,
Parsons

about voxel size in the reconstruction image

Dear villekf,

Best wishes.

problem when trying to reconstruct mCT and Vision data

Hello, there:
I am trying to using devel version to reconstruct mCT(32-bit list mode) and Vision(64-bit list mode) raw data.
Both have problems.
For mCT, the code stopped when trying to load the data. Below is the screent print when running the code:
"">> Biograph_mCT_main
Using 32-bit list-mode data with TOF (13 bins).
Using implementation 4.
OSEM reconstruction method selected.
No precomputed data will be used.
Improved Siddon's algorithm used with 1 transaxial ray and 1 axial ray.
Randoms correction ON.
Sinogram gap filling ON.
Corrections applied during reconstruction (ordinary Poisson).
Using STATIC sinogram data (prompts).
Every 8th column measurement is taken per subset.
Using an image (matrix) size of 128x128x109 with 3 iterations and 8 subsets.
Beginning data load""

And the error is as shown in figure 1.

For Vision, the code can load the data successfully but the matlab quit after "Start Reconstruction".

I attached the list mode data for both mCT and Vision and could you please help me to figure it out what is the problem?

https://drive.google.com/file/d/1z4BM0mJ0gWlOGrUuEdni5NxnQCHxsNTf/view?usp=drive_link

Thank you so much.
Ethan

ACOSEM

Hi sir,

i done run main_PET.m

and I try this recon method ACOSEM. i changed to true.

%%% Accelerated COSEM (ACOSEM)
% Supported by implementations 1, 2 and 4
options.acosem = true;

It work. but when i run visualize_pet.m the error pop up as below.

visualize_pet
Warning: The current selected algorithm does not contain any estimes! 
> In check_algorithms (line 15)
In visualize_pet (line 83) 
The following are contained in the input array:
Element 10: ACOSEM



CAN SOMEONE HELP ME?

SPECT reconstruction coding

Hi sir and all,

Anyone can help me to develop coding for reconstruction SPECT image?

I will pay for it. I really needed it.

Please help me.

PET system with more than 65536 detectors

Hi!

I'm attemting to use this software to reconstruct data comming from a PET system with more than 65536 detector? I don't know how to modify the code. Any suggestion please?

Thank you!

BSREM ALGORITHM

Hi Sir, want to ask you.

Did your algorithm Block Sequential Regularized Expectation Maximization (BSREM) [14] is same with
Bayesian penalized likelihood reconstruction algorithm (BSREM) ??

No ASCII (.dat) coincidence files were found

Hi villekf/OMEGA,

why i run gate_main_simple.m the error pop up below?

Error using load_data (line 575)
No ASCII (.dat) coincidence files were found. Check your filepath (options.fpath) or current
folder.

Error in gate_main_simple (line 420)
    options.coincidences = load_data(options);

is it have to locate the raw data that you give here https://doi.org/10.5281/zenodo.3522199 in somewhere folder?

Inveon_PET_main.m issue

Hi sir,
I am a rookie in this field. When I run the Inveon data from Zenodo

>>Inveon_PET_main

the error pop up as below

Error using inveon_list2matlab
16 input arguments required.

Error in load_data (line 175)
    [LL1, LL2, tpoints, DD1, DD2, raw_SinM, SinD] =
    inveon_list2matlab(nimi,(vali),(alku),(loppu),pituus, uint32(detectors),
    options.randoms_correction, sinoSize, ...

Error in Inveon_PET_main (line 1680)
    options.coincidences = load_data(options);

Can someone tell the problem is?

main_PET.m issue

Dear sir, when I want to run my own raw data PET, I use this code

>> main_PET.m

but error like below pop up

Error using OMEGA_error_check (line 304)
Implementation 4 supports only one OS and one MLEM algorithm at a time.

Error in main_PET (line 1390)
options = OMEGA_error_check(options);

can someone tell the problem is?

Projection images for the 3D walnut example

Hi!

I can't find the projection images in the link given in walnut_CT_main.m ... Or if it's in the .mat files, how to extract them ?

Sorry if it's a stupid question, I'm a newbie to matlab...
Thanks for providing OMEGA, it's really useful !
Cheers,
Thomas

How to save image

Hi villekf/OMEGA,

I done run for OSEM and ACOSEM method. the image can view.

but how to save image in my foder as dicom format?

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