In this article we present the NeuTomPy Toolbox, a new Python package for tomographic data processing and reconstruction. The toolbox includes pre-processing algorithms, artifacts removal and a wide range of iterative reconstruction methods as well as the Filtered Back Projection algorithm. The NeuTomPy toolbox was conceived primarily for neutron tomography datasets and developed to support the need of users and researchers to compare state-of-the-art reconstruction methods and choose the optimal data processing workflow for their data. In fact, in several cases sparse-view datasets are acquired to reduce scan time during a neutron tomography experiment. Hence, there is great interest in improving quality of the reconstructed images by means of iterative methods and advanced image-processing algorithms. The toolbox has a modular design, multi-threading capabilities and it supports Windows, Linux and Mac OS operating systems. The NeuTomPy toolbox is open source and it is released under the GNU General Public License v3, encouraging researchers and developers to contribute. In this paper we present an overview of the main toolbox functionalities and finally we show a typical usage example.
Micieli, D., Minniti, T., Gorini, G. (2019). NeuTomPy toolbox, a Python package for tomographic data processing and reconstruction. SOFTWAREX, 9, 260-264 [10.1016/j.softx.2019.01.005].
NeuTomPy toolbox, a Python package for tomographic data processing and reconstruction
Minniti, Triestino;
2019-01-01
Abstract
In this article we present the NeuTomPy Toolbox, a new Python package for tomographic data processing and reconstruction. The toolbox includes pre-processing algorithms, artifacts removal and a wide range of iterative reconstruction methods as well as the Filtered Back Projection algorithm. The NeuTomPy toolbox was conceived primarily for neutron tomography datasets and developed to support the need of users and researchers to compare state-of-the-art reconstruction methods and choose the optimal data processing workflow for their data. In fact, in several cases sparse-view datasets are acquired to reduce scan time during a neutron tomography experiment. Hence, there is great interest in improving quality of the reconstructed images by means of iterative methods and advanced image-processing algorithms. The toolbox has a modular design, multi-threading capabilities and it supports Windows, Linux and Mac OS operating systems. The NeuTomPy toolbox is open source and it is released under the GNU General Public License v3, encouraging researchers and developers to contribute. In this paper we present an overview of the main toolbox functionalities and finally we show a typical usage example.File | Dimensione | Formato | |
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D. Micieli, T. Minniti, G. Gorini, SoftwareX 9 (2019) 260-264.pdf
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