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Gratopy 0.1

Kristian Bredies; Richard Huber


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        <foaf:name>Richard Huber</foaf:name>
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    <dct:description>&lt;p&gt;The gratopy (&lt;strong&gt;Gr&lt;/strong&gt;az &lt;strong&gt;a&lt;/strong&gt;ccelerated &lt;strong&gt;to&lt;/strong&gt;mographic projections for &lt;strong&gt;Py&lt;/strong&gt;thon) toolbox is a Python3 software package for the efficient and high-quality computation of Radon transforms, fanbeam transforms as well as the associated backprojections. The included operators are based on pixel-driven projection methods which were shown to possess &lt;a href="https://epubs.siam.org/doi/abs/10.1137/20M1326635"&gt;favorable approximation properties&lt;/a&gt;. The toolbox offers a powerful parallel OpenCL/GPU implementation which admits high execution speed and allows for seamless integration into &lt;a href="https://documen.tician.de/pyopencl/"&gt;PyOpenCL&lt;/a&gt;. Gratopy can efficiently be combined with other PyOpenCL code and is well-suited for the development of iterative tomographic reconstruction approaches, in particular, for those involving optimization algorithms.&lt;/p&gt; &lt;p&gt;&lt;strong&gt;Highlights&lt;/strong&gt;&lt;/p&gt; &lt;ul&gt; &lt;li&gt;Easy-to-use tomographic projection toolbox.&lt;/li&gt; &lt;li&gt;High-quality 2D projection operators.&lt;/li&gt; &lt;li&gt;Fast projection due to custom OpenCL/GPU implementation.&lt;/li&gt; &lt;li&gt;Seamless integration into PyOpenCL.&lt;/li&gt; &lt;li&gt;Basic iterative reconstruction schemes included (Landweber, CG, total variation).&lt;/li&gt; &lt;li&gt;Comprehensive documentation, tests and example code.&lt;/li&gt; &lt;/ul&gt;</dct:description>
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