Fast and flexible X-ray tomography using the ASTRA toolbox.

By Wim van Aarle, Willem Jan Palenstijn, J. Cant, Eline Janssens, F. Bleichrodt, Andrei Dabravolski, J. De Beenhouwer, K. Joost Batenburg, Jan Sijbers. Optics Express, 2016

930 citations recorded by the source corpus.

Object reconstruction from a series of projection images, such as in computed tomography (CT), is a popular tool in many different application fields. Existing commercial software typically provides sufficiently accurate and convenient-to-use reconstruction tools to the end-user. However, in applications where a non-standard acquisition protocol is used, or where advanced reconstruction methods are required, the standard software tools often are incapable of computing accurate reconstruction images. This article introduces the ASTRA Toolbox. Aimed at researchers across multiple tomographic application fields, the ASTRA Toolbox provides a highly efficient and highly flexible open source set of tools for tomographic projection and reconstruction. The main features of the ASTRA Toolbox are discussed and several use cases are presented.

Subfields: Biomedical Engineering, Radiation, Radiology, Nuclear Medicine and Imaging

View Paper: https://www.semanticscholar.org/paper/a53adacb2702afa29232fc3c59c8733ec2e648da

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Biomedical Engineering

1. Ozan Öktem
2. Jonas Adler
3. Shuhao Cao

In Radiation

1. Jong Chul Ye
2. Zongben Xu
3. Yoseob Han

In Radiology, Nuclear Medicine and Imaging

1. Jonas Adler
2. Ozan Öktem
3. Jong Chul Ye
4. Zongben Xu
5. Yoseob Han

Citations in the corpus

• Learned Primal-Dual Reconstruction (2017, methodology): “We used the ODL operator RayTransform in order to evaluate the ray transform and its adjoint using the graphics processing unit (GPU) accelerated ‘astra_gpu’ backend [27].”