Automatic detection of rotational centers using GPU from projection data for micro-tomography in synchrotron radiation

Yongsheng Pan; Francesco De Carlo; Xianghui Xiao

doi:10.1117/12.911561

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3 March 2012 Automatic detection of rotational centers using GPU from projection data for micro-tomography in synchrotron radiation

Yongsheng Pan, Francesco De Carlo, Xianghui Xiao

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Proceedings Volume 8313, Medical Imaging 2012: Physics of Medical Imaging; 831328 (2012) https://doi.org/10.1117/12.911561
Event: SPIE Medical Imaging, 2012, San Diego, California, United States

Abstract

Determination of the rotation axis position for tomographic projection images is critical to perform an accurate reconstruction. Rotational centers in micro-tomography may shift by several microns after the initial calibration due to various factors such as temperature variation, sample system stability and sample loading procedures. Automatic detection of rotational centers after data acquisition is therefore crucial for accurate and efficient reconstructions, and it is commonly implemented at various synchrotron facilities. We propose to implement a reliable cross correlation method on the projections of 0 and 180 degree to automatically re-align the rotation axis at data collection time. For this purpose, several issues, such as the flat-field correction for the imaging system and the irregular data near projection boundaries, are handled to increase the stability achieving subpixel alignments. The method is shown from experimental results to be accurate, efficient and stable. The results from automatic detections are mostly within one pixel difference from manual/operator detection results. Following the data collection we developed an automatic sub-pixel rotational centering method. Intermediate results from this final process are generated for user inspection. The proposed method is able to detect rotational center shifts within 7 seconds for high-resolution projections of size 2048×2048. It is shown to be stable for static samples in complicated cases. GPU is utilized to fasten the cross correlation computation in the space domain, which achieves about 10 times speedup. The proposed method fits seamlessly into the current framework of beamline 2-BM at the Advanced Photon Source, Argonne National Laboratory. It may save 5 minutes for partial reconstructions and 5-10 minutes for manual detections without sacrificing accuracy.

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Yongsheng Pan, Francesco De Carlo, and Xianghui Xiao "Automatic detection of rotational centers using GPU from projection data for micro-tomography in synchrotron radiation", Proc. SPIE 8313, Medical Imaging 2012: Physics of Medical Imaging, 831328 (3 March 2012); https://doi.org/10.1117/12.911561

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