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Data sustained misalignment correction in microscopic cone beam CT via optimization under the Grangeat Epipolar consistency condition
Author(s) -
Luo Shouhua,
Zheng Liang,
Luo Shuang,
Gu Ning,
Tang Xiangyang
Publication year - 2020
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1002/mp.13915
Subject(s) - epipolar geometry , cone beam computed tomography , consistency (knowledge bases) , cone beam ct , cone (formal languages) , optics , nuclear medicine , physics , mathematics , computed tomography , computer science , computer vision , medicine , radiology , geometry , algorithm , image (mathematics)
Purpose The misalignment correction in cone beam computed tomography (CBCT), which is usually carried out in an offline manner, is a difficult and tedious process. It becomes even more challenging in microscopic CBCT due to the much higher requirements on spatial resolution. In practice, however, an offline approach for misalignment correction may not be readily implementable, especially in the situations where either time is of the essence or the process needs to be carried out repetitively. Thus, an online self‐calibration (i.e., data sustained misalignment correction without the involvement of specific alignment phantom) would be more practical. In this work, we investigate the data sustained misalignment correction in microscopic CBCT via optimization under the Grangeat Epipolar Consistence Condition and evaluate its performance via phantom and specimen studies. Methods With the cost function defined according to the Grangeat Epipolar Consistency Condition (G‐ECC) and by minimizing the cost function using the simplex‐simulated annealing algorithm (SIMPSA), we evaluate and verify the G‐ECC optimization‐based online self‐calibration method's performance. Performance is measured in sensitivity, robustness, and accuracy using the projection data of phantoms generated by computer simulation and botanical specimens acquired by a prototype microscopic CBCT. Results The online data sustained misalignment correction in microscopic CBCT via G‐ECC optimization works very well in sensitivity and robustness, in addition to its accuracy of 0.27%, 0.48%, and 0.34% relative errors, respectively, in obtaining the three geometric parameters that are the most critical to image reconstruction in CBCT. Quantitatively, the performance in meeting the requirements on spatial resolution is comparable to, if not better than, that of the offline misalignment correction method, in which a specific alignment phantom has to be used. Conclusions The G‐ECC optimization‐based online self‐calibration approach provides a practical solution (as long as no latitudinal (lateral) data truncation occurs) for misalignment correction in microscopic CBCT, an application that demands high accuracy in geometric alignment for biological (cellular) imaging at super high spatial resolutions in the order of micrometers (2.1 µm).