Development of an Auto Sample Centering Algorithm at the Macromolecular Crystallography Beam Line of the Pohang Light Source

단백질 결정학 빔 라인에서의 자동 샘플 정렬 알고리즘 개발

  • Published : 2006.07.01

Abstract

An automatic sample centering system is underway at the protein crystallography beam line of the Pohang Light Source to improve the efficiency of the crystal screening process. A sample pin which contains a protein crystal is mounted on a goniometer head. Then the crystal should be moved to the center of X-ray beam by controlling the motorized goniometer to obtain diffraction data. Since the X-ray beam is located at the center of the image obtained from the CCD camera when the image of the sample pin is in focus, an auto-focusing algorithm is a very important part in the auto-sample-centering system. However the results of applying several well-known auto focusing algorithms directly to the images are not satisfactory owing to the following factors: misalignment of CCD camera, non-uniform cryo-stream in the background of the image and the supporter of the loop. The performance of an auto-focusing algorithm can be increased if the algorithm is applied to only the loop region identified. Non-uniform cryo-stream and a various illumination condition and a stain, which is shown in the image, are main obstacles to loop region identification. In this paper, a simple loop region identification algorithm, which can solve these problems, is proposed and the effective ness of the proposed scheme is shown by applying the auto-focusing algorithm to the loop region identified.

Keywords

References

  1. Pohl E, Ristau U, Gehrmann T, Jahn D, Robrahn B, Malthan D, Dobler H, Hermes C., 'Automation of the EMBL Hamburg protein crystallography beamline BW7B', J. Synchrotron Rad. 11, PP. 372-377, 2004 https://doi.org/10.1107/S090904950401516X
  2. Gyorgy Snell, Carl Cork, Robert Nordmeyer, Earl Cornell, George Meigs, Derek Yegian, Joseph Jaklevic, Jian Jin, Raymond C. Stevens, and Thomas Earnest, 'Technical Advance Automated Sample Mounting and Alignment System for Biological Crystallography at a Synchrotron Source', Structure, Vol. 12, pp. 537-545, 2004 https://doi.org/10.1016/j.str.2004.03.011
  3. J. M. Tenenbaum, 'Accummodation in computer vision', Ph.D. thesis, Stanford University. 1970
  4. Hanma, M. Masuda, H. Nabeyama and Y. Saito, 'Novel technologies for automatic focusing and white balancing of solid state color video camera', IEEE Trans. on Consumer Electronics, vol. CE-29, no. 3, pp. 376-381, 1983 https://doi.org/10.1109/TCE.1983.356324
  5. S. K. Nayar and Y. Nakagawa, 'Shape from focus'. IEEE Tans. Pattern Analysis and Machine Intelligence, vol. 16, pp, 824-831, 1994 https://doi.org/10.1109/34.308479
  6. A. Jarvis, 'Focus optimization criteria for computer image processing', Microscope, vol. 24, no. 2, pp, 163-180, 1976
  7. S. -H. Shin, J. -H. Park, K. -S. Kim, I. -J. Cho, and S. H. Kim, 'A study on a new auto-focusing algorithm for digital cameras', Trans. KIEE, vol. 50D, no. 9, pp. ?447-453, 2001
  8. R. C. Gonzalez, R. E. Wood, 'Digital Image Processing 2nd ed.', Prentice Hall, 2002
  9. Rafael C. Gonzalez, Richard E. Woods and Steven L. Eddins, 'Digital Image Processing Using MATLAB', PrenticeHall, 2004