1. EDGE-BASED PEAK POSITION SEARCH ALGORITHM FOR PET DETECTORS Presenter: Kun Di Advisor: Dr. Chung-E Wang Dr. Ted Krovetz Department of Computer Science California State University, Sacramento November 22, 2010

2. 2016-6-5Department of Computer Science2 Agenda Motivation Background Methodology –Edge Detection –Gradient Information Analysis –Peaks Detection Results Summary and Future Work

3. 2016-6-5Department of Computer Science3 Motivation The positron emission tomography (PET) scanner –Gamma Rays –Array of Scintillation Crystals –Photomultiplier Tubes (PMTs), Avalanche Photo Diodes (APDs) –Coincidence processing Calibration: –Position Profile (Peak Positions) Automatic peak detection is desirable because manually selecting each peak is time-consuming, especially for large crystal arrays (e.g. 20x20). Pictures (except the right-bottom one) are from http://en.wikipedia.org/wiki/Positron_emission_tomography

4. 2016-6-5Department of Computer Science4 Background Previous Effort –Neural network based algorithm[2] –Non-rigid registration to a Fourier-based template [3] –PCA-based algorithm [4] –Morphological-based algorithm [5][6] Main obstacles –Distortion –Peak fusion.

5. 2016-6-5Department of Computer Science5 Edge Detection Canny Edge - Continuous Edge –Gaussian Smooth –Gradient (magnitude) –Non-Maximum Suppression –High and Low Threshold –Trace Edge Gradient

6. 2016-6-5Department of Computer Science6 Gradient Information –Magnitude –Direction Special Points –Top, Bottom, Left, right –Break Points Horizontal, Vertical Gradient Information Analysis

7. 2016-6-5Department of Computer Science7 Peaks Detection Algorithm Raw image input; Generate Gaussian smoothed image; Edge detection according to gradient magnitude; Get interested region according to the edges and gradient directions of each point on each edge; Identify peaks according to the number of crystals and hit-sum of each interested region; Manually correct the peaks if necessary; Save the peaks;

8. 2016-6-5Department of Computer Science8 Tools Implementation Automatic peaks detection Adjustment of settings to achieve better result Manual correction Sorting peaks Saving peak positions to text file for writing back to PET system

9. 2016-6-5Department of Computer Science9 Results

10. 2016-6-5Department of Computer Science10 Summary and Future Work The tool works pretty good. Distortion problem has been solved. The result depends upon the quality of edge detection. –Low quality of edge detection may cause peak missing in case of highly fused peaks. In order to improve the performance, the whole image pattern should be considered. Therefore, a supplemental algorithm is going to be designed

11. 2016-6-5Department of Computer Science11 Reference [1] http://en.wikipedia.org/wiki/Positron_emission_tomographyhttp://en.wikipedia.org/wiki/Positron_emission_tomography [2] D. Hu, B. Atkins, M. Lenox, B. Castleberry, and S. Siegel, “A neural network based algorithm for building crystal look-up table of PET block detector,” in Proc. IEEE Nuclear Science Symp. Conf. Rec., Nov. 2006, vol. 4, pp. 2458–2461. [3] A. Chaudhari, A. Joshi, S. Bowen, R. Leahy, S. Cherry, and R. Badawi, “Crystal identification in positron emission tomography using nonrigid registration to a Fourier-based template,” Phys. Med. Biol., vol. 53, no. 18, pp. 5011–5027, Sep. 2008. [4] J. Breuer and K. Wienhard, "PCA-Based Algorithm for Generation of Crystal Lookup Tables for PET Block Detecto," IEEE TRANSACTIONS ON NUCLEAR SCIENCE, VOL. 56, NO. 3, JUNE 2009, pp. 602-607. [5] Albert Mao, Student Volunteer, Imaging Physics Laboratory, Nuclear Medicine Department, Clinical Center, National Institutes of Health, "Positron Emission Tomograph Detector Module Calibration Through Morphological Algorithms and Interactive Correction," [6] Z. Hu, C. Kao, W. Liu, Y. Dong, Z. Zhang, Q. Xie, C. Chen, "Semi-Automatic Position Calibration for a Dual-Head Small Animal PET Scanner," 2007 IEEE Nuclear Science Symposium Conference Record, pp. 1618-1621. [7] P. Després, W. C. Barber, T. Funk, M. McClish, K. S. Shah, and B. H. Hasegawa, "Modeling and Correction of Spatial Distortion in Position-Sensitive Avalanche Photodiodes," IEEE TRANSACTIONS ON NUCLEAR SCIENCE, VOL. 54, NO. 1, FEBRUARY 2007, pp. 23-29. [8] J. Zhang, P. Olcott, and C. Levin, “A new positioning algorithm for position-sensitive avalanche photodiodes,” IEEE Trans. Nucl. Sci., vol. 54, no. 3, pp. 433–437, Jun. 2007. [9] J. Canny, "A computational approach to edge detection", IEEE Trans. Pattern Analysis and Machine Intelligence, vol 8, pages 679-714, 1986.