An Application of Simulated Annealing in Compensation of Nonlinearity of Scanners
Source abstract
Abstract
Galvo scanners are popular devices for fast transversal scanning. A triangular signal is usually employed to drive galvo scanners at scanning rates close to the inverse of their response time where scanning deflection becomes a nonlinear function of applied voltage. To address this, the triangular signal is synthesized from several short ramps with different slopes. An optimization algorithm similar to a simulated annealing algorithm is used for finding the optimal signal shape to drive the galvo scanners. As a result, a significant reduction in the nonlinearity of the galvo scanning is obtained.
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Research context
OpenAlex topics: Photoacoustic and Ultrasonic Imaging · Optical measurement and interference techniques · Advanced Measurement and Metrology Techniques
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Biomedical Engineering, Wayne State University, Detroit, MI 48201, USA
School of Physical Science, University of Kent, Canterbury, Kent CT2 7NZ, UK
Department of Dermatology, Wayne State University School of Medicine, Detroit, MI 48201, USA
Barbara Ann Karmanos Cancer Institute, Detroit, MI 48201, USA
References (43)
Show source-provided references
1. Podoleanu, A.G. (2014). Optical Coherence Tomography, The British Journal of Radiology.
2. Shanmugasundaram, A., and Palani, R. (1979). Electrical Machine Design Data Book, New Age International.
3. OCT skin image enhancement through attenuation compensation10.1364/AO.51.004927 ↗
4. Mnerie, C., Preitl, S., and Duma, V.-F. (2013, January 13). Mathematical model of a galvanometer-based scanner: Simulations and experiments. Proceedings of the SPIE Optical Metrology 2013, Munich, Germany.10.1117/12.2020462 ↗
5. Hariri, A., Fatima, A., and Avanaki, M.R.N. (2018). A Novel Library for the Correction of a Galvo-Scanner’s Non-Linearity at High Frequencies. Res. J. Opt. Photonics, 2, Available online: https://www.scitechnol.com/peer-review/a-novel-library-for-the-correction-of-a-galvoscanners-nonlinearity-at-high-frequencies-Lrx1.php?article_id=8033.
6. Beam deflection and scanning by two-mirror and two-axis systems of different architectures: A unified approach10.1364/AO.47.005976 ↗
7. Third-order theory of the Risley-prism-based beam steering system10.1364/AO.50.000679 ↗
8. Advanced galvanometer-based optical scanner design10.1108/02602280310481968 ↗
9. Optical design of a variable view imaging system with the combination of a telecentric scanner and double wedge prisms10.1364/AO.49.000239 ↗
10. En-face coherence imaging using galvanometer scanner modulation10.1364/OL.23.000147 ↗
11. Optimal scanning function of a galvanometer scanner for an increased duty cycle10.1117/1.3497570 ↗
12. Aylward, R.P. (1999, January 2). Advances and technologies of galvanometer-based optical scanners. Proceedings of the SPIE’s International Symposium on Optical Science, Engineering, and Instrumentation, Denver, CO, USA.10.1117/12.351641 ↗
13. Gadhok, J.S. (1999, January 2). Achieving high-duty cycle sawtooth scanning with galvanometric scanners. Proceedings of the SPIE 3787, Optical Scanning: Design and Application, Denver, CO, USA.10.1117/12.351643 ↗
14. Galvanometric and resonant scanners
15. Investigation of computer-based skin cancer detection using optical coherence tomography10.1080/09500340902990007 ↗
16. Investigation of basal cell carcinoma using dynamic focus optical coherence tomography10.1364/AO.52.002116 ↗
17. Quantitative evaluation of scattering in optical coherence tomography skin images using the extended Huygens–Fresnel theorem10.1364/AO.52.001574 ↗
18. Image quality improvement in optical coherence tomography using Lucy–Richardson deconvolution algorithm10.1364/AO.52.005663 ↗
19. Experimental investigations of the scanning functions of galvanometer-based scanners with applications in OCT10.1364/AO.50.005735 ↗
20. Simulated annealing algorithms: An overview10.1109/101.17235 ↗
21. Nasiri-Avanaki, M.-R., Hojjatoleslami, S.A., Paun, M., Tuohy, S., Meadway, A., Dobre, G., and Podoleanu, A.G. (2009, January 28). Optical coherence tomography system optimization using simulated annealing algorithm. Proceedings of the 11th WSEAS international conference on Mathematical methods and computational techniques in electrical engineering, Athens, Greece.
22. Avanaki, M.R., Hojjatoleslami, S., Meadway, A., Dobre, G., and Podoleanu, A.G. (2010, January 27–28). Adaptive optics with simulated annealing in confocal microscopy. Proceedings of the Iranian Conference, Mathematical Methods and Applied Computing, Isfahan, Iran.
23. High-resolution photoacoustic tomography of resting-state functional connectivity in the mouse brain10.1073/pnas.1311868111 ↗
24. Speckle reduction using an artificial neural network algorithm10.1364/AO.52.005050 ↗
25. Simulated annealing optimization in wavefront shaping controlled transmission10.1364/AO.57.006233 ↗
26. Fayyaz, Z., Salimi, F., Mohammadian, N., Fatima, A., Tabar, M.R.R., and Avanaki, M.R. (2018, January 22). Wavefront shaping using simulated annealing algorithm for focusing light through turbid media. Proceedings of the Photons Plus Ultrasound: Imaging and Sensing 2018, San Francisco, CA, USA.
27. Trifanov, I., Neagu, L., Bradu, A., Ribeiro, A.L., and Podoleanu, A.G. (2011, January 11). Characterization of a fibre optic swept laser source at 1 μm for optical coherence tomography imaging systems. Proceedings of the Optical Coherence Tomography and Coherence Domain Optical Methods in Biomedicine XV, San Francisco, CA, USA.10.1117/12.874771 ↗
28. Fast algorithm for blind optimization of optical systems. Statistics and methodology
29. Avanaki, M.R., Hojjatoleslami, S., Sarmadi, H., Ebrahimpour, R., and Podoleanu, A.G. (2010, January 11–13). Genetic algorithm for optimization of optical systems. Proceedings of the 2010 18th Iranian Conference on Electrical Engineering, Isfahan, Iran.10.1109/IRANIANCEE.2010.5507081 ↗
30. Avanaki, M.R., Khoshki, R.M., Hojjatoleslami, S., and Podoleanu, A.G. (2012, January 30). Sensor-less aberration correction in optical imaging systems using blind optimization. Proceedings of the Third Asia Pacific Optical Sensors Conference, Sydney, Australia.10.1117/12.914228 ↗
31. Avanaki, M.R., Podoleanu, A., Sarmadi, H., Meadway, A., and Hojjatoleslami, S. (2010, January 27–28). Blind optimization for aberration correction in confocal imaging system. Proceedings of the 2010 6th Iranian Conference on Machine Vision and Image Processing, Isfahan, Iran.10.1109/IranianMVIP.2010.6401476 ↗
32. Mahmoodkalayeh, S., Lu, X., Ansari, M.A., Li, H., and Nasiriavanaki, M. (2018, January 26). Optimization of light illumination for photoacoustic computed tomography of human infant brain. Proceedings of the Photons Plus Ultrasound: Imaging and Sensing 2018, San Francisco, CA, USA.10.1117/12.2291592 ↗
33. Nasiri Avanaki, M.R. (2011). Image Enhancement Algorithms and System Optimization for Optical Coherence Tomography. [Ph.D. Thesis, University of Kent].
34. Development and Optimization of a Fluorescent Imaging System to Detect Amyloid-β Proteins: Phantom Study10.1177/1179597218781081 ↗
35. Optimization by simulated annealing: Quantitative studies10.1007/BF01009452 ↗
36. Wavefront aberration correction in single mode fibre systems
37. An efficient implementation of parallel simulated annealing algorithm in GPUs10.1007/s10898-012-9979-z ↗
38. An overview of methods to mitigate artifacts in optical coherence tomography imaging of the skin10.1111/srt.12423 ↗
39. Universal in vivo textural model for human skin based on optical coherence tomograms10.1038/s41598-017-17398-8 ↗
40. Optical coherence tomography technology and quality improvement methods for optical coherence tomography images of skin: A short review10.1177/1179597217713475 ↗
41. Development of low-cost photoacoustic imaging systems using very low-energy pulsed laser diodes10.1117/1.JBO.22.7.075001 ↗
42. Turani, Z., Fatemizadeh, E., Blumetti, T., Daveluy, S., Moraes, A.F., Chen, W., Mehregan, D., Andersen, P.E., and Nasiriavanaki, M. (2019). Optical Radiomic Signatures Derived from Optical Coherence Tomography Images to Improve Identification of Melanoma. Cancer Res.10.1117/12.2526624 ↗
43. Noninvasive photoacoustic computed tomography of mouse brain metabolism in vivo10.1016/j.neuroimage.2012.08.054 ↗