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Opt."],"published-print":{"date-parts":[[2026,10,1]]},"abstract":"<jats:p>Accurate two-dimensional image reconstruction in compact resonant electromagnetic microelectromechanical system (MEMS) scanning confocal microscopy depends on segmenting a continuously acquired one-dimensional detector stream into image lines and estimating the scan parameters. Mismatch between nominal drive timing and actual fast-axis motion can cause line dislocation and geometric distortion, whereas additional sensing hardware, external synchronization, or image-domain estimation may increase instrument size and implementation complexity. We present a method that obtains the required line-data information directly from the fast-axis back electromotive force (back-EMF). Under constant-current H-bridge drive, the fast-axis coil-terminal voltage was acquired by pseudo-differential sampling and processed to extract the back-EMF waveform. From the extracted waveform, a field-programmable gate array (FPGA) generated center-aligned line data, the line-scan period, and the optical scan amplitude in real time. The host computer used these outputs to perform scan-parameter-based two-dimensional image reconstruction. For a standard square-grid target, the line-offset standard deviation decreased from 4.397 to 0.618 pixels, a reduction of approximately 86%. The mean grid-cell aspect ratio improved from 1.1282 to 1.0074, closer to the ideal value of unity, while its mean absolute error (MAE) relative to unity decreased from 0.1282 to 0.0082, a reduction of approximately 93.6%. Imaging of a plant leaf showed improved interline continuity and local morphological consistency in complex cellular structures. The current system displayed 1000\u00d71000-pixel images in real time at 30\u00a0fps, demonstrating the feasibility of this route for acquiring back-EMF-derived line-data information and applying it to image correction in a compact high-frame-rate imaging configuration.<\/jats:p>","DOI":"10.1364\/ao.611852","type":"journal-article","created":{"date-parts":[[2026,9,9]],"date-time":"2026-09-09T14:09:11Z","timestamp":1788962951000},"page":"9928","update-policy":"https:\/\/doi.org\/10.1364\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Dislocation and distortion correction using back-EMF-derived line-data information in compact resonant electromagnetic MEMS scanning confocal microscopy"],"prefix":"10.1364","volume":"65","author":[{"ORCID":"https:\/\/orcid.org\/0009-0002-6810-6453","authenticated-orcid":true,"given":"Meng","family":"Xue","sequence":"first","affiliation":[{"id":[{"id":"https:\/\/ror.org\/00ay9v204","id-type":"ROR","asserted-by":"publisher"}]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhaoqing","family":"Yang","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/00ay9v204","id-type":"ROR","asserted-by":"publisher"}]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wei","family":"Fu","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/00ay9v204","id-type":"ROR","asserted-by":"publisher"}]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2600-5507","authenticated-orcid":true,"given":"Hanming","family":"Guo","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/00ay9v204","id-type":"ROR","asserted-by":"publisher"}]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"285","published-online":{"date-parts":[[2026,9,29]]},"reference":[{"key":"ao-65-28-9928-R1","doi-asserted-by":"publisher","first-page":"697","DOI":"10.1016\/j.abd.2021.10.010","type":"journal-article","volume":"97","author":"Braghiroli","year":"2022","journal-title":"An. 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All rights, including for text and data mining (TDM), Artificial Intelligence (AI) training, and similar technologies, are reserved.","name":"copyright","label":"Copyright"}]}}