{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T08:05:36Z","timestamp":1790841936870,"version":"4.1.0"},"reference-count":34,"publisher":"Oxford University Press (OUP)","issue":"5","license":[{"start":{"date-parts":[[2026,9,8]],"date-time":"2026-09-08T00:00:00Z","timestamp":1788825600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/pages\/standard-publication-reuse-rights"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62271032"],"award-info":[{"award-number":["62271032"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62171012"],"award-info":[{"award-number":["62171012"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61771033"],"award-info":[{"award-number":["61771033"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,9,8]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Based on compressed sensing, undersampling is a low cost and efficient way to speed up the process of atomic force microscopy (AFM) imaging. The under-sampled information obtained is important in producing high-quality reconstructed images. Different samples and dynamic measurement show different characteristic of topography, which makes it impossible to acquire acceptable AFM image with same under-sampled scanning pattern. This work aims to propose an unsampling path planning method for effective under-sampled image acquisition. The preprocess is realized by object detection and k-means method. The path planning method combines Self-Organizing Map, Ant Colony Optimization and B-Spline. Through parallel calculation and cluster analysis, large-scale traveling salesman problem (L-TSP) is divided into several small-scale traveling salesman problems. After undersampling, the reconstruction process is realized by Bayesian compressed sensing. Several path planning algorithms are performed for comparison. An experimental example of L-TSP in AFM is carried out. Experimental and application results demonstrate that the proposed method can optimize scanning path of tens of thousands under-sampled points within minute. The proposed method succeeds to save time and guarantee the quality of AFM imaging.<\/jats:p>","DOI":"10.1093\/mam\/ozag094","type":"journal-article","created":{"date-parts":[[2026,8,20]],"date-time":"2026-08-20T11:52:09Z","timestamp":1787226729000},"source":"Crossref","is-referenced-by-count":0,"title":["Accelerating Atomic Force Microscopy Imaging based on an Optimized Path Planning Method"],"prefix":"10.1093","volume":"32","author":[{"given":"Peng","family":"Cheng","sequence":"first","affiliation":[{"name":"School of Physics, Beihang University , Xueyuan Road No. 37, Haidian District, Beijing 100191 ,","place":["China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2982-3054","authenticated-orcid":false,"given":"Yingzi","family":"Li","sequence":"additional","affiliation":[{"name":"School of Physics, Beihang University , Xueyuan Road No. 37, Haidian District, Beijing 100191 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