{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,30]],"date-time":"2026-04-30T08:33:45Z","timestamp":1777538025038,"version":"3.51.4"},"reference-count":16,"publisher":"MDPI AG","issue":"21","license":[{"start":{"date-parts":[[2021,10,26]],"date-time":"2021-10-26T00:00:00Z","timestamp":1635206400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61771230"],"award-info":[{"award-number":["61771230"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Shandong Provincial Jinan Science and Technology Project","award":["201816082"],"award-info":[{"award-number":["201816082"]}]},{"name":"Shandong Provincial Jinan Science and Technology Project","award":["201817001"],"award-info":[{"award-number":["201817001"]}]},{"name":"Youth Program of Shandong Provincial Natural Science Foundation","award":["ZR2020QF011"],"award-info":[{"award-number":["ZR2020QF011"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Patch-based medical image registration has been well explored in recent decades. However, the patch fusion process can generate grid-like artifacts along the edge of patches for the following two reasons: firstly, in order to ensure the same size of input and output, zero-padding is used, which causes uncertainty in the edges of the output feature map during the feature extraction process; secondly, the sliding window extraction patch with different strides will result in different degrees of grid-like artifacts. In this paper, we propose an exponential-distance-weighted (EDW) method to remove grid-like artifacts. To consider the uncertainty of predictions near patch edges, we used an exponential function to convert the distance from the point in the overlapping regions to the center point of the patch into a weighting coefficient. This gave lower weights to areas near the patch edges, to decrease the uncertainty predictions. Finally, the dense displacement field was obtained by this EDW weighting method. We used the OASIS-3 dataset to evaluate the performance of our method. The experimental results show that the proposed EDW patch fusion method removed grid-like artifacts and improved the dice similarity coefficient superior to those of several state-of-the-art methods. The proposed fusion method can be used together with any patch-based registration model.<\/jats:p>","DOI":"10.3390\/s21217112","type":"journal-article","created":{"date-parts":[[2021,10,26]],"date-time":"2021-10-26T23:54:33Z","timestamp":1635292473000},"page":"7112","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Exponential-Distance Weights for Reducing Grid-like Artifacts in Patch-Based Medical Image Registration"],"prefix":"10.3390","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5988-4021","authenticated-orcid":false,"given":"Liang","family":"Wu","sequence":"first","affiliation":[{"name":"School of Control Science and Engineering, Shandong University, Jinan 250061, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shunbo","family":"Hu","sequence":"additional","affiliation":[{"name":"School of Information Science and Engineering, Linyi University, Linyi 276005, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Changchun","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Control Science and Engineering, Shandong University, Jinan 250061, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2021,10,26]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.media.2018.07.002","article-title":"Weakly-supervised convolutional neural networks for multimodal image registration","volume":"49","author":"Hu","year":"2018","journal-title":"Med. 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