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Besides, the effectiveness of the DLIR methods was also rarely validated on the downstream tasks. In the study, a multi\u2010scale complexity\u2010aware registration network (MSCAReg\u2010Net) was proposed by devising a complexity\u2010aware technique to facilitate DLIR under a single\u2010resolution framework. Specifically, the complexity\u2010aware technique devised a multi\u2010scale complexity\u2010aware module (MSCA\u2010Module) to perceive deformations with distinct complexities, and employed a feature calibration module (FC\u2010Module) and a feature aggregation module (FA\u2010Module) to facilitate the MSCA\u2010Module by generating more distinguishable deformation features. Experimental results demonstrated the superiority of the proposed MSCAReg\u2010Net over the existing methods in terms of registration accuracy. Besides, other than the indices of Dice similarity coefficient (DSC) and percentage of voxels with non\u2010positive Jacobian determinant (), a comprehensive evaluation of the registration performance was performed by applying this method on a downstream task of multi\u2010atlas hippocampus segmentation (MAHS). Experimental results demonstrated that this method contributed to a better hippocampus segmentation over other DLIR methods, and a comparable segmentation performance with the leading SyN method. The comprehensive assessment including DSC, , and the downstream application on MAHS demonstrated the advances of this method.<\/jats:p>","DOI":"10.1049\/ipr2.12988","type":"journal-article","created":{"date-parts":[[2023,11,22]],"date-time":"2023-11-22T13:23:33Z","timestamp":1700659413000},"page":"839-855","update-policy":"http:\/\/dx.doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["MSCAReg\u2010Net: Multi\u2010scale complexity\u2010aware convolutional neural network for deformable image registration"],"prefix":"10.1049","volume":"18","author":[{"ORCID":"http:\/\/orcid.org\/0000-0002-1381-2791","authenticated-orcid":false,"given":"Hu","family":"Yu","sequence":"first","affiliation":[{"name":"School of Computer and Control Engineering Yantai University Yantai Shandong Province China"}]},{"ORCID":"http:\/\/orcid.org\/0000-0002-7853-8033","authenticated-orcid":false,"given":"Qiang","family":"Zheng","sequence":"additional","affiliation":[{"name":"School of Computer and Control Engineering Yantai University Yantai Shandong Province China"}]},{"given":"Fang","family":"Hu","sequence":"additional","affiliation":[{"name":"Key Laboratory of Medical Imaging and Artificial Intelligence of Hunan Province Xiangnan University Chenzhou Hunan Province China"}]},{"ORCID":"http:\/\/orcid.org\/0000-0001-5084-7689","authenticated-orcid":false,"given":"Chaoqing","family":"Ma","sequence":"additional","affiliation":[{"name":"School of Computer and Control Engineering Yantai University Yantai Shandong Province China"},{"name":"Key Laboratory of Medical Imaging and Artificial Intelligence of Hunan Province Xiangnan University Chenzhou Hunan Province China"}]},{"given":"Shuo","family":"Wang","sequence":"additional","affiliation":[{"name":"Yantai University Trier College of Sustainable Technology Yantai University Yantai Shandong Province China"},{"name":"Trier University of Applied Sciences Trier Germany"}]},{"ORCID":"http:\/\/orcid.org\/0000-0002-9721-6590","authenticated-orcid":false,"given":"Shuai","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Radiology Binzhou Medical University Hospital Binzhou Shandong Province China"}]}],"member":"265","published-online":{"date-parts":[[2023,11,21]]},"reference":[{"key":"e_1_2_11_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2013.2265603"},{"key":"e_1_2_11_3_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2009.02.018"},{"key":"e_1_2_11_4_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijrobp.2008.04.013"},{"key":"e_1_2_11_5_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2017.2668842"},{"key":"e_1_2_11_6_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2007.06.004"},{"key":"e_1_2_11_7_1","first-page":"266","volume-title":"Medical Image Computing and Computer\u2010Assisted Intervention (MICCAI 2017)","author":"Roh\u00e9 M.\u2010M.","year":"2017"},{"key":"e_1_2_11_8_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2019.2897538"},{"key":"e_1_2_11_9_1","doi-asserted-by":"crossref","unstructured":"Balakrishnan G. 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