{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,13]],"date-time":"2026-04-13T13:17:07Z","timestamp":1776086227046,"version":"3.50.1"},"reference-count":46,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2023,3,14]],"date-time":"2023-03-14T00:00:00Z","timestamp":1678752000000},"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":["U19A2086"],"award-info":[{"award-number":["U19A2086"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>X-ray grating interferometry (XGI) can provide multiple image modalities. It does so by utilizing three different contrast mechanisms\u2014attenuation, refraction (differential phase-shift), and scattering (dark-field)\u2014in a single dataset. Combining all three imaging modalities could create new opportunities for the characterization of material structure features that conventional attenuation-based methods are unable probe. In this study, we proposed an image fusion scheme based on the non-subsampled contourlet transform and spiking cortical model (NSCT-SCM) to combine the tri-contrast images retrieved from XGI. It incorporated three main steps: (i) image denoising based on Wiener filtering, (ii) the NSCT-SCM tri-contrast fusion algorithm, and (iii) image enhancement using contrast-limited adaptive histogram equalization, adaptive sharpening, and gamma correction. The tri-contrast images of the frog toes were used to validate the proposed approach. Moreover, the proposed method was compared with three other image fusion methods by several figures of merit. The experimental evaluation results highlighted the efficiency and robustness of the proposed scheme, with less noise, higher contrast, more information, and better details.<\/jats:p>","DOI":"10.3390\/s23063115","type":"journal-article","created":{"date-parts":[[2023,3,15]],"date-time":"2023-03-15T05:22:59Z","timestamp":1678857779000},"page":"3115","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Multimodal Image Fusion for X-ray Grating Interferometry"],"prefix":"10.3390","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0729-4526","authenticated-orcid":false,"given":"Haoran","family":"Liu","sequence":"first","affiliation":[{"name":"School of Data Science and Artificial Intelligence, Wenzhou University of Technology, Wenzhou 325000, China"},{"name":"State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu 610059, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7054-997X","authenticated-orcid":false,"given":"Mingzhe","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Data Science and Artificial Intelligence, Wenzhou University of Technology, Wenzhou 325000, China"},{"name":"State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu 610059, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xin","family":"Jiang","sequence":"additional","affiliation":[{"name":"School of Data Science and Artificial Intelligence, Wenzhou University of Technology, Wenzhou 325000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jinglei","family":"Luo","sequence":"additional","affiliation":[{"name":"The Engineering & Technical College of Chengdu University of Technology, Leshan 614000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuming","family":"Song","sequence":"additional","affiliation":[{"name":"The Engineering & Technical College of Chengdu University of Technology, Leshan 614000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xingyue","family":"Chu","sequence":"additional","affiliation":[{"name":"The Engineering & Technical College of Chengdu University of Technology, Leshan 614000, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guibin","family":"Zan","sequence":"additional","affiliation":[{"name":"Sigray, Inc., Concord, CA 94520, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,3,14]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"568","DOI":"10.1148\/radiol.211412","article-title":"Contrast-enhanced Mammography: A Systematic Review and Meta-Analysis of Diagnostic Performance","volume":"302","author":"Cozzi","year":"2022","journal-title":"Radiology"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1001\/jamaneurol.2021.4082","article-title":"Noncontrast Computed Tomography vs Computed Tomography Perfusion or Magnetic Resonance Imaging Selection in Late Presentation of Stroke With Large-Vessel Occlusion","volume":"79","author":"Nguyen","year":"2022","journal-title":"JAMA Neurol."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Martz, H.E., Logan, C.M., Schneberk, D.J., and Shull, P.J. 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