{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,27]],"date-time":"2026-02-27T07:25:53Z","timestamp":1772177153748,"version":"3.50.1"},"reference-count":30,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2026,2,25]],"date-time":"2026-02-25T00:00:00Z","timestamp":1771977600000},"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":"crossref","award":["12027808"],"award-info":[{"award-number":["12027808"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["12374436"],"award-info":[{"award-number":["12374436"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Jiangsu Qinglan Project"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J. Imaging"],"abstract":"<jats:p>Circular-Scan photoacoustic tomography (PAT) can provide high-resolution images of optical absorption, but its analytical reconstructions, such as delay-and-sum (DAS), are highly sensitive to scanning radius (SR) inaccuracies, which cause severe geometric distortions and artifacts. In this work, we propose a deep learning framework, termed smooth deconvolution ResNet (SD-ResNet), to correct DAS reconstruction degradation induced by SR errors. SD-ResNet uses an ImageNet-pretrained ResNet-50 encoder and a lightweight deconvolutional decoder with additional smoothing convolutions to suppress checkerboard artifacts and restore fine structural details. A paired training dataset is generated using k-Wave simulations driven by human thoracic computed tomography (CT) slices: for each phantom, radiofrequency data are simulated once, and DAS images reconstructed with the true SR serve as ground truth, whereas images reconstructed with biased SR values serve as inputs. This design provides structurally diverse training samples and enhances generalization. In silico experiments show that SD-ResNet effectively recovers image quality across a range of SR deviations. Phantom experiments with polyethylene microspheres further confirm that the proposed method can substantially reduce artifacts and recover correct source shapes under practical SR mismatches, offering a robust tool for SR-error-resilient PAT imaging.<\/jats:p>","DOI":"10.3390\/jimaging12030097","type":"journal-article","created":{"date-parts":[[2026,2,25]],"date-time":"2026-02-25T09:42:22Z","timestamp":1772012542000},"page":"97","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A Deep Learning-Based Correction for Scanning Radius Errors in Circular-Scan Photoacoustic Tomography"],"prefix":"10.3390","volume":"12","author":[{"given":"Jie","family":"Yin","sequence":"first","affiliation":[{"name":"School of Electrical and Control Engineering, Nanjing Polytechnic Institute, Nanjing 210048, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yingjie","family":"Feng","sequence":"additional","affiliation":[{"name":"MOE Key Laboratory of Modern Acoustics, Department of Physics, Collaborative Innovation Center of Advanced Microstructures, Nanjing University, Nanjing 210023, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Junjun","family":"He","sequence":"additional","affiliation":[{"name":"School of Intelligent Manufacturing, Nanjing Polytechnic Institute, Nanjing 210048, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Min","family":"Xie","sequence":"additional","affiliation":[{"name":"School of Electrical and Control Engineering, Nanjing Polytechnic Institute, Nanjing 210048, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8052-6827","authenticated-orcid":false,"given":"Chao","family":"Tao","sequence":"additional","affiliation":[{"name":"MOE Key Laboratory of Modern Acoustics, Department of Physics, Collaborative Innovation Center of Advanced Microstructures, Nanjing University, Nanjing 210023, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2026,2,25]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"100320","DOI":"10.1016\/j.pacs.2021.100320","article-title":"Characterization of multi biomarkers for bone health assessment based on photoacoustic physicochemical analysis method","volume":"25","author":"Feng","year":"2022","journal-title":"Photoacoustics"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1557","DOI":"10.1364\/BOE.557086","article-title":"Quantitative assessment of thrombosis induced blood oxygenation change in deep tissues based on photoacoustic tomography: An ex vivo study","volume":"16","author":"Feng","year":"2025","journal-title":"Biomed. 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