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Herein, we developed a strategic platform that combines a novel ultrasensitive magnetic resonance (MR) contrast agent with deep learning to significantly enhance the tumor\u2010to\u2010normal ratio (TNR). We designed ultrasmall iron oxide nanoparticles (USIO NPs) conjugated with trastuzumab (Tmab) for targeted MR imaging of HER2\u2010positive breast cancer. The USIO@Tmab nanoprobe demonstrated excellent HER2 specificity and pH\u2010responsive activation. The relaxivity of the nanoprobe shifted from a low T\n                    <jats:sub>1<\/jats:sub>\n                    \u2010weighted intensity (r\n                    <jats:sub>1<\/jats:sub>\n                    = 1.43\u00a0mM\n                    <jats:sup>\u2212<\/jats:sup>\n                    <jats:sup>1<\/jats:sup>\n                    s\n                    <jats:sup>\u2212<\/jats:sup>\n                    <jats:sup>1<\/jats:sup>\n                    ) under physiological conditions to an enhanced value (r\n                    <jats:sub>1<\/jats:sub>\n                    = 4.07\u00a0mM\n                    <jats:sup>\u2212<\/jats:sup>\n                    <jats:sup>1<\/jats:sup>\n                    s\n                    <jats:sup>\u2212<\/jats:sup>\n                    <jats:sup>1<\/jats:sup>\n                    ) in the acidic tumor microenvironment due to the detachment of Tmab protein. Additionally, we employed the 3D nnU\u2010Net deep learning framework as a post\u2010processing visualization aid to enhance tumor boundary detection via image fusion, rather than to amplify the underlying MRI signal. This approach yielded high segmentation accuracy, with an Intersection\u2010over\u2010Union (IoU) of 0.88 and a Dice coefficient of 0.93. This strategy provided an additional 2.59\u2010fold increase in TNR and enabled the reconstruction of three\u2010dimensional (3D) tumor models, offering clinicians an intuitive visualization of tumor structure for precise diagnosis and surgical guidance.\n                  <\/jats:p>","DOI":"10.1002\/advs.77355","type":"journal-article","created":{"date-parts":[[2026,8,24]],"date-time":"2026-08-24T15:44:00Z","timestamp":1787586240000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["AI\u2010Assisted Tumor Boundary Delineation via Targeted Ultrasmall Iron Oxide Nanoprobe for High\u2010Contrast HER2\u2010Positive Tumor Imaging"],"prefix":"10.1002","author":[{"given":"Jiaying","family":"Zheng","sequence":"first","affiliation":[{"name":"Department of Biomedical Engineering College of Engineering Shantou University  Shantou People's Republic of 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