Generative Inpainting-Based Anomaly Detection for CT Liver Tumor Detection.
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| Title: | Generative Inpainting-Based Anomaly Detection for CT Liver Tumor Detection. |
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| Authors: | Shi Y; Biomedical Imaging Center, Department of Biomedical Engineering, School of Engineering, Rensselaer Polytechnic Institute, Troy, NY 12180 USA., Niu C; Biomedical Imaging Center, Department of Biomedical Engineering, School of Engineering, Rensselaer Polytechnic Institute, Troy, NY 12180 USA., Simpson AL; Biomedical Computing and Informatics, Queen's University, ON K7L 3N6, Canada., De Man B; GE HealthCare Technology & Innovation Center, Niskayuna, NY 12309 USA., Do R; Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY 10065 USA., Wang G; Biomedical Imaging Center, Department of Biomedical Engineering, School of Engineering, Rensselaer Polytechnic Institute, Troy, NY 12180 USA. |
| Source: | IEEE transactions on radiation and plasma medical sciences [IEEE Trans Radiat Plasma Med Sci] 2025 Nov; Vol. 9 (8), pp. 1051-1061. Date of Electronic Publication: 2025 Mar 17. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: IEEE Country of Publication: United States NLM ID: 101705223 Publication Model: Print-Electronic Cited Medium: Print ISSN: 2469-7311 (Print) Linking ISSN: 24697303 NLM ISO Abbreviation: IEEE Trans Radiat Plasma Med Sci Subsets: PubMed not MEDLINE |
| Database: | MEDLINE Ultimate |
| ISSN: | 2469-7311 |
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| DOI: | 10.1109/trpms.2025.3551946 |
