Pulmonary ventilation images from planning CT images using deep learning on locally-advanced NSCLC patients.
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| Title: | Pulmonary ventilation images from planning CT images using deep learning on locally-advanced NSCLC patients. |
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| Authors: | Katsuta Y; Department of Radiation Oncology, Tohoku University Graduate School of Medicine, Sendai, Japan., Hoshino T; Department of Radiation Oncology, Tohoku University Graduate School of Medicine, Sendai, Japan., Yamamoto T; Department of Radiation Oncology, Tohoku University Graduate School of Medicine, Sendai, Japan., Kadoya N; Department of Radiation Oncology, Tohoku University Graduate School of Medicine, Sendai, Japan., Tanaka S; Department of Radiation Oncology, Tohoku University Graduate School of Medicine, Sendai, Japan., Arai K; Department of Radiation Oncology, Tohoku University Graduate School of Medicine, Sendai, Japan., Umezawa R; Department of Radiation Oncology, Tohoku University Graduate School of Medicine, Sendai, Japan., Takahashi N; Department of Radiation Oncology, Tohoku University Graduate School of Medicine, Sendai, Japan., Jingu K; Department of Radiation Oncology, Tohoku University Graduate School of Medicine, Sendai, Japan. |
| Source: | Journal of applied clinical medical physics [J Appl Clin Med Phys] 2026 Sep; Vol. 27 (9), pp. e70777. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Wiley on behalf of American Association of Physicists in Medicine Country of Publication: United States NLM ID: 101089176 Publication Model: Print Cited Medium: Internet ISSN: 1526-9914 (Electronic) Linking ISSN: 15269914 NLM ISO Abbreviation: J Appl Clin Med Phys Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 1526-9914 |
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| DOI: | 10.1002/acm2.70777 |
