Parametric regression model approach for CT-based prediction of stopping power ratio for a Hounsfield look-up table.
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| Title: | Parametric regression model approach for CT-based prediction of stopping power ratio for a Hounsfield look-up table. |
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| Authors: | Yagi M; Division of Radiation Oncology, National Cancer Centre Singapore, Singapore.; Department of Radiation Oncology, The University of Osaka Graduate School of Medicine, Osaka, Japan., Calvin Koh WY; Division of Radiation Oncology, National Cancer Centre Singapore, Singapore., Lew KS; Division of Radiation Oncology, National Cancer Centre Singapore, Singapore., Chua CGA; Division of Radiation Oncology, National Cancer Centre Singapore, Singapore., Yeap PL; Division of Radiation Oncology, National Cancer Centre Singapore, Singapore.; Department of Oncology, University of Cambridge, Cambridge, United Kingdom., Wibawa A; Division of Radiation Oncology, National Cancer Centre Singapore, Singapore., Master Z; Division of Radiation Oncology, National Cancer Centre Singapore, Singapore., Lee JCL; Division of Radiation Oncology, National Cancer Centre Singapore, Singapore.; Division of Physics and Applied Physics, School of Physical and Mathematical Science, Nanyang Technological University, Singapore, Singapore., Park SY; Division of Radiation Oncology, National Cancer Centre Singapore, Singapore.; Oncology Academic Clinical Programme, Duke-NUS Medical School, Singapore, Singapore., Tan HQ; Division of Radiation Oncology, National Cancer Centre Singapore, Singapore.; Division of Physics and Applied Physics, School of Physical and Mathematical Science, Nanyang Technological University, Singapore, Singapore.; Oncology Academic Clinical Programme, Duke-NUS Medical School, Singapore, Singapore. |
| Source: | Biomedical physics & engineering express [Biomed Phys Eng Express] 2026 Jun 18; Vol. 12 (3). Date of Electronic Publication: 2026 Jun 18. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: IOP Publishing Ltd Country of Publication: England NLM ID: 101675002 Publication Model: Electronic Cited Medium: Internet ISSN: 2057-1976 (Electronic) Linking ISSN: 20571976 NLM ISO Abbreviation: Biomed Phys Eng Express Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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