Combining radiomics and deep learning features of intra-tumoral and peri-tumoral regions for the classification of breast cancer lung metastasis and primary lung cancer with low-dose CT.
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| Title: | Combining radiomics and deep learning features of intra-tumoral and peri-tumoral regions for the classification of breast cancer lung metastasis and primary lung cancer with low-dose CT. |
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| Authors: | Li L; School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230026, China.; Department of Medical Imaging, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, 215163, China., Zhou X; Department of PET/CT Center, Harbin Medical University Cancer Hospital, Harbin, 150081, China.; Department of Radiology, Second Affiliated Hospital of Harbin Medical University, Harbin, 150086, China., Cui W; School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230026, China.; Department of Medical Imaging, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, 215163, China., Li Y; Department of PET/CT Center, Harbin Medical University Cancer Hospital, Harbin, 150081, China., Liu T; Department of Pathology, Second Affiliated Hospital of Harbin Medical University, Harbin, 150086, China., Yuan G; School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230026, China. yuangang@sibet.ac.cn.; Department of Medical Imaging, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, 215163, China. yuangang@sibet.ac.cn., Peng Y; Department of Medical Imaging, International Exemplary Cooperation Base of Precision Imaging for Diagnosis and Treatment, Guizhou Provincial People's Hospital, Guizhou, 550002, China. pys@mail.ustc.edu.cn., Zheng J; School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230026, China.; Department of Medical Imaging, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, 215163, China. |
| Source: | Journal of cancer research and clinical oncology [J Cancer Res Clin Oncol] 2023 Nov; Vol. 149 (17), pp. 15469-15478. Date of Electronic Publication: 2023 Aug 29. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Springer-Verlag Country of Publication: Germany NLM ID: 7902060 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1432-1335 (Electronic) Linking ISSN: 01715216 NLM ISO Abbreviation: J Cancer Res Clin Oncol Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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| Header | DbId: mdl DbLabel: MEDLINE Ultimate An: 37642722 AccessLevel: 2 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Combining radiomics and deep learning features of intra-tumoral and peri-tumoral regions for the classification of breast cancer lung metastasis and primary lung cancer with low-dose CT. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AU" term="%22Li+L%22">Li L</searchLink>; School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230026, China.; Department of Medical Imaging, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, 215163, China.<br /><searchLink fieldCode="AU" term="%22Zhou+X%22">Zhou X</searchLink>; Department of PET/CT Center, Harbin Medical University Cancer Hospital, Harbin, 150081, China.; Department of Radiology, Second Affiliated Hospital of Harbin Medical University, Harbin, 150086, China.<br /><searchLink fieldCode="AU" term="%22Cui+W%22">Cui W</searchLink>; School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230026, China.; Department of Medical Imaging, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, 215163, China.<br /><searchLink fieldCode="AU" term="%22Li+Y%22">Li Y</searchLink>; Department of PET/CT Center, Harbin Medical University Cancer Hospital, Harbin, 150081, China.<br /><searchLink fieldCode="AU" term="%22Liu+T%22">Liu T</searchLink>; Department of Pathology, Second Affiliated Hospital of Harbin Medical University, Harbin, 150086, China.<br /><searchLink fieldCode="AU" term="%22Yuan+G%22">Yuan G</searchLink>; School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230026, China. yuangang@sibet.ac.cn.; Department of Medical Imaging, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, 215163, China. yuangang@sibet.ac.cn.<br /><searchLink fieldCode="AU" term="%22Peng+Y%22">Peng Y</searchLink>; Department of Medical Imaging, International Exemplary Cooperation Base of Precision Imaging for Diagnosis and Treatment, Guizhou Provincial People's Hospital, Guizhou, 550002, China. pys@mail.ustc.edu.cn.<br /><searchLink fieldCode="AU" term="%22Zheng+J%22">Zheng J</searchLink>; School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230026, China.; Department of Medical Imaging, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, 215163, China. – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%227902060%22">Journal of cancer research and clinical oncology</searchLink> [J Cancer Res Clin Oncol] 2023 Nov; Vol. 149 (17), pp. 15469-15478. <i>Date of Electronic Publication: </i>2023 Aug 29. – Name: TypePub Label: Publication Type Group: TypPub Data: Journal Article – Name: TitleSource Label: Journal Info Group: Src Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22Springer-Verlag%22">Springer-Verlag </searchLink><i>Country of Publication: </i>Germany <i>NLM ID: </i>7902060 <i>Publication Model: </i>Print-Electronic <i>Cited Medium: </i>Internet <i>ISSN: </i>1432-1335 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2201715216%22">01715216 </searchLink><i>NLM ISO Abbreviation: </i>J Cancer Res Clin Oncol <i>Subsets: </i>MEDLINE |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=mdl&AN=37642722 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1007/s00432-023-05329-2 Languages: – Code: eng Text: English PhysicalDescription: Pagination: StartPage: 15469 Titles: – TitleFull: Combining radiomics and deep learning features of intra-tumoral and peri-tumoral regions for the classification of breast cancer lung metastasis and primary lung cancer with low-dose CT. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Li L – PersonEntity: Name: NameFull: Zhou X – PersonEntity: Name: NameFull: Cui W – PersonEntity: Name: NameFull: Li Y – PersonEntity: Name: NameFull: Liu T – PersonEntity: Name: NameFull: Yuan G – PersonEntity: Name: NameFull: Peng Y – PersonEntity: Name: NameFull: Zheng J IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 11 Text: 2023 Nov Type: published Y: 2023 Identifiers: – Type: issn-electronic Value: 1432-1335 Numbering: – Type: volume Value: 149 – Type: issue Value: 17 Titles: – TitleFull: Journal of cancer research and clinical oncology Type: main |
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