Towards quality control and harmonization of deep learning CT radiomics: An in-silico feasibility study with virtual colorectal liver metastases.
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| Title: | Towards quality control and harmonization of deep learning CT radiomics: An in-silico feasibility study with virtual colorectal liver metastases. |
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| Authors: | Venugopal M; Technology & Innovation Center, GE HealthCare, JFWTC, Bengaluru, Karnataka, India., Ramani S; Technology & Innovation Center, GE HealthCare, Niskayuna, New York, USA., Peoples JJ; Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, New York, USA., Do RKG; Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, New York, USA., Simpson AL; School of Computing/Department of Biomedical and Molecular Sciences, Queen's University, Ontario, Canada., Wang G; Department of Biomedical Engineering, Rensselaer Polytechnic Institute, Troy, New York, USA., De Man B; Technology & Innovation Center, GE HealthCare, Niskayuna, New York, USA. |
| Source: | Medical physics [Med Phys] 2026 May; Vol. 53 (5), pp. e70500. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: John Wiley and Sons, Inc Country of Publication: United States NLM ID: 0425746 Publication Model: Print Cited Medium: Internet ISSN: 2473-4209 (Electronic) Linking ISSN: 00942405 NLM ISO Abbreviation: Med Phys Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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