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Journal Abstract Search

431 related items for PubMed ID: 37602841

  • 1. Role of sureness in evaluating AI/CADx: Lesion-based repeatability of machine learning classification performance on breast MRI.
    Whitney HM, Drukker K, Vieceli M, Van Dusen A, de Oliveira M, Abe H, Giger ML.
    Med Phys; 2024 Mar; 51(3):1812-1821. PubMed ID: 37602841
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  • 4. Characterization of spatiotemporal changes for the classification of dynamic contrast-enhanced magnetic-resonance breast lesions.
    Milenković J, Hertl K, Košir A, Zibert J, Tasič JF.
    Artif Intell Med; 2013 Jun; 58(2):101-14. PubMed ID: 23548472
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  • 6. Radiomic and Artificial Intelligence Analysis with Textural Metrics Extracted by Contrast-Enhanced Mammography and Dynamic Contrast Magnetic Resonance Imaging to Detect Breast Malignant Lesions.
    Fusco R, Di Bernardo E, Piccirillo A, Rubulotta MR, Petrosino T, Barretta ML, Mattace Raso M, Vallone P, Raiano C, Di Giacomo R, Siani C, Avino F, Scognamiglio G, Di Bonito M, Granata V, Petrillo A.
    Curr Oncol; 2022 Mar 13; 29(3):1947-1966. PubMed ID: 35323359
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  • 8. A computer-aided diagnosis system for breast DCE-MRI at high spatiotemporal resolution.
    Dalmış MU, Gubern-Mérida A, Vreemann S, Karssemeijer N, Mann R, Platel B.
    Med Phys; 2016 Jan 13; 43(1):84. PubMed ID: 26745902
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  • 10. Breast Cancer Classification on Multiparametric MRI - Increased Performance of Boosting Ensemble Methods.
    Vamvakas A, Tsivaka D, Logothetis A, Vassiou K, Tsougos I.
    Technol Cancer Res Treat; 2022 Jan 13; 21():15330338221087828. PubMed ID: 35341421
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  • 11. Classification of small lesions on dynamic breast MRI: Integrating dimension reduction and out-of-sample extension into CADx methodology.
    Nagarajan MB, Huber MB, Schlossbauer T, Leinsinger G, Krol A, Wismüller A.
    Artif Intell Med; 2014 Jan 13; 60(1):65-77. PubMed ID: 24355697
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  • 13. Radiomics methodology for breast cancer diagnosis using multiparametric magnetic resonance imaging.
    Hu Q, Whitney HM, Giger ML.
    J Med Imaging (Bellingham); 2020 Jul 13; 7(4):044502. PubMed ID: 32864390
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  • 14. Additive Benefit of Radiomics Over Size Alone in the Distinction Between Benign Lesions and Luminal A Cancers on a Large Clinical Breast MRI Dataset.
    Whitney HM, Taylor NS, Drukker K, Edwards AV, Papaioannou J, Schacht D, Giger ML.
    Acad Radiol; 2019 Feb 13; 26(2):202-209. PubMed ID: 29754995
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  • 15. Textural analysis of early-phase spatiotemporal changes in contrast enhancement of breast lesions imaged with an ultrafast DCE-MRI protocol.
    Milenković J, Dalmış MU, Žgajnar J, Platel B.
    Med Phys; 2017 Sep 13; 44(9):4652-4664. PubMed ID: 28622412
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  • 16. Multimodality computer-aided breast cancer diagnosis with FFDM and DCE-MRI.
    Yuan Y, Giger ML, Li H, Bhooshan N, Sennett CA.
    Acad Radiol; 2010 Sep 13; 17(9):1158-67. PubMed ID: 20692620
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  • 17. Artificial Intelligence Applied to Breast MRI for Improved Diagnosis.
    Jiang Y, Edwards AV, Newstead GM.
    Radiology; 2021 Jan 13; 298(1):38-46. PubMed ID: 33078996
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  • 19. Automatic identification and classification of characteristic kinetic curves of breast lesions on DCE-MRI.
    Chen W, Giger ML, Bick U, Newstead GM.
    Med Phys; 2006 Aug 13; 33(8):2878-87. PubMed ID: 16964864
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  • 20. Evaluation of clinical breast MR imaging performed with prototype computer-aided diagnosis breast MR imaging workstation: reader study.
    Shimauchi A, Giger ML, Bhooshan N, Lan L, Pesce LL, Lee JK, Abe H, Newstead GM.
    Radiology; 2011 Mar 13; 258(3):696-704. PubMed ID: 21212365
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