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Multi-institutional classification of fibroglandular tissue and background parenchymal enhancement in breast MRI using deep learning.

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第一作者： Kai,Geissler

第一单位： Fraunhofer Institute for Digital Medicine MEVIS, Bremen, Germany.

作者： Kai,Geissler ^[1] ; Hans,Meine ^[1] ; Hendrik,Laue ^[1] ; Robert,Grimm ^[2] ; Heinrich,von Busch ^[3] ; Susanne,Diekmann ^[1] ; Dieter,Szolar ^[4] ; Sabine,Ohlmeyer ^[5] ; Edyta,Szurowska ^[6] ; Uwe,Fischer ^[7] ; Nachiko,Uchiyama ^[8] ; Kazuki,Oyama ^[9] ; Noemi,Schmidt ^[10] ; Markus,Wenzel ^[11]

作者单位： Fraunhofer Institute for Digital Medicine MEVIS, Bremen, Germany. ^[1] Siemens Healthineers AG, Research & Clinical Translation, Magnetic Resonance, Erlangen, Germany. ^[2] Siemens Healthineers AG, Digital & Automation, Forchheim, Germany. ^[3] Diagnostikum Graz, Graz, Austria. ^[4] Universitätsklinikum Erlangen, Erlangen, Germany. ^[5] Medical University of Gdańsk, Second Radiology Department, Gdańsk, Poland. ^[6] Diagnostic Breast Center Goettingen, Goettingen, Germany. ^[7] National Cancer Center, Department of Radiology, Chuo, Japan. ^[8] Shinshu University School of Medicine, Department of Radiology, Nagano, Japan. ^[9] University Hospital Basel, Universitätsspital CH, Basel, Switzerland. ^[10] Fraunhofer Institute for Digital Medicine MEVIS, Bremen, Germany.;Constructor University, Bremen, Germany. ^[11]

关键词 background parenchymal enhancement classification breast magnetic resonance imaging deep learning segmentation fibroglandular tissue classification fibroglandular tissue segmentation

DOI 10.1117/1.JMI.13.3.034501

PMID 42136968

发布时间 2026-05-15

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Journal of medical imaging (Bellingham, Wash.)

2026年13卷3期

034501页

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Journal of medical imaging (Bellingham, Wash.)

2026年13卷3期

034501页

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Multi-institutional classification of fibroglandular tissue and background parenchymal enhancement in breast MRI using deep learning.

Journal of medical imaging (Bellingham, Wash.)

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Multi-institutional classification of fibroglandular tissue and background parenchymal enhancement in breast MRI using deep learning.

Journal of medical imaging (Bellingham, Wash.)

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Journal of medical imaging (Bellingham, Wash.)

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