Enhancing MR image segmentation with realistic adversarial data augmentation.

Chen, Chen; Qin, Chen; Ouyang, Cheng; Li, Zeju; Wang, Shuo; Qiu, Huaqi; Chen, Liang; Tarroni, Giacomo; Bai, Wenjia; Rueckert, Daniel

Chen, Chen; Qin, Chen; Ouyang, Cheng; Li, Zeju; Wang, Shuo; Qiu, Huaqi; Chen, Liang; Tarroni, Giacomo; Bai, Wenjia; Rueckert, Daniel.

Afiliación

Chen C; Department of Computing, Imperial College London, UK. Electronic address: chen.chen15@imperial.ac.uk.
Qin C; Institute for Digital Communications, School of Engineering, University of Edinburgh, UK; Department of Electronics and Electrical Engineering, Imperial College London, UK.
Ouyang C; Department of Computing, Imperial College London, UK.
Li Z; Department of Computing, Imperial College London, UK.
Wang S; Digital Medicine Research Centre, School of Basic Medical Sciences, Fudan University, China; Shanghai Key Laboratory of MICCAI, Shanghai, China.
Qiu H; Department of Computing, Imperial College London, UK.
Chen L; Department of Computing, Imperial College London, UK.
Tarroni G; Department of Computing, Imperial College London, UK; CitAI Research Centre, Department of Computer Science, City, University of London, UK.
Bai W; Department of Computing, Imperial College London, UK; Department of Brain Sciences, Imperial College London, UK; Data Science Institute, Imperial College London, UK.
Rueckert D; Department of Computing, Imperial College London, UK; Klinikum rechts der Isar, Technical University of Munich, Germany.

Med Image Anal ; 82: 102597, 2022 11.

Article en En | MEDLINE | ID: mdl-36095907

Asunto(s)

Procesamiento de Imagen Asistido por Computador; Redes Neurales de la Computación; Humanos; Masculino; Procesamiento de Imagen Asistido por Computador/métodos; Aprendizaje Automático Supervisado

Palabras clave

Adversarial data augmentation; Adversarial training; Data augmentation; MR image segmentation; Model generalization

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Texto completo: 1 Base de datos: MEDLINE Asunto principal: Procesamiento de Imagen Asistido por Computador / Redes Neurales de la Computación Idioma: En Revista: Med Image Anal Asunto de la revista: DIAGNOSTICO POR IMAGEM Año: 2022 Tipo del documento: Article

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