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Listar por autor "Sangüesa Nebot, Cinta"

RiuNet: Repositorio Institucional de la Universidad Politécnica de Valencia

Listar por autor "Sangüesa Nebot, Cinta"

Ordenar por:Orden:Resultados:

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    A Confidence Habitats Methodology in MR Quantitative Diffusion for the Classification of Neuroblastic Tumors 
    Cerdà Alberich, Leonor; Sangüesa Nebot, Cinta; Alberich-Bayarri, Angel; Carot Sierra, José Miguel; Martinez de las Heras, Blanca; Veiga Canuto, Diana; Cañete, Adela; Martí-Bonmatí, Luis (MDPI AG, 2020-12)
    [EN] There is growing interest in applying quantitative diffusion techniques to magnetic resonance imaging for cancer diagnosis and treatment. These measurements are used as a surrogate marker of tumor cellularity and ...
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    Comparative Multicentric Evaluation of Inter-Observer Variability in Manual and Automatic Segmentation of Neuroblastic Tumors in Magnetic Resonance Images 
    Veiga-Canuto, Diana; Cerdà-Alberich, Leonor; Sangüesa Nebot, Cinta; Martínez de las Heras, Blanca; Pötschger, Ulrique; Gabelloni, Michela; Carot Sierra, José Miguel; Taschner-Mandl, Sabine; Düster, Vanessa; Cañete, Adela; Ladenstein, Ruth; Neri, Emanuele; Marti-Bonmati, Luis (MDPI AG, 2022-08)
    [EN] Simple Summary Tumor segmentation is a key step in oncologic imaging processing and is a time-consuming process usually performed manually by radiologists. To facilitate it, there is growing interest in applying ...
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    Independent Validation of a Deep Learning nnU-Net Tool for Neuroblastoma Detection and Segmentation in MR Images 
    Veiga-Canuto, Diana; Cerdá-Alberich, Leonor; Jimenez-Pastor, Ana; Carot Sierra, José Miguel; Gomis-Maya, Armando; Sangüesa Nebot, Cinta; Fernandez-Patón, Matías; Martinez de las Heras, Blanca; Taschner-Mandl, Sabine; Düster, Vanessa; Pötschger, Ulrike; Simon, Thorsten; Neri, Emanuele; Alberich-Bayarri, Angel; Cañete, Adela; Hero, Barbara; Ladenstein, Ruth; Martí-Bonmatí, Luis (MDPI AG, 2023-03)
    [EN] Tumor segmentation is a key step in oncologic imaging processing. We have recently developed a model to detect and segment neuroblastic tumors on MR images based on deep learning architecture nnU-Net. In this work, ...