- -

Browsing by Author "Ta, Vinh-Thong"

RiuNet: Institutional repository of the Polithecnic University of Valencia

Browsing by Author "Ta, Vinh-Thong"

Sort by: Order: Results:

  • thumb
    Adaptive fusion of texture-based grading for Alzheimer's disease classification 
    Hett, Kilian; Ta, Vinh-Thong; Manjón Herrera, José Vicente; Coupe, Pierrick (Elsevier, 2018)
    [EN] Alzheimer's disease is a neurodegenerative process leading to irreversible mental dysfunctions. To date, diagnosis is established after incurable brain structure alterations. The development of new biomarkers is crucial ...
  • Icon
    An Optimized PatchMatch for multi-scale and multi-feature label fusion 
    Giraud, Rémi; Ta, Vinh-Thong; Papadakis, Nicolas; Manjón Herrera, José Vicente; Collins, Louis; Coupé Pierrick; Alzheimers Dis Neuroimaging Initia (Elsevier, 2016-01-01)
    Automatic segmentation methods are important tools for quantitative analysis of Magnetic Resonance Images (MRI). Recently, patch-based label fusion approaches have demonstrated state-of-the-art segmentation accuracy. In ...
  • thumb
    AssemblyNet: A large ensemble of CNNs for 3D whole brain MRI segmentation 
    Coupé, Pierrick; Mansencal, Boris; Clement, Michael; Giraud, Rémi; Denis de Senneville, Baudouin; Ta, Vinh-Thong; Lepetit, Vincent; Manjón Herrera, José Vicente (Elsevier, 2020-10-01)
    [EN] Whole brain segmentation of fine-grained structures using deep learning (DL) is a very challenging task since the number of anatomical labels is very high compared to the number of available training images. To address ...
  • thumb
    CERES: A new cerebellum lobule segmentation method 
    Romero Gómez, José Enrique; Coupe, Pierrick; Giraud, Remi; Ta, Vinh-Thong; Fonov, Vladimir; Park, Min Tae M; Chalcravarty, M. Mallar; Voineskos, Aristotle N.; Manjón Herrera, José Vicente (Elsevier, 2017)
    [EN] The human cerebellum is involved in language, motor tasks and cognitive processes such as attention or emotional processing. Therefore, an automatic and accurate segmentation method is highly desirable to measure and ...
  • Icon
    DeepLesionBrain: Towards a broader deep-learning generalization for multiple sclerosis lesion segmentation 
    Kamraoui, Reda Abdellah; Ta, Vinh-Thong; Tourdias, Thomas; Mansencal, Boris; Manjón Herrera, José Vicente; Coupé, Pierrick (Elsevier, 2022-02)
    [EN] Recently, segmentation methods based on Convolutional Neural Networks (CNNs) showed promising per-formance in automatic Multiple Sclerosis (MS) lesions segmentation. These techniques have even out-performed human ...
  • thumb
    Multi-scale graph-based grading for Alzheimer's disease prediction 
    Hett, Kilian; Ta, Vinh-Thong; Oguz, Ipek; Manjón Herrera, José Vicente; Coupé, Pierrick; Alzheimers Disease Neuroimaging Initiative (Elsevier, 2021-01)
    [EN] The prediction of subjects with mild cognitive impairment (MCI) who will progress to Alzheimer¿s disease (AD) is clinically relevant, and may above all have a significant impact on accelerating the development of new ...
  • thumb
    Multimodal Hippocampal Subfield Grading For Alzheimer's Disease Classification 
    Hett, Kilian; Ta, Vinh-Thong; Catheline, Gwenaelle; Tourdias, Thomas; Manjón Herrera, José Vicente; Coupé, Pierrick; Alzheimers Disease Neuroimaging Initiative (Nature Publishing Group, 2019-09-25)
    [EN] Numerous studies have proposed biomarkers based on magnetic resonance imaging (MRI) to detect and predict the risk of evolution toward Alzheimer's disease (AD). Most of these methods have focused on the hippocampus, ...