Detecting the appearance of new T2-w multiple sclerosis lesions in longitudinal studies using deep convolutional neural networks

被引:0
|
作者
Salem, M. [1 ]
Valverde, S. [1 ]
Cabezas, M. [1 ]
Pareto, D. [2 ,3 ]
Oliver, A. [1 ]
Salvi, J. [1 ]
Rovira, A. [2 ,3 ]
Llado, X. [1 ]
机构
[1] Univ Girona, ATC, Girona, Spain
[2] Vall dHebron Univ Hosp, Dept Radiol, Sect Neuroradiol, Barcelona, Spain
[3] Vall dHebron Univ Hosp, Dept Radiol, Magnet Resonance Unit, Barcelona, Spain
关键词
D O I
暂无
中图分类号
R74 [神经病学与精神病学];
学科分类号
摘要
P894
引用
收藏
页码:462 / 463
页数:2
相关论文
共 50 条
  • [1] A fully convolutional neural network for new T2-w lesion detection in multiple sclerosis
    Salem, Mostafa
    Valverde, Sergi
    Cabezas, Mariano
    Pareto, Deborah
    Oliver, Arnau
    Salvi, Joaquim
    Rovira, Alex
    Llado, Xavier
    [J]. NEUROIMAGE-CLINICAL, 2020, 25
  • [2] A supervised framework with intensity subtraction and deformation field features for the detection of new T2-w lesions in multiple sclerosis
    Salem, Mostafa
    Cabezas, Mariano
    Valverde, Sergi
    Pareto, Deborah
    Oliver, Arnau
    Salvi, Joaquim
    Rovira, Alex
    Llado, Xavier
    [J]. NEUROIMAGE-CLINICAL, 2018, 17 : 607 - 615
  • [3] Fully automated longitudinal segmentation of new or enlarged multiple sclerosis lesions using 3D convolutional neural networks
    Krueger, Julia
    Opfer, Roland
    Gessert, Nils
    Ostwaldt, Ann-Christin
    Manogaran, Praveena
    Kitzler, Hagen H.
    Schlaefer, Alexander
    Schippling, Sven
    [J]. NEUROIMAGE-CLINICAL, 2020, 28
  • [4] Supervised detection of newly appearing T2-w multiple sclerosis lesions with subtraction and deformation fields features
    Salem, M.
    Cabezas, M.
    Valverde, S.
    Pareto, D.
    Oliver, A.
    Salvi, J.
    Rovira, A.
    Llado, X.
    [J]. MULTIPLE SCLEROSIS JOURNAL, 2017, 23 : 794 - 794
  • [5] Quantification of Brain Lesions in Multiple Sclerosis Patients using Segmentation by Convolutional Neural Networks
    de Oliveira, Marcela
    Santinelli, Felipe Balistieri
    Piacenti-Silva, Marina
    Gomes Rocha, Fernando Coronetti
    Barbieri, Fabio Augusto
    Lisboa-Filho, Paulo Noronha
    Santos, Jorge Manuel
    Cardoso, Jaime dos Santos
    [J]. 2020 IEEE INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOMEDICINE, 2020, : 2045 - 2048
  • [6] Multiple Sclerosis Lesion Segmentation Using Longitudinal Normalization and Convolutional Recurrent Neural Networks
    Tascon-Morales, Sergio
    Hoffmann, Stefan
    Treiber, Martin
    Mensing, Daniel
    Oliver, Arnau
    Guenther, Matthias
    Gregori, Johannes
    [J]. MACHINE LEARNING IN CLINICAL NEUROIMAGING AND RADIOGENOMICS IN NEURO-ONCOLOGY, MLCN 2020, RNO-AI 2020, 2020, 12449 : 148 - 158
  • [7] Automatic and Robust Segmentation of Multiple Sclerosis Lesions with Convolutional Neural Networks
    Afzal, H. M. Rehan
    Luo, Suhuai
    Ramadan, Saadallah
    Lechner-Scott, Jeannette
    Amin, Mohammad Ruhul
    Li, Jiaming
    Afzal, M. Kamran
    [J]. CMC-COMPUTERS MATERIALS & CONTINUA, 2021, 66 (01): : 977 - 991
  • [8] Automated segmentation of multiple sclerosis lesions based on convolutional neural networks
    Haj Messaoud, Nada
    Mansour, Asma
    Aissi, Mouna
    Ayari, Rim
    Frih, Mahbouba
    Ben Abdallah, Asma
    Bedoui, Mohamed Hedi
    [J]. COMPUTER METHODS IN BIOMECHANICS AND BIOMEDICAL ENGINEERING-IMAGING AND VISUALIZATION, 2023, 11 (04): : 1359 - 1377
  • [9] DeepCONN: patch-wise deep convolutional neural networks for the segmentation of multiple sclerosis brain lesions
    Amrita Kaur
    Lakhwinder Kaur
    Ashima Singh
    [J]. Multimedia Tools and Applications, 2024, 83 : 24401 - 24433
  • [10] DeepCONN: patch-wise deep convolutional neural networks for the segmentation of multiple sclerosis brain lesions
    Kaur, Amrita
    Kaur, Lakhwinder
    Singh, Ashima
    [J]. MULTIMEDIA TOOLS AND APPLICATIONS, 2023, 83 (8) : 24401 - 24433