P
Pierrick Coupé
Researcher at L'Abri
Publications - 201
Citations - 11121
Pierrick Coupé is an academic researcher from L'Abri. The author has contributed to research in topics: Segmentation & Noise reduction. The author has an hindex of 45, co-authored 183 publications receiving 9147 citations. Previous affiliations of Pierrick Coupé include University of Bordeaux & Polytechnic University of Valencia.
Papers
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Multi-atlas labeling with population-specific template and non-local patch-based label fusion
TL;DR: This work proposes a new method combining a population-specific nonlinear template atlas approach with non-local patch-based structure segmentation for whole brain segmentation into individual structures to benefit from the efficient intensity-driven segmentation of the non- local means framework.
Book ChapterDOI
Blind MRI Brain Lesion Inpainting Using Deep Learning
José V. Manjón,José E. Romero,Roberto Vivo-Hernando,G. Rubio,Fernando Aparici,María de la Iglesia-Vayá,Thomas Tourdias,Pierrick Coupé +7 more
TL;DR: A deep network is proposed that is able to blindly inpaint lesions in brain images automatically allowing current pipelines to robustly operate under pathological conditions and improved robustness/accuracy in the brain segmentation problem using the SPM12 pipeline with automatically inpainted images.
Journal ArticleDOI
pBrain: A novel pipeline for Parkinson related brain structure segmentation.
José V. Manjón,Alexa Bertó,José E. Romero,Enrique Lanuza,Roberto Vivo-Hernando,Fernando Aparici-Robles,Pierrick Coupé +6 more
TL;DR: A novel pipeline for Parkinson`s disease structure segmentation using state-of-the-art fast multiatlas patch-based label fusion with systematic error correction allowing the analysis of large legacy databases is presented.
Posted ContentDOI
Multimodal Hippocampal Subfield Grading For Alzheimer\'s Disease Classification
TL;DR: The experiments conducted in this work showed that the whole hippocampus provides the most discriminant biomarkers for advanced AD detection while biomarkers applied into subiculum obtain the best results for AD prediction, improving by 2% the accuracy compared to the entire hippocampus.
Book ChapterDOI
Patch-Based DTI Grading: Application to Alzheimer’s Disease Classification
Kilian Hett,Kilian Hett,Vinh-Thong Ta,Vinh-Thong Ta,Rémi Giraud,Mary Mondino,Mary Mondino,José V. Manjón,Pierrick Coupé,Pierrick Coupé,Alzheimer’s Disease Neuroimaging Initiative +10 more
TL;DR: In this paper, the authors proposed a patch-based grading-based DTI features with basic MRI/DTI biomarkers and evaluated their method within a cross validation classification framework.