Zobrazeno 1 - 10
of 373
pro vyhledávání: '"Decazes, P."'
Autor:
Mesbah, Zacharia, Mottay, Léo, Modzelewski, Romain, Decazes, Pierre, Hapdey, Sébastien, Ruan, Su, Thureau, Sébastien
For the last three years, the AutoPET competition gathered the medical imaging community around a hot topic: lesion segmentation on Positron Emitting Tomography (PET) scans. Each year a different aspect of the problem is presented; in 2024 the multip
Externí odkaz:
http://arxiv.org/abs/2410.02807
Single-modality medical images generally do not contain enough information to reach an accurate and reliable diagnosis. For this reason, physicians generally diagnose diseases based on multimodal medical images such as, e.g., PET/CT. The effective fu
Externí odkaz:
http://arxiv.org/abs/2309.05919
Autor:
David Morland, Lukshe Kanagaratnam, Fabrice Hubelé, Elise Toussaint, Sylvain Choquet, Aurélie Kas, Pierre-Ambroise Caquot, Corinne Haioun, Emmanuel Itti, Stéphane Leprêtre, Pierre Decazes, Fontanet Bijou, Paul Schwartz, Caroline Jacquet, Adrien Chauchet, Julien Matuszak, Nassim Kamar, Pierre Payoux, K-VIROGREF Study Group, Eric Durot
Publikováno v:
EJNMMI Research, Vol 14, Iss 1, Pp 1-10 (2024)
Abstract Background Besides International Prognostic Index (IPI) score, baseline prognostic factors of post-transplant lymphoproliferative disorders (PTLD) are poorly identified due to the rarity of the disease. New indexes derived from healthy organ
Externí odkaz:
https://doaj.org/article/938661d0b675480cade62b8d05c6d279
Autor:
S. Draye-Carbonnier, V. Camus, S. Becker, D. Tonnelet, E. Lévêque, A. Zduniak, F. Jardin, H. Tilly, P. Vera, P. Decazes
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-14 (2024)
Abstract The prognostic value of radiomic quantitative features measured on pre-treatment 18F-FDG PET/CT was investigated in patients with follicular lymphoma (FL). We conducted a retrospective study of 126 FL patients (grade 1-3a) diagnosed between
Externí odkaz:
https://doaj.org/article/aa4fb1c952dd489dbbb9c593fd337efa
Publikováno v:
International Journal of Approximate Reasoning, Volume 149, 2022, Pages 39-60
An automatic evidential segmentation method based on Dempster-Shafer theory and deep learning is proposed to segment lymphomas from three-dimensional Positron Emission Tomography (PET) and Computed Tomography (CT) images. The architecture is composed
Externí odkaz:
http://arxiv.org/abs/2201.13078
Autor:
Yousefirizi, Fereshteh, Decazes, Pierre, Amyar, Amine, Ruan, Su, Saboury, Babak, Rahmim, Arman
Artificial intelligence (AI) techniques have significant potential to enable effective, robust and automated image phenotyping including identification of subtle patterns. AI-based detection searches the image space to find the regions of interest ba
Externí odkaz:
http://arxiv.org/abs/2110.10332
Lymphoma detection and segmentation from whole-body Positron Emission Tomography/Computed Tomography (PET/CT) volumes are crucial for surgical indication and radiotherapy. Designing automatic segmentation methods capable of effectively exploiting the
Externí odkaz:
http://arxiv.org/abs/2108.05422
PET and CT are two modalities widely used in medical image analysis. Accurately detecting and segmenting lymphomas from these two imaging modalities are critical tasks for cancer staging and radiotherapy planning. However, this task is still challeng
Externí odkaz:
http://arxiv.org/abs/2104.13293
One of the most challenges in medical imaging is the lack of data. It is proven that classical data augmentation methods are useful but still limited due to the huge variation in images. Using generative adversarial networks (GAN) is a promising way
Externí odkaz:
http://arxiv.org/abs/2003.08663
Autor:
Caroline Robert, Aurélien Marabelle, Fabrice Barlesi, Samy Ammari, David Planchard, Siham Farhane, Paul-Henry Cournède, Pierre Decazes, Younes Belkouchi, Léo Mottay, Littisha Lawrance, Antoine de Prévia, Hugues Talbot, Florian Guisier, Tony Ibrahim, Pierre Vera, Nathalie Lassau
Publikováno v:
Journal for ImmunoTherapy of Cancer, Vol 11, Iss 9 (2023)
Background Our aim was to explore the prognostic value of anthropometric parameters in a large population of patients treated with immunotherapy.Methods We retrospectively included 623 patients with advanced non-small cell lung cancer (NSCLC) (n=318)
Externí odkaz:
https://doaj.org/article/45c25158807d48c79b5b5abe405896a3