Zobrazeno 1 - 10
of 26
pro vyhledávání: '"Bone, Alexandre"'
Autor:
Vétil, Rebeca, Abi-Nader, Clément, Bône, Alexandre, Vullierme, Marie-Pierre, Rohé, Marc-Michel, Gori, Pietro, Bloch, Isabelle
We address the problem of learning Deep Learning Radiomics (DLR) that are not redundant with Hand-Crafted Radiomics (HCR). To do so, we extract DLR features using a VAE while enforcing their independence with HCR features by minimizing their mutual i
Externí odkaz:
http://arxiv.org/abs/2308.11389
Large medical imaging datasets can be cheaply and quickly annotated with low-confidence, weak labels (e.g., radiological scores). Access to high-confidence labels, such as histology-based diagnoses, is rare and costly. Pretraining strategies, like co
Externí odkaz:
http://arxiv.org/abs/2307.04617
Identifying cirrhosis is key to correctly assess the health of the liver. However, the gold standard diagnosis of the cirrhosis needs a medical intervention to obtain the histological confirmation, e.g. the METAVIR score, as the radiological presenta
Externí odkaz:
http://arxiv.org/abs/2302.08427
Autor:
Vétil, Rebeca, Nader, Clément Abi, Bône, Alexandre, Vullierme, Marie-Pierre, Roheé, Marc-Michel, Gori, Pietro, Bloch, Isabelle
Publikováno v:
Medical Image Computing and Computer Assisted Intervention 2022, Lecture Notes in Computer Science volume 13432, pp 464-473
We propose a scalable and data-driven approach to learn shape distributions from large databases of healthy organs. To do so, volumetric segmentation masks are embedded into a common probabilistic shape space that is learned with a variational auto-e
Externí odkaz:
http://arxiv.org/abs/2210.12095
Autor:
Ali, Omar, Bone, Alexandre, Accardo, Caterina, Belkouchi, Omar, Rohe, Marc-Michel, Vibert, Eric, Vignon-Clementel, Irene
Surgical resections are the most prevalent curative treatment for primary liver cancer. Tumors located in critical positions are known to complexify liver resections (LR). While experienced surgeons in specialized medical centers may have the necessa
Externí odkaz:
http://arxiv.org/abs/2210.08318
Autor:
Saha, Anindo, Bosma, Joeran S., Twilt, Jasper J., van Ginneken, Bram, Noordman, Constant R., Slootweg, Ivan, Roest, Christian, Fransen, Stefan J., Sunoqrot, Mohammed R.S., Bathen, Tone F., Rouw, Dennis, Immerzeel, Jos, Geerdink, Jeroen, van Run, Chris, Groeneveld, Miriam, Meakin, James, Karagöz, Ahmet, Bône, Alexandre, Routier, Alexandre, Marcoux, Arnaud, Abi-Nader, Clément, Li, Cynthia Xinran, Feng, Dagan, Alis, Deniz, Karaarslan, Ercan, Ahn, Euijoon, Nicolas, François, Sonn, Geoffrey A., Bhattacharya, Indrani, Kim, Jinman, Shi, Jun, Jahanandish, Hassan, An, Hong, Kan, Hongyu, Oksuz, Ilkay, Qiao, Liang, Rohé, Marc-Michel, Yergin, Mert, Khadra, Mohamed, Şeker, Mustafa E., Kartal, Mustafa S., Debs, Noëlie, Fan, Richard E., Saunders, Sara, Soerensen, Simon J.C., Moroianu, Stefania, Vesal, Sulaiman, Yuan, Yuan, Malakoti-Fard, Afsoun, Mačiūnien, Agnė, Kawashima, Akira, de Sousa Machadov, Ana M.M. de M.G., Moreira, Ana Sofia L., Ponsiglione, Andrea, Rappaport, Annelies, Stanzione, Arnaldo, Ciuvasovas, Arturas, Turkbey, Baris, de Keyzer, Bart, Pedersen, Bodil G., Eijlers, Bram, Chen, Christine, Riccardo, Ciabattoni, Courrech Staal, Ewout F.W., Jäderling, Fredrik, Langkilde, Fredrik, Aringhieri, Giacomo, Brembilla, Giorgio, Son, Hannah, Vanderlelij, Hans, Raat, Henricus P.J., Pikūnienė, Ingrida, Macova, Iva, Schoots, Ivo, Caglic, Iztok, Zawaideh, Jeries P., Wallström, Jonas, Bittencourt, Leonardo K., Khurram, Misbah, Choi, Moon H., Takahashi, Naoki, Tan, Nelly, Franco, Paolo N., Gutierrez, Patricia A., Thimansson, Per Erik, Hanus, Pieter, Puech, Philippe, Rau, Philipp R., de Visschere, Pieter, Guillaume, Ramette, Cuocolo, Renato, Falcão, Ricardo O., van Stiphout, Rogier S.A., Girometti, Rossano, Briediene, Ruta, Grigienė, Rūta, Gitau, Samuel, Withey, Samuel, Ghai, Sangeet, Penzkofer, Tobias, Barrett, Tristan, Tammisetti, Varaha S., Løgager, Vibeke B., Černý, Vladimír, Venderink, Wulphert, Law, Yan M., Lee, Young J., Bjartell, Anders, Padhani, Anwar R., Bonekamp, David, Villeirs, Geert, Salomon, Georg, Giannarini, Gianluca, Kalpathy-Cramer, Jayashree, Barentsz, Jelle, Maier-Hein, Klaus H., Rusu, Mirabela, Obuchowski, Nancy A., Rouvière, Olivier, van den Bergh, Roderick, Panebianco, Valeria, Kasivisvanathan, Veeru, Yakar, Derya, Elschot, Mattijs, Veltman, Jeroen, Fütterer, Jurgen J., de Rooij, Maarten, Huisman, Henkjan, Bosma, Joeran S *, Twilt, Jasper J *, Padhani, Anwar R, Maier-Hein, Klaus H, Obuchowski, Nancy A, Fütterer, Jurgen J
Publikováno v:
In The Lancet Oncology July 2024 25(7):879-887
Autor:
Brusset, Bleuenn, Jacquemin, Marion, Teyssier, Yann, Roth, Gaël S., Sturm, Nathalie, Roustit, Matthieu, Bône, Alexandre, Ghelfi, Julien, Costentin, Charlotte E., Decaens, Thomas
Publikováno v:
In JHEP Reports January 2024 6(1)
Autor:
Goparaju, Anupama, Bone, Alexandre, Hu, Nan, Henninger, Heath B., Anderson, Andrew E., Durrleman, Stanley, Jacxsens, Matthijs, Morris, Alan, Csecs, Ibolya, Marrouche, Nassir, Elhabian, Shireen Y.
Statistical shape modeling (SSM) is widely used in biology and medicine as a new generation of morphometric approaches for the quantitative analysis of anatomical shapes. Technological advancements of in vivo imaging have led to the development of op
Externí odkaz:
http://arxiv.org/abs/2009.02878
We propose a method to learn a distribution of shape trajectories from longitudinal data, i.e. the collection of individual objects repeatedly observed at multiple time-points. The method allows to compute an average spatiotemporal trajectory of shap
Externí odkaz:
http://arxiv.org/abs/1803.10119
The analysis of manifold-valued data requires efficient tools from Riemannian geometry to cope with the computational complexity at stake. This complexity arises from the always-increasing dimension of the data, and the absence of closed-form express
Externí odkaz:
http://arxiv.org/abs/1711.08725