Zobrazeno 1 - 10
of 28
pro vyhledávání: '"Greer, Hastings"'
Autor:
Greer, Hastings, Tian, Lin, Vialard, Francois-Xavier, Kwitt, Roland, Estepar, Raul San Jose, Niethammer, Marc
Image registration estimates spatial correspondences between a pair of images. These estimates are typically obtained via numerical optimization or regression by a deep network. A desirable property of such estimators is that a correspondence estimat
Externí odkaz:
http://arxiv.org/abs/2405.16738
Autor:
Tian, Lin, Greer, Hastings, Kwitt, Roland, Vialard, Francois-Xavier, Estepar, Raul San Jose, Bouix, Sylvain, Rushmore, Richard, Niethammer, Marc
Conventional medical image registration approaches directly optimize over the parameters of a transformation model. These approaches have been highly successful and are used generically for registrations of different anatomical regions. Recent deep r
Externí odkaz:
http://arxiv.org/abs/2403.05780
This work proposes NePhi, a generalizable neural deformation model which results in approximately diffeomorphic transformations. In contrast to the predominant voxel-based transformation fields used in learning-based registration approaches, NePhi re
Externí odkaz:
http://arxiv.org/abs/2309.07322
Autor:
Greer, Hastings, Tian, Lin, Vialard, Francois-Xavier, Kwitt, Roland, Bouix, Sylvain, Estepar, Raul San Jose, Rushmore, Richard, Niethammer, Marc
Inverse consistency is a desirable property for image registration. We propose a simple technique to make a neural registration network inverse consistent by construction, as a consequence of its structure, as long as it parameterizes its output tran
Externí odkaz:
http://arxiv.org/abs/2305.00087
Autor:
Tian, Lin, Greer, Hastings, Vialard, François-Xavier, Kwitt, Roland, Estépar, Raúl San José, Rushmore, Richard Jarrett, Makris, Nikolaos, Bouix, Sylvain, Niethammer, Marc
We present an approach to learning regular spatial transformations between image pairs in the context of medical image registration. Contrary to optimization-based registration techniques and many modern learning-based methods, we do not directly pen
Externí odkaz:
http://arxiv.org/abs/2206.05897
Autor:
Baheti, Bhakti, Chakrabarty, Satrajit, Akbari, Hamed, Bilello, Michel, Wiestler, Benedikt, Schwarting, Julian, Calabrese, Evan, Rudie, Jeffrey, Abidi, Syed, Mousa, Mina, Villanueva-Meyer, Javier, Fields, Brandon K. K., Kofler, Florian, Shinohara, Russell Takeshi, Iglesias, Juan Eugenio, Mok, Tony C. W., Chung, Albert C. S., Wodzinski, Marek, Jurgas, Artur, Marini, Niccolo, Atzori, Manfredo, Muller, Henning, Grobroehmer, Christoph, Siebert, Hanna, Hansen, Lasse, Heinrich, Mattias P., Canalini, Luca, Klein, Jan, Gerken, Annika, Heldmann, Stefan, Hering, Alessa, Hahn, Horst K., Meng, Mingyuan, Bi, Lei, Feng, Dagan, Kim, Jinman, Zeineldin, Ramy A., Karar, Mohamed E., Mathis-Ullrich, Franziska, Burgert, Oliver, Abderezaei, Javid, Pionteck, Aymeric, Chopra, Agamdeep, Kurt, Mehmet, Yan, Kewei, Yan, Yonghong, Tang, Zhe, Ma, Jianqiang, Nasser, Sahar Almahfouz, Kurian, Nikhil Cherian, Meena, Mohit, Shamsi, Saqib, Sethi, Amit, Tustison, Nicholas J., Avants, Brian B., Cook, Philip, Gee, James C., Tian, Lin, Greer, Hastings, Niethammer, Marc, Hoopes, Andrew, Hoffmann, Malte, Dalca, Adrian V., Christodoulidis, Stergios, Estiene, Theo, Vakalopoulou, Maria, Paragios, Nikos, Marcus, Daniel S., Davatzikos, Christos, Sotiras, Aristeidis, Menze, Bjoern, Bakas, Spyridon, Waldmannstetter, Diana
Registration of longitudinal brain MRI scans containing pathologies is challenging due to dramatic changes in tissue appearance. Although there has been progress in developing general-purpose medical image registration techniques, they have not yet a
Externí odkaz:
http://arxiv.org/abs/2112.06979
Learning maps between data samples is fundamental. Applications range from representation learning, image translation and generative modeling, to the estimation of spatial deformations. Such maps relate feature vectors, or map between feature spaces.
Externí odkaz:
http://arxiv.org/abs/2105.04459
Autor:
Bonaretti, Serena, Barzaghi, Leonardo, Barzegari, Mojtaba, Burghardt, Andrew J., Cameron, Donnie, Carballido-Gamio, Julio, Crimi, Gianluigi, Durongbhan, Pholpat, Espinosa Hernandez, Michelle, Fraterrigo, Giulia, Grassi, Lorenzo, Greer, Hastings, Iori, Gianluca, Kuczynski, Michael, Manske, Sarah, McCormick, Matthew, Neeteson, Nathan, Niethammer, Marc, Pani, Martino, Quintiens, Jilmen, Sadeghi, Majid Mohammad, Santini, Francesco, Schileo, Enrico, Stok, Kathryn S., Taddei, Fulvia, Tse, Justin J, Vicory, Jared, Wesseling, Mariska, Wong, Andy Kin On, Zukić, Dženan
Preprint of the manifesto paper of the ORMIR community
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::575422d5c94fe85fdfa9a5258edac188
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Akademický článek
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