Zobrazeno 1 - 10
of 2 551
pro vyhledávání: '"A. M. Jorge"'
Autor:
Christodoulou, Evangelia, Reinke, Annika, Houhou, Rola, Kalinowski, Piotr, Erkan, Selen, Sudre, Carole H., Burgos, Ninon, Boutaj, Sofiène, Loizillon, Sophie, Solal, Maëlys, Rieke, Nicola, Cheplygina, Veronika, Antonelli, Michela, Mayer, Leon D., Tizabi, Minu D., Cardoso, M. Jorge, Simpson, Amber, Jäger, Paul F., Kopp-Schneider, Annette, Varoquaux, Gaël, Colliot, Olivier, Maier-Hein, Lena
Medical imaging is spearheading the AI transformation of healthcare. Performance reporting is key to determine which methods should be translated into clinical practice. Frequently, broad conclusions are simply derived from mean performance values. I
Externí odkaz:
http://arxiv.org/abs/2409.17763
Autor:
Tangwiriyasakul, Chayanin, Borges, Pedro, Moriconi, Stefano, Wright, Paul, Mah, Yee-Haur, Teo, James, Nachev, Parashkev, Ourselin, Sebastien, Cardoso, M. Jorge
Stroke is a leading cause of disability and death. Effective treatment decisions require early and informative vascular imaging. 4D perfusion imaging is ideal but rarely available within the first hour after stroke, whereas plain CT and CTA usually a
Externí odkaz:
http://arxiv.org/abs/2404.04025
Cortical surface analysis has gained increased prominence, given its potential implications for neurological and developmental disorders. Traditional vision diffusion models, while effective in generating natural images, present limitations in captur
Externí odkaz:
http://arxiv.org/abs/2402.04753
Autor:
D. M. S. Bosco, C. Andrighetto, P. A. C. Luz, M. L. Poiatti, A. M. Jorge, C. L. Francisco, H. S. Aranha, G. A. Trivelin, R. F. Vaz, J. M. F. Santos
Publikováno v:
Boletim de Indústria Animal, Vol 73, Iss 4, Pp 304-309 (2016)
The objective of this study was to evaluate the physical and microbiological characteristics of aged and tenderized beef commercialized in the Dracena region, SP. Eight samples of aged meat and eight samples of tenderized meat were randomly purchased
Externí odkaz:
https://doaj.org/article/794adf48efc84c129a4ebe787b367ef7
Autor:
Cardoso, M. Jorge, Moosbauer, Julia, Cook, Tessa S., Erdal, B. Selnur, Genereaux, Brad, Gupta, Vikash, Landman, Bennett A., Lee, Tiarna, Nachev, Parashkev, Somasundaram, Elanchezhian, Summers, Ronald M., Younis, Khaled, Ourselin, Sebastien, Pfister, Franz MJ
The integration of AI into radiology introduces opportunities for improved clinical care provision and efficiency but it demands a meticulous approach to mitigate potential risks as with any other new technology. Beginning with rigorous pre-deploymen
Externí odkaz:
http://arxiv.org/abs/2311.14570
Autor:
Fernandez, Virginia, Pinaya, Walter Hugo Lopez, Borges, Pedro, Graham, Mark S., Vercauteren, Tom, Cardoso, M. Jorge
Generative modelling and synthetic data can be a surrogate for real medical imaging datasets, whose scarcity and difficulty to share can be a nuisance when delivering accurate deep learning models for healthcare applications. In recent years, there h
Externí odkaz:
http://arxiv.org/abs/2311.04552
Autor:
Wang, Jueqi, Levman, Jacob, Pinaya, Walter Hugo Lopez, Tudosiu, Petru-Daniel, Cardoso, M. Jorge, Marinescu, Razvan
High-resolution (HR) MRI scans obtained from research-grade medical centers provide precise information about imaged tissues. However, routine clinical MRI scans are typically in low-resolution (LR) and vary greatly in contrast and spatial resolution
Externí odkaz:
http://arxiv.org/abs/2308.12465
Autor:
Lekadir, Karim, Feragen, Aasa, Fofanah, Abdul Joseph, Frangi, Alejandro F, Buyx, Alena, Emelie, Anais, Lara, Andrea, Porras, Antonio R, Chan, An-Wen, Navarro, Arcadi, Glocker, Ben, Botwe, Benard O, Khanal, Bishesh, Beger, Brigit, Wu, Carol C, Cintas, Celia, Langlotz, Curtis P, Rueckert, Daniel, Mzurikwao, Deogratias, Fotiadis, Dimitrios I, Zhussupov, Doszhan, Ferrante, Enzo, Meijering, Erik, Weicken, Eva, González, Fabio A, Asselbergs, Folkert W, Prior, Fred, Krestin, Gabriel P, Collins, Gary, Tegenaw, Geletaw S, Kaissis, Georgios, Misuraca, Gianluca, Tsakou, Gianna, Dwivedi, Girish, Kondylakis, Haridimos, Jayakody, Harsha, Woodruf, Henry C, Mayer, Horst Joachim, Aerts, Hugo JWL, Walsh, Ian, Chouvarda, Ioanna, Buvat, Irène, Tributsch, Isabell, Rekik, Islem, Duncan, James, Kalpathy-Cramer, Jayashree, Zahir, Jihad, Park, Jinah, Mongan, John, Gichoya, Judy W, Schnabel, Julia A, Kushibar, Kaisar, Riklund, Katrine, Mori, Kensaku, Marias, Kostas, Amugongo, Lameck M, Fromont, Lauren A, Maier-Hein, Lena, Alberich, Leonor Cerdá, Rittner, Leticia, Phiri, Lighton, Marrakchi-Kacem, Linda, Donoso-Bach, Lluís, Martí-Bonmatí, Luis, Cardoso, M Jorge, Bobowicz, Maciej, Shabani, Mahsa, Tsiknakis, Manolis, Zuluaga, Maria A, Bielikova, Maria, Fritzsche, Marie-Christine, Camacho, Marina, Linguraru, Marius George, Wenzel, Markus, De Bruijne, Marleen, Tolsgaard, Martin G, Ghassemi, Marzyeh, Ashrafuzzaman, Md, Goisauf, Melanie, Yaqub, Mohammad, Abadía, Mónica Cano, Mahmoud, Mukhtar M E, Elattar, Mustafa, Rieke, Nicola, Papanikolaou, Nikolaos, Lazrak, Noussair, Díaz, Oliver, Salvado, Olivier, Pujol, Oriol, Sall, Ousmane, Guevara, Pamela, Gordebeke, Peter, Lambin, Philippe, Brown, Pieta, Abolmaesumi, Purang, Dou, Qi, Lu, Qinghua, Osuala, Richard, Nakasi, Rose, Zhou, S Kevin, Napel, Sandy, Colantonio, Sara, Albarqouni, Shadi, Joshi, Smriti, Carter, Stacy, Klein, Stefan, Petersen, Steffen E, Aussó, Susanna, Awate, Suyash, Raviv, Tammy Riklin, Cook, Tessa, Mutsvangwa, Tinashe E M, Rogers, Wendy A, Niessen, Wiro J, Puig-Bosch, Xènia, Zeng, Yi, Mohammed, Yunusa G, Aquino, Yves Saint James, Salahuddin, Zohaib, Starmans, Martijn P A
Despite major advances in artificial intelligence (AI) for medicine and healthcare, the deployment and adoption of AI technologies remain limited in real-world clinical practice. In recent years, concerns have been raised about the technical, clinica
Externí odkaz:
http://arxiv.org/abs/2309.12325
Autor:
Pinaya, Walter H. L., Graham, Mark S., Kerfoot, Eric, Tudosiu, Petru-Daniel, Dafflon, Jessica, Fernandez, Virginia, Sanchez, Pedro, Wolleb, Julia, da Costa, Pedro F., Patel, Ashay, Chung, Hyungjin, Zhao, Can, Peng, Wei, Liu, Zelong, Mei, Xueyan, Lucena, Oeslle, Ye, Jong Chul, Tsaftaris, Sotirios A., Dogra, Prerna, Feng, Andrew, Modat, Marc, Nachev, Parashkev, Ourselin, Sebastien, Cardoso, M. Jorge
Recent advances in generative AI have brought incredible breakthroughs in several areas, including medical imaging. These generative models have tremendous potential not only to help safely share medical data via synthetic datasets but also to perfor
Externí odkaz:
http://arxiv.org/abs/2307.15208
Autor:
Graham, Mark S., Pinaya, Walter Hugo Lopez, Wright, Paul, Tudosiu, Petru-Daniel, Mah, Yee H., Teo, James T., Jäger, H. Rolf, Werring, David, Nachev, Parashkev, Ourselin, Sebastien, Cardoso, M. Jorge
Methods for out-of-distribution (OOD) detection that scale to 3D data are crucial components of any real-world clinical deep learning system. Classic denoising diffusion probabilistic models (DDPMs) have been recently proposed as a robust way to perf
Externí odkaz:
http://arxiv.org/abs/2307.03777