Zobrazeno 1 - 10
of 67
pro vyhledávání: '"Starmans, Martijn P. A."'
Autor:
Spaanderman, Douwe J., Marzetti, Matthew, Wan, Xinyi, Scarsbrook, Andrew F., Robinson, Philip, Oei, Edwin H. G., Visser, Jacob J., Hemke, Robert, van Langevelde, Kirsten, Hanff, David F., van Leenders, Geert J. L. H., Verhoef, Cornelis, Gruühagen, Dirk J., Niessen, Wiro J., Klein, Stefan, Starmans, Martijn P. A.
Soft-tissue and bone tumours (STBT) are rare, diagnostically challenging lesions with variable clinical behaviours and treatment approaches. This systematic review provides an overview of Artificial Intelligence (AI) methods using radiological imagin
Externí odkaz:
http://arxiv.org/abs/2408.12491
Autor:
Garrucho, Lidia, Reidel, Claire-Anne, Kushibar, Kaisar, Joshi, Smriti, Osuala, Richard, Tsirikoglou, Apostolia, Bobowicz, Maciej, del Riego, Javier, Catanese, Alessandro, Gwoździewicz, Katarzyna, Cosaka, Maria-Laura, Abo-Elhoda, Pasant M., Tantawy, Sara W., Sakrana, Shorouq S., Shawky-Abdelfatah, Norhan O., Abdo-Salem, Amr Muhammad, Kozana, Androniki, Divjak, Eugen, Ivanac, Gordana, Nikiforaki, Katerina, Klontzas, Michail E., García-Dosdá, Rosa, Gulsun-Akpinar, Meltem, Lafcı, Oğuz, Mann, Ritse, Martín-Isla, Carlos, Prior, Fred, Marias, Kostas, Starmans, Martijn P. A., Strand, Fredrik, Díaz, Oliver, Igual, Laura, Lekadir, Karim
Current research in breast cancer Magnetic Resonance Imaging (MRI), especially with Artificial Intelligence (AI), faces challenges due to the lack of expert segmentations. To address this, we introduce the MAMA-MIA dataset, comprising 1506 multi-cent
Externí odkaz:
http://arxiv.org/abs/2406.13844
Autor:
Spaanderman, Douwe J., Starmans, Martijn P. A., van Erp, Gonnie C. M., Hanff, David F., Sluijter, Judith H., Schut, Anne-Rose W., van Leenders, Geert J. L. H., Verhoef, Cornelis, Grunhagen, Dirk J., Niessen, Wiro J., Visser, Jacob J., Klein, Stefan
Segmentations are crucial in medical imaging to obtain morphological, volumetric, and radiomics biomarkers. Manual segmentation is accurate but not feasible in the radiologist's clinical workflow, while automatic segmentation generally obtains sub-pa
Externí odkaz:
http://arxiv.org/abs/2402.07746
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:
Starmans, Martijn P. A., van der Voort, Sebastian R., Phil, Thomas, Timbergen, Milea J. M., Vos, Melissa, Padmos, Guillaume A., Kessels, Wouter, Hanff, David, Grunhagen, Dirk J., Verhoef, Cornelis, Sleijfer, Stefan, Bent, Martin J. van den, Smits, Marion, Dwarkasing, Roy S., Els, Christopher J., Fiduzi, Federico, van Leenders, Geert J. L. H., Blazevic, Anela, Hofland, Johannes, Brabander, Tessa, van Gils, Renza A. H., Franssen, Gaston J. H., Feelders, Richard A., de Herder, Wouter W., Buisman, Florian E., Willemssen, Francois E. J. A., Koerkamp, Bas Groot, Angus, Lindsay, van der Veldt, Astrid A. M., Rajicic, Ana, Odink, Arlette E., Deen, Mitchell, T., Jose M. Castillo, Veenland, Jifke, Schoots, Ivo, Renckens, Michel, Doukas, Michail, de Man, Rob A., IJzermans, Jan N. M., Miclea, Razvan L., Vermeulen, Peter B., Bron, Esther E., Thomeer, Maarten G., Visser, Jacob J., Niessen, Wiro J., Klein, Stefan
Radiomics uses quantitative medical imaging features to predict clinical outcomes. Currently, in a new clinical application, finding the optimal radiomics method out of the wide range of available options has to be done manually through a heuristic t
Externí odkaz:
http://arxiv.org/abs/2108.08618
Autor:
Starmans, Martijn P. A., Timbergen, Milea J. M., Vos, Melissa, Renckens, Michel, Grünhagen, Dirk J., van Leenders, Geert J. L. H., Dwarkasing, Roy S., Willemssen, François E. J. A., Niessen, Wiro J., Verhoef, Cornelis, Sleijfer, Stefan, Visser, Jacob J., Klein, Stefan
Publikováno v:
J Digit Imaging (2022)
Distinguishing gastrointestinal stromal tumors (GISTs) from other intra-abdominal tumors and GISTs molecular analysis is necessary for treatment planning, but challenging due to its rarity. The aim of this study was to evaluate radiomics for distingu
Externí odkaz:
http://arxiv.org/abs/2010.06824
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