Zobrazeno 1 - 10
of 312
pro vyhledávání: '"Bron, Esther"'
Autor:
Mateus, Pedro, Garst, Swier, Yu, Jing, Cats, Davy, Harms, Alexander G. J., Birhanu, Mahlet, Beekman, Marian, Slagboom, P. Eline, Reinders, Marcel, van der Grond, Jeroen, Dekker, Andre, Jansen, Jacobus F. A., Beran, Magdalena, Schram, Miranda T., Visser, Pieter Jelle, Moonen, Justine, Ghanbari, Mohsen, Roshchupkin, Gennady, Vojinovic, Dina, Bermejo, Inigo, Mei, Hailiang, Bron, Esther E.
Biological age scores are an emerging tool to characterize aging by estimating chronological age based on physiological biomarkers. Various scores have shown associations with aging-related outcomes. This study assessed the relation between an age sc
Externí odkaz:
http://arxiv.org/abs/2409.01235
Deep learning has achieved impressive performance across various medical imaging tasks. However, its inherent bias against specific groups hinders its clinical applicability in equitable healthcare systems. A recently discovered phenomenon, Neural Co
Externí odkaz:
http://arxiv.org/abs/2407.05843
AI-based association analysis for medical imaging using latent-space geometric confounder correction
Autor:
Liu, Xianjing, Li, Bo, Vernooij, Meike W., Wolvius, Eppo B., Roshchupkin, Gennady V., Bron, Esther E.
AI has greatly enhanced medical image analysis, yet its use in epidemiological population imaging studies remains limited due to visualization challenges in non-linear models and lack of confounder control. Addressing this, we introduce an AI method
Externí odkaz:
http://arxiv.org/abs/2311.12836
Autor:
Kang, Wenjie, Li, Bo, Papma, Janne M., Jiskoot, Lize C., De Deyn, Peter Paul, Biessels, Geert Jan, Claassen, Jurgen A. H. R., Middelkoop, Huub A. M., van der Flier, Wiesje M., Ramakers, Inez H. G. B., Klein, Stefan, Bron, Esther E.
Machine learning methods have shown large potential for the automatic early diagnosis of Alzheimer's Disease (AD). However, some machine learning methods based on imaging data have poor interpretability because it is usually unclear how they make the
Externí odkaz:
http://arxiv.org/abs/2308.07778
Autor:
Li, Bo, de Bresser, Jeroen, Niessen, Wiro, van Osch, Matthias, van der Flier, Wiesje M., Biessels, Geert Jan, Vernooij, Meike W., Bron, Esther
Lacunes of presumed vascular origin, also referred to as lacunar infarcts, are important to assess cerebral small vessel disease and cognitive diseases such as dementia. However, visual rating of lacunes from imaging data is challenging, time-consumi
Externí odkaz:
http://arxiv.org/abs/2306.10622
Autor:
Hammecher, Claudia Chinea, van Garderen, Karin, Smits, Marion, Wesseling, Pieter, Westerman, Bart, French, Pim, Kouwenhoven, Mathilde, Verhaak, Roel, Vos, Frans, Bron, Esther, Li, Bo
Glioma growth may be quantified with longitudinal image registration. However, the large mass-effects and tissue changes across images pose an added challenge. Here, we propose a longitudinal, learning-based, and groupwise registration method for the
Externí odkaz:
http://arxiv.org/abs/2306.10611
Autor:
Sudre, Carole H., Van Wijnen, Kimberlin, Dubost, Florian, Adams, Hieab, Atkinson, David, Barkhof, Frederik, Birhanu, Mahlet A., Bron, Esther E., Camarasa, Robin, Chaturvedi, Nish, Chen, Yuan, Chen, Zihao, Chen, Shuai, Dou, Qi, Evans, Tavia, Ezhov, Ivan, Gao, Haojun, Sanguesa, Marta Girones, Gispert, Juan Domingo, Anson, Beatriz Gomez, Hughes, Alun D., Ikram, M. Arfan, Ingala, Silvia, Jaeger, H. Rolf, Kofler, Florian, Kuijf, Hugo J., Kutnar, Denis, Lee, Minho, Li, Bo, Lorenzini, Luigi, Menze, Bjoern, Molinuevo, Jose Luis, Pan, Yiwei, Puybareau, Elodie, Rehwald, Rafael, Su, Ruisheng, Shi, Pengcheng, Smith, Lorna, Tillin, Therese, Tochon, Guillaume, Urien, Helene, van der Velden, Bas H. M., van der Velpen, Isabelle F., Wiestler, Benedikt, Wolters, Frank J., Yilmaz, Pinar, de Groot, Marius, Vernooij, Meike W., de Bruijne, Marleen
Imaging markers of cerebral small vessel disease provide valuable information on brain health, but their manual assessment is time-consuming and hampered by substantial intra- and interrater variability. Automated rating may benefit biomedical resear
Externí odkaz:
http://arxiv.org/abs/2208.07167
Autor:
Venkatraghavan, Vikram, van der Voort, Sebastian R., Bos, Daniel, Smits, Marion, Barkhof, Frederik, Niessen, Wiro J., Klein, Stefan, Bron, Esther E.
Computer-aided methods have shown added value for diagnosing and predicting brain disorders and can thus support decision making in clinical care and treatment planning. This chapter will provide insight into the type of methods, their working, their
Externí odkaz:
http://arxiv.org/abs/2206.14683
Autor:
Kuipers, Sanne, Kappelle, L. Jaap, Greving, Jacoba P., Amier, Raquel P., de Bresser, Jeroen, Bron, Esther E., Leeuwis, Anna E., Marcks, Nick, den Ruijter, Hester M., Biessels, Geert Jan, Exalto, Lieza G.
Publikováno v:
In International Journal of Cardiology 1 January 2025 418
Autor:
Bron, Esther E., Klein, Stefan, Reinke, Annika, Papma, Janne M., Maier-Hein, Lena, Alexander, Daniel C., Oxtoby, Neil P.
Machine learning methods exploiting multi-parametric biomarkers, especially based on neuroimaging, have huge potential to improve early diagnosis of dementia and to predict which individuals are at-risk of developing dementia. To benchmark algorithms
Externí odkaz:
http://arxiv.org/abs/2112.07922