Zobrazeno 1 - 10
of 260
pro vyhledávání: '"RaviKumar, Nishant"'
Publikováno v:
Maldonado-Garcia, C., Zakeri, A., Frangi, A.F., Ravikumar, N. (2025). Predictive Intelligence in Medicine. PRIME 2024. LNCS, vol 15155, Springer, Cham
Early identification of patients at risk of cardiovascular diseases (CVD) is crucial for effective preventive care, reducing healthcare burden, and improving patients' quality of life. This study demonstrates the potential of retinal optical coherenc
Externí odkaz:
http://arxiv.org/abs/2410.14423
Computer vision models are increasingly capable of classifying ovarian epithelial cancer subtypes, but they differ from pathologists by processing small tissue patches at a single resolution. Multi-resolution graph models leverage the spatial relatio
Externí odkaz:
http://arxiv.org/abs/2407.18105
Autor:
Breen, Jack, Allen, Katie, Zucker, Kieran, Godson, Lucy, Orsi, Nicolas M., Ravikumar, Nishant
Large pretrained transformers are increasingly being developed as generalised foundation models which can underpin powerful task-specific artificial intelligence models. Histopathology foundation models show great promise across many tasks, but analy
Externí odkaz:
http://arxiv.org/abs/2405.09990
Autor:
Lin, Fengming, Xia, Yan, MacRaild, Michael, Deo, Yash, Dou, Haoran, Liu, Qiongyao, Cheng, Nina, Ravikumar, Nishant, Frangi, Alejandro F.
The automated segmentation of cerebral aneurysms is pivotal for accurate diagnosis and treatment planning. Confronted with significant domain shifts and class imbalance in 3D Rotational Angiography (3DRA) data from various medical institutions, the t
Externí odkaz:
http://arxiv.org/abs/2402.15239
Autor:
Lin, Fengming, Xia, Yan, MacRaild, Michael, Deo, Yash, Dou, Haoran, Liu, Qiongyao, Wu, Kun, Ravikumar, Nishant, Frangi, Alejandro F.
Unsupervised domain adaptation (UDA) aims to align the labelled source distribution with the unlabelled target distribution to obtain domain-invariant predictive models. Since cross-modality medical data exhibit significant intra and inter-domain shi
Externí odkaz:
http://arxiv.org/abs/2402.15237
Autor:
Ibrahim, Mihaela Croitor, Ravikumar, Nishant, Curd, Alistair, Leng, Joanna, Umney, Oliver, Peckham, Michelle
Z-disks are complex structures that delineate repeating sarcomeres in striated muscle. They play significant roles in cardiomyocytes such as providing mechanical stability for the contracting sarcomere, cell signalling and autophagy. Changes in Z-dis
Externí odkaz:
http://arxiv.org/abs/2401.13472
Artificial intelligence has found increasing use for ovarian cancer morphological subtyping from histopathology slides, but the optimal magnification for computational interpretation is unclear. Higher magnifications offer abundant cytological inform
Externí odkaz:
http://arxiv.org/abs/2311.13956
Autor:
Gaggion, Nicolás, Matheson, Benjamin A., Xia, Yan, Bonazzola, Rodrigo, Ravikumar, Nishant, Taylor, Zeike A., Milone, Diego H., Frangi, Alejandro F., Ferrante, Enzo
Cardiovascular magnetic resonance imaging is emerging as a crucial tool to examine cardiac morphology and function. Essential to this endeavour are anatomical 3D surface and volumetric meshes derived from CMR images, which facilitate computational an
Externí odkaz:
http://arxiv.org/abs/2311.13706
Medical image interpretation is central to most clinical applications such as disease diagnosis, treatment planning, and prognostication. In clinical practice, radiologists examine medical images and manually compile their findings into reports, whic
Externí odkaz:
http://arxiv.org/abs/2311.11097
Image-to-text radiology report generation aims to automatically produce radiology reports that describe the findings in medical images. Most existing methods focus solely on the image data, disregarding the other patient information accessible to rad
Externí odkaz:
http://arxiv.org/abs/2311.11090