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Medical image segmentation review: The success of u-net
Automatic medical image segmentation is a crucial topic in the medical domain and
successively a critical counterpart in the computer-aided diagnosis paradigm. U-Net is the …
successively a critical counterpart in the computer-aided diagnosis paradigm. U-Net is the …
Deep learning approaches for data augmentation in medical imaging: a review
A Kebaili, J Lapuyade-Lahorgue, S Ruan - Journal of imaging, 2023 - mdpi.com
Deep learning has become a popular tool for medical image analysis, but the limited
availability of training data remains a major challenge, particularly in the medical field where …
availability of training data remains a major challenge, particularly in the medical field where …
Ego-exo4d: Understanding skilled human activity from first-and third-person perspectives
Abstract We present Ego-Exo4D a diverse large-scale multimodal multiview video dataset
and benchmark challenge. Ego-Exo4D centers around simultaneously-captured egocentric …
and benchmark challenge. Ego-Exo4D centers around simultaneously-captured egocentric …
Monai: An open-source framework for deep learning in healthcare
MJ Cardoso, W Li, R Brown, N Ma, E Kerfoot… - ar** new medical image
processing algorithms, and deep learning based models have been remarkably successful …
processing algorithms, and deep learning based models have been remarkably successful …
Loss odyssey in medical image segmentation
The loss function is an important component in deep learning-based segmentation methods.
Over the past five years, many loss functions have been proposed for various segmentation …
Over the past five years, many loss functions have been proposed for various segmentation …