Medical image segmentation review: The success of u-net

R Azad, EK Aghdam, A Rauland, Y Jia… - … on Pattern Analysis …, 2024 - ieeexplore.ieee.org
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 …

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 …

Ego-exo4d: Understanding skilled human activity from first-and third-person perspectives

K Grauman, A Westbury, L Torresani… - Proceedings of the …, 2024 - openaccess.thecvf.com
Abstract We present Ego-Exo4D a diverse large-scale multimodal multiview video dataset
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 …

Loss odyssey in medical image segmentation

J Ma, J Chen, M Ng, R Huang, Y Li, C Li, X Yang… - Medical image …, 2021 - Elsevier
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 …