CarveMix: A Data Augmentation Technique for Brain Lesion Segmentation from China

In this paper, the authors describe a new approach called CarveMix, which was proposed as a data augmentation technique for brain lesion segmentation. They use a set of 3D annotated images with brain lesions to train a neural network to analyze brain tissue. The goal of the study is to evaluate the performance of this new approach, which is more accurate and better performs than other approaches based on image-sending and convolutional recognition.CarveMix works well in both naturalistic and artificial intelligence experiments and demonstrates that it can be used to improve the sensitivity and accuracy of neural networks designed for tasks involving brain injuries.The authors present the results of four brain segmentation tasks using CarVEMix and show that the approach improves accuracy and outperforms other approaches

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Automated brain lesion segmentation #CarveMix #simple and effective data augmentation approach