Deep learning has transformed the segmentation of lung structures in computed tomography by enabling fully automated delineation of lung parenchyma, airways and lobes with high accuracy and efficiency ...

Existing deep learning methods have achieved significant success in medical image segmentation. However, this success largely relies on stacking advanced modules and architectures, which has created a ...

The quest for efficient 3D plant shoot segmentation, vital for extracting plant phenotypic traits, has driven the integration of deep learning with point clouds. Traditional 2D methods, while ...