Sparse keypoint segmentation of lung fissures: efficient geometric deep learning for abstracting volumetric images.
Journal:
International journal of computer assisted radiology and surgery
PMID:
39775630
Abstract
PURPOSE: Lung fissure segmentation on CT images often relies on 3D convolutional neural networks (CNNs). However, 3D-CNNs are inefficient for detecting thin structures like the fissures, which make up a tiny fraction of the entire image volume. We propose to make lung fissure segmentation more efficient by using geometric deep learning (GDL) on sparse point clouds.