3D Deep Learning Angiography (3D-DLA) from C-arm Conebeam CT.

ABSTRACT:

Background and purpose

Deep learning is a branch of artificial intelligence that has demonstrated unprecedented performance in many medical imaging applications. Our purpose was to develop a deep learning angiography method to generate 3D cerebral angiograms from a single contrast-enhanced C-arm conebeam CT acquisition in order to reduce image artifacts and radiation dose.

Materials and methods

A set of 105 3D rotational angiography examinations were randomly selected from an internal data base. All were acquired using a clinical system in conjunction with a standard injection protocol. More than 150 million labeled voxels from 35 subjects were used for training. A deep convolutional neural network was trained to classify each image voxel into 3 tissue types (vasculature, bo

SUBMITTER: Montoya JC 

PROVIDER: S-EPMC6758552 | biostudies-literature | 2018 May

REPOSITORIES: biostudies-literature