A fast and accurate brain extraction method for CT head images.

ABSTRACT:

Background

Brain extraction is an essential prerequisite for the automated diagnosis of intracranial lesions and determines, to a certain extent, the accuracy of subsequent lesion recognition, location, and segmentation. Segmentation using a fully convolutional neural network (FCN) yields high accuracy but a relatively slow extraction speed.

Methods

This paper proposes an integrated algorithm, FABEM, to address the above issues. This method first uses threshold segmentation, closed operation, convolutional neural network (CNN), and image filling to generate a specific mask. Then, it detects the number of connected regions of the mask. If the number of connected regions equals 1, the extraction is done by directly multiplying with the original image. Otherwise, the mask was f

SUBMITTER: Hu D 

PROVIDER: S-EPMC10498619 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature