Deep Learning-Enabled Clinically Applicable CT Planbox for Stroke With High Accuracy and Repeatability.

ABSTRACT:

Background

Computed tomography (CT) plays an essential role in classifying stroke, quantifying penumbra size and supporting stroke-relevant radiomics studies. However, it is difficult to acquire standard, accurate and repeatable images during follow-up. Therefore, we invented an intelligent CT to evaluate stroke during the entire follow-up.

Methods

We deployed a region proposal network (RPN) and V-Net to endow traditional CT with intelligence. Specifically, facial detection was accomplished by identifying adjacent jaw positions through training and testing an RPN on 76,382 human faces using a preinstalled 2-dimensional camera; two regions of interest (ROIs) were segmented by V-Net on another training set with 295 subjects, and the moving distance of scanning couch was calcul

SUBMITTER: Wang Y 

PROVIDER: S-EPMC8961979 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature