A deep-learning system to help make the surgical planning of coil embolization for unruptured intracranial aneurysms.

ABSTRACT:

Background

Coil embolization is a common method for treating unruptured intracranial aneurysms (UIAs). To effectively perform coil embolization for UIAs, clinicians must undergo extensive training with the assistance of senior physicians over an extended period. This study aimed to establish a deep-learning system for measuring the morphological features of UIAs and help the surgical planning of coil embolization for UIAs.

Methods

Preoperative computational tomography angiography (CTA) data and surgical data from UIA patients receiving coil embolization in our medical institution were retrospectively reviewed. A convolutional neural network (CNN) model was trained on the preoperative CTA data, and the morphological features of UIAs were measured automatically using this CNN

SUBMITTER: Nie X 

PROVIDER: S-EPMC10494453 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature