An artificial intelligence powered platform for auto-analyses of spine alignment irrespective of image quality with prospective validation.

ABSTRACT:

Background

Assessment of spine alignment is crucial in the management of scoliosis, but current auto-analysis of spine alignment suffers from low accuracy. We aim to develop and validate a hybrid model named SpineHRNet+, which integrates artificial intelligence (AI) and rule-based methods to improve auto-alignment reliability and interpretability.

Methods

From December 2019 to November 2020, 1,542 consecutive patients with scoliosis attending two local scoliosis clinics (The Duchess of Kent Children's Hospital at Sandy Bay in Hong Kong; Queen Mary Hospital in Pok Fu Lam on Hong Kong Island) were recruited. The biplanar radiographs of each patient were collected with our medical machine EOS™. The collected radiographs were recaptured using smartphones or screenshots, with dei

SUBMITTER: Meng N 

PROVIDER: S-EPMC8741432 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature