In this work we propose to use Deep Learning to automatically calculate the coordinates of
the vertebral corners in sagittal x-rays images of the thoracolumbar spine and, from those …

Human spinal balance assessment relies considerably on sagittal radiographic parameter
measurement. Deep learning could be applied for automatic landmark detection and …

Purpose We present an automated method for extracting anatomical parameters from
biplanar radiographs of the spine, which is able to deal with a wide scenario of conditions …

Purpose Artificial intelligence based on deep learning (DL) approaches enables the
automatic recognition of anatomic landmarks and subsequent estimation of various …

Background Adolescent idiopathic scoliosis (AIS) is the most common type of spinal disorder
affecting children. Clinical screening and diagnosis require physical and radiographic …

Purpose To construct and evaluate the efficacy of a deep learning system to rapidly and
automatically locate six vertebral landmarks, which are used to measure vertebral body …

Vertebral landmarks of posterior-anterior X-ray images can be used to determine the
curvature of the spine, which is essential for the assessment of Adolescent Idiopathic …

With the prevalence of degenerative diseases due to the increase in the aging population,
we have encountered many spine-related disorders. Since the spine is a crucial part of the …

Accurate localization and identification of vertebrae in 3D spinal images is essential for
many clinical tasks. However, automatic localization and identification of vertebrae remains …

Motivation/Purpose: This work reports the development and validation of an algorithm to
automatically detect and localize vertebrae in CT images of patients undergoing spine …