There is an expanding body of literature that describes the application of deep learning and
other machine learning and artificial intelligence methods with potential relevance to …

The purpose of this article is to present diagnostic methods used in the diagnosis of scoliosis
in the form of a brief review. This article aims to point out the advantages of select methods …

Automatic vertebral body contour extraction (AVBCE) from heterogeneous spinal MRI is
indispensable for the comprehensive diagnosis and treatment of spinal diseases. However …

The accuracy of the Cobb measurement is essential for the diagnosis and treatment of
scoliosis. Manual measurement is however influenced by the observer variability hence …

Scoliosis diagnosis and assessment rely upon Cobb angle estimation from X-ray images of
the spine. Recently, automated scoliosis assessment has been greatly improved using deep …

Visual assessment based on intraoperative 2D X-rays remains the predominant aid for
intraoperative decision-making, surgical guidance, and error prevention. However, correctly …

Objectives To develop a deep learning algorithm to automatically evaluate and diagnose
scoliosis on full spinal X-ray images. Methods This retrospective study collected full spinal X …

Scoliosis is a three-dimensional deformity of lateral bending and rotation of the spine.
Artificial intelligence (AI) is a set of theories and techniques for studying artificial intelligence …

Automated Cobb angle estimation on X-ray images is crucial to scoliosis diagnosis. The
existing efforts are typically two extremes, which either laboriously detect the raw vertebral …

Patch-based medical image registration has been well explored in recent decades.
However, the patch fusion process can generate grid-like artifacts along the edge of patches …