Abstract Purpose of Review Opportunistic screening is a combination of techniques to
identify subjects of high risk for osteoporotic fracture using routine clinical CT scans …

By leveraging the recent development of artificial intelligence algorithms, several medical
sectors have benefited from using automatic segmentation tools from bioimaging to segment …

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

Background Acute vertebral fracture is usually caused by low-energy injury with
osteoporosis and high-energy trauma. The AOSpine thoracolumbar spine injury …

Purpose To propose a fully automated deep learning (DL) framework for the vertebral
morphometry and Cobb angle measurement from three-dimensional (3D) computed …

High‐precision image segmentation of the spine in computed tomography (CT) images is
important for the diagnosis of spinal diseases and surgical path planning. Manual …

Accurate annotation of vertebral bodies is crucial for automating the analysis of spinal X-ray
images. However, manual annotation of these structures is a laborious and costly process …

Scoliosis is a complicated spinal deformity, and millions of people are suffering from this
disease worldwide. Early detection and accurate scoliosis assessment are vital for effective …

Purpose To summarize and critically evaluate the existing studies for spinopelvic
measurements of sagittal balance that are based on deep learning (DL). Methods Three …

Vertebrae localization, segmentation and identification in CT images is key to numerous
clinical applications. While deep learning strategies have brought to this field significant …