Rationale and Objectives The automated segmentation of organs and tissues throughout the
body using computed tomography and magnetic resonance imaging has been rapidly …

CT vertebral segmentation plays an essential role in various clinical applications, such as
computer‐assisted surgical interventions, assessment of spinal abnormalities, and vertebral …

This article aims to present a review of the segmentation techniques of the 3D data
representing human body in the form of point clouds. The techniques discussed are divided …

Vertebral labelling and segmentation are two fundamental tasks in an automated spine
processing pipeline. Reliable and accurate processing of spine images is expected to …

Robust and fast detection of anatomical structures is a prerequisite for both diagnostic and
interventional medical image analysis. Current solutions for anatomy detection are typically …

Precise segmentation and anatomical identification of the vertebrae provides the basis for
automatic analysis of the spine, such as detection of vertebral compression fractures or other …

In this paper, we introduce a simple, yet powerful pipeline for medical image segmentation
that combines Fully Convolutional Networks (FCNs) with Fully Convolutional Residual …

Accurate vertebrae segmentation from medical images plays an important role in clinical
tasks of surgical planning, diagnosis, kyphosis, scoliosis, degenerative disc disease …

Localization and segmentation of vertebral bodies from spine CT volumes are crucial for
pathological diagnosis, surgical planning, and postoperative assessment. However, fully …

Objective Osteoporosis is a prevalent and treatable condition, but it remains
underdiagnosed. In this study, a deep learning-based system was developed to …