Objective: Explore a new deep learning (DL) object detection algorithm for clinical auxiliary
diagnosis of lumbar spondylolisthesis and compare it with doctors' evaluation to verify the …

Spine is one of the major organs in human body. It consists of multiple vertebrae and inter-
vertebral discs. As the locations and labels of vertebrae provide a vertical reference …

The determination of anatomic landmarks is an essential step in modeling, shape analysis,
segmentation, and registration of the spine, as well as in spine interventions. In this paper …

The knowledge of the location of the centers of vertebral bodies and intervertebral discs is
valuable for the analysis of the spine. Existing methods for the detection and segmentation …

Segmentation of the lumbar spine in 3D is a necessary step in numerous medical
applications, but remains a challenging problem for computational methods due to the …

Objective Deep learning is an advanced machine-learning approach that is used in several
medical fields. Here, we developed a deep learning model using an object detection …

In this paper, a former method has been adapted to perform vertebra segmentations for the
2nd Workshop on Computational Methods and Clinical Applications for Spine Imaging (CSI …

We propose a novel fully automatic approach to localize the lumbar intervertebral discs in
MR images with PHOG based SVM and a probabilistic graphical model. At the local level …

Accurate localization and identification of vertebrae in spinal imaging is crucial for the
clinical tasks of diagnosis, surgical planning, and post-operative assessment. The main …

BACKGROUND CONTEXT: Recent work has yielded a method for automatic labeling of
vertebrae in intraoperative radiographs to assist manual level counting. The method, called …