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Related Concept Videos

General Structure of a Vertebra01:30

General Structure of a Vertebra

A typical vertebra, with the exception of the sacrum and coccyx, consists of a body, a vertebral arch, and seven different projections termed processes. The anterior portion of the vertebrae, the body, supports about half the body’s weight. The vertebral bodies progressively increase in size and thickness from the cervical region to the lumbar region of the vertebral column. The intervertebral discs present between the bodies of adjacent vertebrae firmly unites them, forming a continuous column.
Vertebral Column: Regions and Curvature01:16

Vertebral Column: Regions and Curvature

The vertebral column or spine is a flexible column that supports the head, neck, and body and  allows for their movements. It also protects the spinal cord.
Regions of the Vertebral Column
In an adult, the spine is subdivided into five regions: the cervical, the thoracic, the lumbar, the sacral, and the coccygeal region. The spine initially develops as a series of 33 vertebrae; after 20 years of age, the nine bones in the sacral region, five sacral, and four coccygeal bones fuse to form the...
Classification of Bones01:18

Classification of Bones

The bones of the human skeletal system are of varied shapes, sizes, and functions. They can be classified based on their shape and function into four major classes: long bones, short bones, flat bones, and irregular bones. Some classifications include a fifth type, the sesamoid bones, as a separate class, whereas others categorize them under short bones.
Long and Short Bones
The appendicular skeleton, particularly the upper and lower limbs, is primarily made of long and short bones. The long...
Structural Classification of Joints01:20

Structural Classification of Joints

Joints, also known as articulations, are classified based on their structural characteristics, i.e., based on whether the articulating surfaces of the adjacent bones are directly connected by fibrous connective tissue or cartilage, or whether the articulating surfaces contact each other within a fluid-filled joint cavity. These differences serve to divide the joints of the body into three structural classifications.
A fibrous joint is where the adjacent bones are united by fibrous connective...
Bone Structure01:55

Bone Structure

Within the skeletal system, the structure of a bone, or osseous tissue, can be exemplified in a long bone, like the femur, where there are two types of osseous tissue: cortical and cancellous.
Articulations of the Vertebral Column01:28

Articulations of the Vertebral Column

In addition to being held together by the intervertebral discs, adjacent vertebrae also articulate with each other at synovial joints formed between the superior and inferior articular processes called zygapophysial joints (facet joints). These are plane joints that provide for only limited motions between the vertebrae. The orientation of the articular processes at these joints varies in different regions of the vertebral column and serves to determine the types of motions available in each...

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Related Experiment Video

Updated: May 28, 2026

Precision Measurements and Parametric Models of Vertebral Endplates
10:35

Precision Measurements and Parametric Models of Vertebral Endplates

Published on: September 17, 2019

Automatic construction of statistical shape models for vertebrae.

Meike Becker1, Matthias Kirschner, Simon Fuhrmann

  • 1GRIS, TU Darmstadt, Fraunhoferstrasse 5, 64287 Darmstadt, Germany. meike.becker@gris.tu-darmstadt.de

Medical Image Computing and Computer-Assisted Intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
|October 15, 2011
PubMed
Summary
This summary is machine-generated.

This study presents an automated method for solving the correspondence problem in statistical shape models (SSMs) for vertebrae segmentation. The approach improves SSM quality compared to the ICP method.

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Three-Dimensional Shape Modeling and Analysis of Brain Structures
05:33

Three-Dimensional Shape Modeling and Analysis of Brain Structures

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Last Updated: May 28, 2026

Precision Measurements and Parametric Models of Vertebral Endplates
10:35

Precision Measurements and Parametric Models of Vertebral Endplates

Published on: September 17, 2019

Three-Dimensional Shape Modeling and Analysis of Brain Structures
05:33

Three-Dimensional Shape Modeling and Analysis of Brain Structures

Published on: November 14, 2019

Area of Science:

  • Medical imaging
  • Computer-aided diagnosis
  • Biomedical engineering

Background:

  • Statistical shape models (SSMs) are crucial for segmenting complex anatomical structures like vertebrae.
  • A significant challenge in using SSMs is establishing accurate correspondences between shapes.
  • Existing methods often struggle with the complexity of vertebral anatomy.

Purpose of the Study:

  • To develop a generic, automated approach for solving the correspondence problem in vertebrae segmentation using SSMs.
  • To improve the quality and accuracy of SSMs for complex anatomical structures.
  • To overcome limitations of current correspondence methods.

Main Methods:

  • A novel method involving defining closed loops on a reference vertebra and propagating them to a training set.
  • Parameterizing shapes to rectangles after cutting along these loops.
  • Optimizing a combined energy function to establish correspondences and minimize geometric distortion.
  • Implementing an adaptive resampling technique for enhanced shape representation.

Main Results:

  • The proposed method successfully establishes correspondences for vertebrae.
  • It significantly reduces area and angle distortion compared to traditional approaches.
  • Generated SSMs demonstrate higher quality than those produced by the Iterative Closest Point (ICP) algorithm.
  • Qualitative and quantitative evaluations confirm the method's effectiveness.

Conclusions:

  • The developed automated approach effectively solves the correspondence problem for vertebrae in SSMs.
  • This method enhances the quality of SSMs, leading to more accurate segmentation.
  • It offers a robust alternative to existing methods like ICP for complex shape analysis.