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Classification of Bones

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...

Bone Structure

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.

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Updated: Jun 19, 2026

Three-Dimensional Shape Modeling and Analysis of Brain Structures

Three-Dimensional Shape Modeling and Analysis of Brain Structures

Published on: November 14, 2019

Construction of statistical shape atlases for bone structures based on a two-level framework.

Chenyu Wu¹, Patricia E Murtha, Branislav Jaramaz

¹The Robotics Institute, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, PA 15213, USA. chenyuwu@cmu.edu

The International Journal of Medical Robotics + Computer Assisted Surgery : MRCAS

|October 6, 2009

Summary

This summary is machine-generated.

This study introduces a novel two-level framework and semi-automatic strategy for efficient and accurate statistical shape atlas construction in 3D medical imaging, improving analysis of bone structures.

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Area of Science:

Medical Imaging
Computational Anatomy
Biomedical Engineering

Background:

Statistical shape atlases are crucial for 3D medical image analysis, encoding population shape variations.
Challenges remain in atlas construction regarding efficiency, accuracy, and correspondence.
Existing methods often require prior shape information.

Purpose of the Study:

To develop an efficient and accurate framework for statistical shape atlas construction.
To address limitations in speed, precision, and automation in atlas generation.
To enable atlas creation without prior shape knowledge.

Main Methods:

A two-level framework was developed to accelerate the registration process.
A semi-automatic strategy was proposed for simultaneous segmentation and registration.
The approach does not require prior information about the shape.

Main Results:

Statistical shape atlases were successfully constructed for the femur and spine.
Experimental results validated the efficiency and accuracy of the proposed methods.
The framework demonstrated robust performance on both 3D surface data and DICOM images.

Conclusions:

The two-level framework and semi-automatic strategy enable efficient atlas construction for bone structures.
Accuracy is maintained throughout the atlas generation process.
The method is versatile, handling diverse imaging data types.