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Related Concept Videos

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...
Bone Remodeling01:40

Bone Remodeling

Bone remodeling is a continuous and balanced process of bone resorption by osteoclasts and bone formation by osteoblasts. In adults, it helps maintain bone mass and calcium homeostasis. While mechanical stress can stimulate turnover as part of the normal maintenance and reparative process, several hormones also regulate bone remodeling.
Bone Formation by Intramembranous Ossification01:29

Bone Formation by Intramembranous Ossification

Intramembranous ossification is one of the two processes involved in the development of bones within an embryo. The flat bones of the face, most of the cranial bones, and the clavicles are formed via this process. During intramembranous ossification, the bones develop directly from sheets of undifferentiated mesenchymal connective tissue.
The process begins when mesenchymal cells in the embryonic skeleton gather together and differentiate into osteogenic cells, which then develop into...
Bone Disorders01:29

Bone Disorders

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Bone Formation by Endochondral Ossification01:24

Bone Formation by Endochondral Ossification

Bone formation, or ossification, begins around the sixth to seventh week of embryonic development. Most bones develop from a cartilaginous template through the process of endochondral ossification. Cartilage formation begins when clusters of mesenchymal cells differentiate into chondrocytes. These chondrocytes proliferate rapidly and secrete an extracellular matrix that becomes encased in a membrane called the perichondrium. The resulting cartilage model provides a template that resembles the...
Changes in the Appendicular Skeleton with Age01:09

Changes in the Appendicular Skeleton with Age

The upper and lower limb initially develops as a small bulge called a limb bud, which appears on the lateral side of the early embryo. The upper limb bud appears near the end of the fourth week of development, with the lower limb bud appearing shortly after.
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Related Experiment Video

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Automated Joint Space Detection Improves Bone Segmentation Accuracy
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Published on: November 28, 2025

Web-based bone age assessment by content-based image retrieval for case-based reasoning.

Benedikt Fischer1, Petra Welter, Rolf W Günther

  • 1Department of Medical Informatics, RWTH Aachen University, Pauwels str. 30, 52057, Aachen, Germany. bfischer@mi.rwth-aachen.de

International Journal of Computer Assisted Radiology and Surgery
|June 15, 2011
PubMed
Summary
This summary is machine-generated.

Content-based image retrieval (CBIR) supports pediatric radiologists in bone age assessment (BAA) by comparing current cases to similar historical images. This AI-powered tool provides a second opinion, improving diagnostic accuracy for skeletal maturity estimation.

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Area of Science:

  • Radiology
  • Medical Imaging
  • Artificial Intelligence in Medicine

Background:

  • Bone age assessment (BAA) is crucial in pediatric radiology.
  • Current methods include atlas comparison (Greulich and Pyle) or specific bone examination (Tanner and Whitehouse).
  • There is a need for advanced tools to support BAA accuracy and efficiency.

Purpose of the Study:

  • To develop and evaluate a content-based image retrieval (CBIR) system for supporting radiological bone age assessment (BAA).
  • To provide pediatric radiologists with a tool that compares current hand radiographs to a database of similar cases with validated bone ages.

Main Methods:

  • A web-based prototype CBIR system was developed for BAA.
  • The system uses cross-correlation to find the ten most similar cases from the USC hand database (1,101 cases) for each epiphysis.
  • Epiphyseal centers were marked in the USC image data for enhanced retrieval.

Main Results:

  • Leave-one-out experiments demonstrated a mean error rate of 0.99 years (SD 0.76 years) compared to the mean USC-BAA.
  • The prototype allows radiologists to assess agreement based on retrieved case similarity and derived age estimates.

Conclusions:

  • CBIR offers a valuable second opinion for radiologists performing BAA.
  • Web applications integrating CBIR can enhance radiologist workflow.
  • Future improvements in similarity computation and interface usability are recommended.