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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...

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Related Experiment Video

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Detecting pediatric wrist fractures using deep-learning-based object detection.

John R Zech¹, Giuseppe Carotenuto², Zenas Igbinoba³

¹Department of Radiology, Columbia University Irving Medical Center/New York Presbyterian Hospital, 622 W 168th St., New York, NY, 10032, USA. jrz2111@columbia.edu.

Pediatric Radiology

|January 17, 2023

Summary

This summary is machine-generated.

Deep learning accurately detects pediatric wrist fractures, including subtle buckle fractures. AI assistance significantly improved trainee radiograph interpretation accuracy for these fractures.

Keywords:

Artificial intelligence Bone Buckle fracture Children Convolutional neural network Deep learning Radiography Wrist

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Area of Science:

Radiology
Artificial Intelligence
Medical Imaging

Background:

Missed fractures are a leading cause of diagnostic errors in emergency departments.
Subtle pediatric wrist fractures are particularly challenging to identify on radiographs.

Purpose of the Study:

Evaluate a deep learning framework for classifying pediatric wrist fractures.
Assess the AI's performance in augmenting trainee radiograph interpretation.

Main Methods:

A Faster R-CNN deep learning model was trained on 395 pediatric wrist radiographs.
Trainee radiologists interpreted radiographs with and without AI assistance.

Main Results:

The AI model achieved 88% accuracy and 0.92 AUC in detecting fractures.
AI assistance improved resident accuracy from 80% to 93% for all fractures and 69% to 92% for buckle fractures.

Conclusions:

Deep learning effectively identifies pediatric wrist fractures, even subtle ones.
AI significantly enhances diagnostic accuracy for trainees interpreting pediatric wrist radiographs.