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Updated: Dec 25, 2025

Real-time Monitoring of High Intensity Focused Ultrasound HIFU Ablation of In Vitro Canine Livers Using Harmonic Motion Imaging for Focused Ultrasound HMIFU

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Real-time Burn Classification using Ultrasound Imaging.

Sangrock Lee¹, Rahul¹, Hanglin Ye¹

¹Center for Modeling, Simulation and Imaging in Medicine, Rensselaer Polytechnic Institute, Troy, NY, USA.

Scientific Reports

|April 4, 2020

Summary

This study introduces a real-time ultrasound imaging method for classifying burn depth. It achieves high accuracy in distinguishing burn severity using texture analysis, aiding clinical burn assessment.

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Area of Science:

Biomedical Engineering
Medical Imaging
Dermatology

Background:

Accurate burn depth classification is crucial for effective treatment and prognosis.
Distinguishing between superficial and deep second-degree burns remains a clinical challenge.

Purpose of the Study:

To develop and validate a real-time, non-invasive method for burn depth classification using B-mode ultrasound imaging.
To assess the efficacy of texture analysis derived from ultrasound images for burn severity assessment.

Main Methods:

Utilized B-mode ultrasound imaging of ex vivo porcine skin tissue subjected to controlled thermal injury.
Computed Grey-Level Co-occurrence Matrix (GLCM) to extract textural features from ultrasound images.
Employed nonlinear Support Vector Machine (SVM) and Kernel Fisher Discriminant Analysis (KFDA) for classification.
Validated the classification model using leave-one-out cross-validation.

Main Results:

Achieved an average pairwise classification accuracy of 99% for differentiating four burn conditions.
Attained an average multiclass classification accuracy of 93% for burn depth assessment.
Demonstrated accurate tissue characteristic assessment with moderate sample sizes.

Conclusions:

The proposed ultrasound imaging and GLCM texture feature approach offers a promising tool for real-time burn depth classification.
This method has the potential to significantly aid clinicians in accurately assessing burn severity, especially in differentiating challenging cases like superficial versus deep second-degree burns.