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Updated: May 10, 2025

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Attention-aware Deep Learning Models for Dermoscopic Image Classification for Skin Disease Diagnosis.

Malliga Subramanian1, Kogilavani Shanmugavadivel2, Sudha Thangaraj1

  • 1Department of Computer Science and Engineering, Kongu Engineering College, Perundurai, Erode, Tamil Nadu, India.

Current Medical Imaging
|April 22, 2025
PubMed
Summary
This summary is machine-generated.

Deep learning models accurately classify skin diseases using dermoscopic images. RegNetX with attention mechanisms achieved 98.61% accuracy, aiding early skin lesion diagnosis.

Keywords:
Attention mechanismBayesian optimization.CNNEfficientNetB3RegNetXResNet-152Skin lesionVGG19

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Area of Science:

  • Dermatology
  • Artificial Intelligence
  • Medical Imaging

Background:

  • Skin lesions present diagnostic challenges due to visual similarities.
  • Early identification and treatment of skin diseases are crucial to prevent severe health issues.

Purpose of the Study:

  • To develop and evaluate deep learning models for accurate skin lesion classification using dermoscopic images.
  • To enhance model performance by integrating attention mechanisms for focused feature extraction.

Main Methods:

  • Utilized four pre-trained Convolutional Neural Network (CNN) architectures: RegNetX, EfficientNetB3, VGG19, and ResNet-152.
  • Integrated channel-wise and spatial attention mechanisms into CNNs to improve focus on relevant image regions.
  • Optimized model hyperparameters using Bayesian optimization for enhanced performance.

Main Results:

  • RegNetX demonstrated superior performance, achieving an accuracy of 98.61% in classifying seven types of skin diseases.
  • The integration of attention mechanisms significantly improved the models' ability to identify critical features in dermoscopic images.
  • RegNetX with attention mechanisms showed robust performance, highlighting its effectiveness in diagnostic tasks.

Conclusions:

  • Attention-aware deep learning models effectively classify skin diseases from dermoscopic images.
  • The RegNetX model, enhanced with optimized attention mechanisms, offers accurate and robust diagnoses.
  • This technology is critical for the early detection and treatment of various skin conditions.