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A Deep Learning Model Based on Capsule Networks for COVID Diagnostics through X-ray Images.
Gabriela Rangel1,2, Juan C Cuevas-Tello1, Mariano Rivera3
1Facultad de Ingeniería, Universidad Autonoma de San Luis Potosi, San Luis Potosi 78290, Mexico.
Diagnostics (Basel, Switzerland)
|September 9, 2023
Summary
This study introduces DRCaps, a Capsule Network model for detecting diseases like pneumonia and COVID-19 in chest X-rays. DRCaps achieves 90% accuracy, offering a simpler, more effective deep learning approach for medical imaging diagnostics.
Area of Science:
- Medical Imaging
- Artificial Intelligence
- Deep Learning
Background:
- X-ray diagnostics are crucial for detecting diseases but require expert availability.
- Current deep learning models like Convolutional Neural Networks (CNNs) have limitations in medical image analysis.
- Capsule Networks (CapsNet) offer a promising alternative to address these limitations.
Purpose of the Study:
- To develop an improved deep learning model for detecting diseases in chest X-ray images.
- To evaluate the effectiveness of Capsule Networks (CapsNet) in diagnosing conditions like pneumonia and COVID-19.
- To propose a novel model, DRCaps, that enhances CapsNet performance and efficiency.
Main Methods:
- Utilized Capsule Networks (CapsNet) for chest X-ray analysis.
- Developed an improved model named DRCaps, incorporating a dilation rate (dr) parameter.
- Managed 226 × 226 resolution images and employed a reconstruction stage to prevent overfitting.
- Avoided max-pooling operations, using stride and dilation rate for downsampling.
Main Results:
- Achieved a high accuracy of 90% on a dataset of 16,669 chest X-ray images.
- The DRCaps model has a size of 11M, demonstrating efficiency.
- DRCaps outperformed comparable models in accuracy, parameter count, and handling image sizes.
- Demonstrated the effectiveness of the reconstruction stage in preventing overfitting.
Conclusions:
- DRCaps offers a superior deep learning solution for chest X-ray disease detection compared to existing models.
- The model is effective in diagnosing conditions such as pneumonia and COVID-19.
- DRCaps provides a simplified approach, avoiding complex preprocessing and data augmentation.
