18149485. TASK-SPECIFIC IMAGE STYLE TRANSFER simplified abstract (GE Precision Healthcare LLC)
Contents
TASK-SPECIFIC IMAGE STYLE TRANSFER
Organization Name
Inventor(s)
Chandan Kumar Mallappa Aladahalli of Bengaluru (IN)
Krishna Seetharam Shriram of Bengaluru (IN)
Vikram Reddy Melapudi of Bangalore (IN)
Shital Sheshrao Yelne of Nagpur (IN)
TASK-SPECIFIC IMAGE STYLE TRANSFER - A simplified explanation of the abstract
This abstract first appeared for US patent application 18149485 titled 'TASK-SPECIFIC IMAGE STYLE TRANSFER
Simplified Explanation: The patent application describes systems and techniques for task-specific image style transfer, particularly in the context of medical images. The system can generate a new medical image with a different visual style while maintaining the anatomical content of the original image.
- The system accesses a first medical image with a specific visual style and anatomical content.
- It uses an optimization algorithm to create a second medical image with a different visual style but the same anatomical content.
- The optimization algorithm is based on feature maps extracted from a pre-trained deep learning neural network.
Key Features and Innovation:
- Task-specific image style transfer for medical images.
- Generation of a new medical image with a different visual style while preserving anatomical content.
- Optimization algorithm based on feature maps from a deep learning neural network.
Potential Applications:
- Medical imaging research and development.
- Radiology and diagnostic imaging.
- Image enhancement and customization in healthcare.
Problems Solved:
- Facilitates the customization of visual styles in medical images.
- Allows for the exploration of different visual representations of anatomical content.
Benefits:
- Improved visualization and interpretation of medical images.
- Enhanced customization and personalization of medical imaging.
- Potential for better communication of medical information to patients.
Commercial Applications: Optimizing Medical Image Style Transfer for Enhanced Diagnostic Imaging
Prior Art: Prior research in medical image processing and style transfer techniques.
Frequently Updated Research: Ongoing developments in deep learning algorithms for medical image analysis.
Questions about Medical Image Style Transfer: 1. How does this technology improve the interpretation of medical images? 2. What are the potential limitations of using deep learning algorithms for image style transfer in healthcare settings?
Original Abstract Submitted
Systems/techniques that facilitate task-specific image style transfer are provided. In various embodiments, a system can access a first medical image, wherein the first medical image can exhibit anatomical content and a first visual style. In various aspects, the system can generate, via execution of an optimization algorithm, a second medical image based on the first medical image, wherein the second medical image can exhibit the anatomical content and a second visual style that is different from the first visual style. In various instances, the optimization algorithm can be based on feature maps extracted from a pre-trained deep learning neural network that has been configured to perform an inferencing task on medical images exhibiting the second visual style.
