Context:
The rise of AI-generated synthetic medical images can provide an ethical, scalable, and cost-effective solution to the medical field.
Relevance:
GS III: Science and Technology
Dimensions of the Article:
- Synthetic Medical Image
- Benefits
Synthetic Medical Image:
- These images are generated using AI or computer algorithms and are not captured by traditional imaging methods such as MRI, CT scans, or X-rays.
- They are entirely constructed using mathematical models or AI techniques like generative adversarial networks (GANs), diffusion models, and autoencoders.
- In the medical field, synthetic medical images are similarly created, where AI produces new medical scans or radiological images that resemble real ones, but they are not based on actual patient data.
How are these images produced?
- A variational autoencoder (VAE) compresses an image into a simpler form called the latent space and then tries to recreate the original image from that compressed version. The process continuously improves by reducing the difference between the real and recreated image.
- GANs involve two parts: a generator that creates synthetic images from random data and a discriminator that checks whether the image is real or artificial. Both improve through competition—the generator makes more realistic images, and the discriminator gets better at detecting fakes.
- Diffusion models begin with random noise and progressively transform it into a realistic image, using a step-by-step process that refines the noise into something resembling the images it was trained on.
Benefits:
- Intramodality translation: Refers to the process of producing synthetic images within the same imaging modality, such as improving or reconstructing MRI scans from other MRI scan data.
- Intermodality translation: Refers to the process of producing synthetic images by converting one imaging modality to another like synthesis of CT scans from MRI scans.
- As these images do not involve any patient data, they mitigate privacy issues, allowing for healthy interaction of researchers and healthcare practitioners in the development of AI without the fear of breaching patient privacy.
- Including synthetic medical images also helps in cutting down both the time and cost required to obtain actual medical data.
-Source: The Hindu
