Synthetic Medical Images

Syllabus :GS 3/Science and Tech 

In News

• The rise of AI-generated synthetic medical images has been observed. 

About Synthetic medical images

• They are generated by AI or computer algorithms without being captured by traditional imaging devices such as MRI, CT scans, or X-rays. 
• These images are entirely constructed using mathematical models or AI techniques like generative adversarial networks (GANs), diffusion models, and autoencoders.
  • GANs involve a generator creating images and a discriminator assessing their authenticity, improving through competition.
  • VAEs compress images into latent spaces and reconstruct them.
  • Diffusion models transform random noise into realistic images step-by-step.

Advantages:

• It allows intra- and inter-modality translation, helping generate missing scans from available data.
  • Intramodality Translation: Generates synthetic images within the same imaging modality (e.g., reconstructing MRI scans).
  • Inter-Modality Translation: Creates synthetic images by converting data between different modalities (e.g., generating CT scans from MRI data).
• It is generated without real patient data, reducing privacy concerns and facilitating data sharing.
• It addresses the time and expense associated with collecting real medical images.

Challenges:

• Risk of creating deepfakes that could impersonate patients, leading to incorrect diagnoses and fraudulent claims.
• Synthetic images may not capture the subtle nuances of real-world medical data, risking the accuracy of AI diagnoses.
• Over-reliance on synthetic images could blur the lines between reality and fabrication, potentially leading to diagnostic models that misalign with actual patient cases.

Solutions:

• While synthetic medical images offer innovation opportunities, reliance on them poses regulatory and ethical challenges. Human oversight is crucial to maintain the integrity of healthcare decisions.
• Collaboration between clinicians and AI engineers is essential to enhance the quality of synthetic images and ensure they reflect real-world medical complexities.
• The use of synthetic images should be approached with optimism and caution to maximize benefits without undermining real-world healthcare understanding.

Source:TH