AI Image and Video Creation

Introduction: Why Visual AI Matters in Healthcare

In our previous modules, we explored how large language models process text, the importance of effective prompting, and how clinical decision support tools augment your practice. Now we turn to something that might feel more surprising: the ability to create images and videos from simple text descriptions.

You might reasonably ask, "Why would a physician need to generate images?" The answer spans more territory than you might expect:

• Patient education materials explaining conditions and procedures
• Practice marketing assets—logos, social media graphics, presentation visuals
• Educational content for learners
• Conceptual illustrations for research presentations
• Visual aids during patient conversations

The technology has matured remarkably over the past year. What once produced uncanny, obviously artificial images now generates visuals that can be genuinely useful—sometimes indistinguishable from professional photography or illustration. And video generation, which seemed like science fiction just two years ago, now produces clips that can convey motion, demonstrate concepts, and tell visual stories.

This module covers the leading tools available today, how to use them effectively, and—critically—the limitations and ethical considerations that should guide your use. We'll focus on practical applications relevant to clinical practice and medical education, with hands-on prompt examples you can try immediately.

Building on What We've Learned

Before diving into visual AI, let's connect this to the concepts we've established throughout this course.

The Prompting Principles Still Apply

Remember our analogy between AI prompting and taking a patient history? The same principles transfer directly to visual generation. A vague prompt yields vague results. Specificity and context matter enormously.

Consider the parallel:

The specificity you bring to a prompt directly shapes the quality and usefulness of the output.

Models Are Not Artists—They're Pattern Synthesizers

Just as language models don't "understand" in the human sense, image generators don't "see" or "imagine." They've learned statistical patterns from vast image-text datasets. When you describe something, the model generates pixels that match the patterns associated with your description.

This has practical implications. The models excel at generating images that resemble their training data. They struggle with novel combinations, unusual perspectives, or highly specific technical accuracy. A request for a "cross-section of the brachial plexus" will produce something anatomically plausible but potentially inaccurate in details—much like how a language model might generate confident-sounding but subtly wrong medical information.

Verification Remains Essential

The Current Landscape: Major Tools and Their Capabilities

The AI image and video generation space has evolved rapidly. Let's survey the major tools available today, organized by their primary modality.

Image Generation Tools

Google Nano Banana (via Gemini)

Google's Nano Banana—the image generation model powering Gemini—has become the gold standard for AI image creation, particularly for healthcare applications. It went viral in August 2025 when users discovered it could transform selfies into 3D figurines, but its real power is in professional applications: creating patient education materials, infographics, and labeled diagrams with accurate, legible text.

Example: This Module as a Whiteboard Summary

The image below was generated by Nano Banana Pro using a single prompt containing the contents of this web page. It demonstrates the model's ability to render complex text accurately, organize information visually, and produce educational materials ready for use.

ChatGPT's GPT-4o Image Generation

OpenAI's image generation is now natively integrated into GPT-4o, making it available directly in ChatGPT. This replaced DALL-E 3 as the default in March 2025.

Video Generation Tools

Google Veo 3.1

Veo 3.1, released October 2025, transformed AI video from an impressive tech demo into a production-ready tool. It generates videos with native audio—from natural conversations to synchronized sound effects—directly from text prompts.

OpenAI Sora 2

OpenAI describes Sora 2 as "the GPT-3.5 moment for video"—a major capability jump that makes physically accurate video generation accessible. Released October 2025, it focuses on realistic motion and physics simulation.

Canva: The Accessible Middle Ground

For healthcare professionals who need practical visual design without becoming AI experts, Canva deserves special attention. While Midjourney, ChatGPT, and Veo are primarily AI generation tools, Canva is a comprehensive design platform that has integrated AI features thoughtfully—making it ideal for everyday practice needs.

Magic Studio: Canva's AI Suite

Canva's "Magic Studio" bundles multiple AI capabilities into their familiar drag-and-drop interface:

Why Canva Works for Healthcare

The advantage of Canva over pure AI generation tools is integration with practical workflow. You're not just generating images—you're creating finished materials. Need a vaccination reminder postcard? A waiting room poster about preventive screenings? An Instagram post announcing flu shot availability? Canva provides templates specifically designed for these use cases, and AI features enhance rather than replace this template-based approach.

Practical Applications for Healthcare

Let's move from tool descriptions to practical applications. Here are specific use cases where visual AI can enhance your practice, with example prompts you can adapt.

Patient Education Materials

Creating clear visual explanations of conditions, procedures, and treatments is perhaps the highest-value application for clinical practice.

Practice Branding and Logos

Creating a professional visual identity for your practice used to require expensive design agencies. AI tools can generate solid starting points.

Social Media and Marketing Content

Presentation Visuals

Medical Education Content

Prompting Strategies for Visual AI

Drawing on our prompting module, here are specific strategies optimized for image and video generation.

The Anatomy of an Effective Image Prompt

Effective prompts typically include several elements:

Style Keywords That Work

Certain keywords reliably influence output style:

• "Medical illustration style" or "medical textbook quality" — Clean, educational aesthetic
• "Photorealistic" — Aims for photography-like output
• "Infographic style" — Data visualization, clean graphics
• "Vector illustration" — Clean lines, scalable, logo-appropriate
• "Warm and friendly" — Patient-facing, approachable
• "Professional" or "clinical" — Appropriate for healthcare context
• "Clean white background" — Useful for materials you'll composite later

Iteration and Refinement

Rarely will your first generation be exactly what you need. Build in time for iteration:

1. Start broad, then narrow: Your first prompt establishes the general direction. Subsequent prompts refine.
2. Identify what's working: When you get a result, note which elements you like before requesting changes.
3. Be specific about changes: "Make the background lighter" is better than "I don't like the background."
4. Use built-in editing: Most tools now allow selective editing—often faster than regenerating entirely.

Video-Specific Prompting

Video prompts need additional considerations:

• Describe motion explicitly: "Camera slowly pans left," "subject walks toward camera," "gentle zoom in."
• Specify pacing: "Slow, contemplative motion" vs. "quick, dynamic movement."
• Consider audio: If using Veo or Sora with audio, describe the soundscape: "ambient office sounds," "no dialogue, just environmental audio."
• Keep it simple: Current video AI handles single continuous actions better than complex multi-step sequences.

Limitations and Critical Considerations

What These Tools Cannot Reliably Do

Being clear about limitations helps you use these tools appropriately:

• Anatomical accuracy: AI-generated anatomical images may contain errors. Never use them as clinical references or for diagnostic education without expert review.
• Consistent characters: Maintaining the exact same person across multiple images remains challenging. Reference image features help but don't guarantee consistency.
• Complex text: While newer models have improved dramatically, long passages of text still risk errors. Always verify any text in generated images.
• Specific real people: Most tools restrict generation of identifiable real individuals. This is a safety feature, not a bug.
• Complex hands and poses: Though improved, hands remain a weak point. Check carefully when hands are prominent.
• Video complexity: Video AI currently handles simple scenes well but struggles with complex multi-person interactions or rapid action sequences.

Ethical Considerations

Transparency about AI origin: Patients and colleagues should know when images are AI-generated, particularly for educational or clinical materials. All major tools now add invisible watermarks, but visible disclosure is also appropriate.

Copyright and commercial use: AI-generated images raise unresolved copyright questions. Most tools grant commercial use rights for images you generate through their platforms. However, the underlying legal framework remains unsettled—multiple lawsuits are ongoing. For high-stakes commercial use, consider consulting with legal counsel.

Deepfakes and misuse: These same tools that create useful content can generate misinformation. As a healthcare professional, you have particular credibility—be thoughtful about how AI-generated content from your practice could be misused if shared out of context.

Getting Started: Your First Projects

The best way to learn these tools is to use them. Here are concrete starting projects appropriate for different experience levels.

Beginner: Practice Logo Concept

Goal: Generate 3-5 logo concepts for a hypothetical (or your real) practice.

Tool: ChatGPT (free), Gemini, or Midjourney

Steps:

1. Write down 3 words that describe the feeling you want your practice to convey (e.g., "warm," "professional," "modern")
2. Identify any visual elements relevant to your specialty or location
3. Choose 2-3 colors that feel appropriate
4. Generate initial concepts using a prompt incorporating these elements
5. Iterate on the most promising result with refinement prompts

Intermediate: Patient Education Handout

Goal: Create a one-page patient education handout on a common condition including AI-generated illustrations.

Tools: Image generator of choice + Canva for layout

Steps:

1. Choose a condition you frequently explain to patients
2. Outline 3-4 key points patients need to understand
3. Identify 1-2 concepts that would benefit from visual explanation
4. Generate illustrations for those concepts
5. Use Canva to combine text and images into a polished handout
6. Have a colleague review for clarity and accuracy

Advanced: Short Educational Video

Goal: Create a 15-30 second educational video demonstrating a patient self-care technique.

Tools: Veo or Sora

Steps:

1. Choose a simple technique (e.g., nasal saline irrigation, proper splint application, wound care)
2. Break the technique into 3-4 distinct steps
3. Generate a short clip for each step
4. Use a video editor (or Canva) to combine clips and add text overlays
5. Review for accuracy—AI may generate incorrect technique

Choosing the Right Tool

With multiple capable options, here's practical guidance on tool selection:

Resources for Further Learning

Official Documentation

YouTube Channels & Video Tutorials

Research & Healthcare Applications

Communities and Prompt Libraries

Key Takeaways