P-RAJIV/cxr_stable_diffusion_v1_5

🩻 CXR Stable Diffusion v1.5

📌 Overview

This model is a fine-tuned version of Stable Diffusion v1.5 trained to generate synthetic chest X-ray (CXR) images.

It is designed to produce medically relevant radiographs based on textual prompts such as disease conditions.

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🚀 Usage

import torch
from diffusers import StableDiffusionPipeline

pipe = StableDiffusionPipeline.from_pretrained(
    "P-RAJIV/cxr_stable_diffusion_v1_5",
    torch_dtype=torch.float16
).to("cuda")

prompt = "Chest X-ray showing pneumonia"

image = pipe(prompt).images[0]
image.save("output.png")

🧪 Example Prompts
"Normal chest X-ray"
"Chest X-ray showing cardiomegaly"
"Lung opacity in right lower lobe"
"Severe pneumonia chest radiograph"

⚠️ Limitations
Generated images are synthetic and not for clinical use
May produce anatomically inconsistent outputs
Performance depends heavily on prompt quality

📚 Training Details
Base Model: Stable Diffusion v1.5
Domain: Chest X-ray imaging
Fine-tuning: Text-to-image diffusion training

🧠 Intended Use
Research in medical imaging
Data augmentation
Diffusion model experimentation

❗ Disclaimer
This model is not intended for medical diagnosis or clinical decision-making.