project - ai medical imaging diagnosis agent

ai_agent_tutorials/ai_medical_imaging_agent/README.md

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+# Medical Imaging Diagnosis Agent
+
+A Medical Imaging Diagnosis Agent build on phidata powered by Gemini 2.0 Flash Experimental that provides AI-assisted analysis of medical images of various scans. The agent acts as a medical imaging diagnosis expert to analyze various types of medical images and videos, providing detailed diagnostic insights and explanations.
+
+## Features
+
+- **Comprehensive Image Analysis**
+  - Image Type Identification (X-ray, MRI, CT scan, ultrasound)
+  - Anatomical Region Detection
+  - Key Findings and Observations
+  - Potential Abnormalities Detection
+  - Image Quality Assessment
+  - Research and Reference
+
+## How to Run
+
+1. **Setup Environment**
+   ```bash
+   # Clone the repository
+   git clone https://github.com/Shubhamsaboo/awesome-llm-apps.git
+   cd ai_agent_tutorials/ai_medical_imaging_agent
+
+   # Install dependencies
+   pip install -r requirements.txt
+   ```
+
+2. **Configure API Keys**
+   - Get Google API key from [Google AI Studio](https://aistudio.google.com)
+
+3. **Run the Application**
+   ```bash
+   streamlit run ai_medical_imaging.py
+   ```
+
+## Analysis Components
+
+- **Image Type and Region**
+  - Identifies imaging modality
+  - Specifies anatomical region
+
+- **Key Findings**
+  - Systematic listing of observations
+  - Detailed appearance descriptions
+  - Abnormality highlighting
+
+- **Diagnostic Assessment**
+  - Potential diagnoses ranking
+  - Differential diagnoses
+  - Severity assessment
+
+- **Patient-Friendly Explanations**
+  - Simplified terminology
+  - Detailed first-principles explanations
+  - Visual reference points
+
+## Notes
+
+- Uses Gemini 2.0 Flash for analysis
+- Requires stable internet connection
+- API usage costs apply
+- For educational and development purposes only
+- Not a replacement for professional medical diagnosis
+
+## Disclaimer
+
+This tool is for educational and informational purposes only. All analyses should be reviewed by qualified healthcare professionals. Do not make medical decisions based solely on this analysis.

ai_agent_tutorials/ai_medical_imaging_agent/ai_medical_imaging.py

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+import os
+from PIL import Image
+from phi.agent import Agent
+from phi.model.google import Gemini
+import streamlit as st
+from phi.tools.duckduckgo import DuckDuckGo
+
+if "GOOGLE_API_KEY" not in st.session_state:
+    st.session_state.GOOGLE_API_KEY = None
+
+with st.sidebar:
+    st.title("ℹ️ Configuration")
+
+    if not st.session_state.GOOGLE_API_KEY:
+        api_key = st.text_input(
+            "Enter your Google API Key:",
+            type="password"
+        )
+        st.caption(
+            "Get your API key from [Google AI Studio]"
+            "(https://aistudio.google.com/apikey) 🔑"
+        )
+        if api_key:
+            st.session_state.GOOGLE_API_KEY = api_key
+            st.success("API Key saved!")
+            st.rerun()
+    else:
+        st.success("API Key is configured")
+        if st.button("🔄 Reset API Key"):
+            st.session_state.GOOGLE_API_KEY = None
+            st.rerun()
+
+    st.info(
+        "This tool provides AI-powered analysis of medical imaging data using "
+        "advanced computer vision and radiological expertise."
+    )
+    st.warning(
+        "⚠DISCLAIMER: This tool is for educational and informational purposes only. "
+        "All analyses should be reviewed by qualified healthcare professionals. "
+        "Do not make medical decisions based solely on this analysis."
+    )
+
+medical_agent = Agent(
+    model=Gemini(
+        api_key=st.session_state.GOOGLE_API_KEY,
+        id="gemini-2.0-flash-exp"
+    ),
+    tools=[DuckDuckGo()],
+    markdown=True
+) if st.session_state.GOOGLE_API_KEY else None
+
+if not medical_agent:
+    st.warning("Please configure your API key in the sidebar to continue")
+
+# Medical Analysis Query
+query = """
+You are a highly skilled medical imaging expert with extensive knowledge in radiology and diagnostic imaging. Analyze the patient's medical image and structure your response as follows:
+
+### 1. Image Type & Region
+- Specify imaging modality (X-ray/MRI/CT/Ultrasound/etc.)
+- Identify the patient's anatomical region and positioning
+- Comment on image quality and technical adequacy
+
+### 2. Key Findings
+- List primary observations systematically
+- Note any abnormalities in the patient's imaging with precise descriptions
+- Include measurements and densities where relevant
+- Describe location, size, shape, and characteristics
+- Rate severity: Normal/Mild/Moderate/Severe
+
+### 3. Diagnostic Assessment
+- Provide primary diagnosis with confidence level
+- List differential diagnoses in order of likelihood
+- Support each diagnosis with observed evidence from the patient's imaging
+- Note any critical or urgent findings
+
+### 4. Patient-Friendly Explanation
+- Explain the findings in simple, clear language that the patient can understand
+- Avoid medical jargon or provide clear definitions
+- Include visual analogies if helpful
+- Address common patient concerns related to these findings
+
+### 5. Research Context
+IMPORTANT: Use the DuckDuckGo search tool to:
+- Find recent medical literature about similar cases
+- Search for standard treatment protocols
+- Provide a list of relevant medical links of them too
+- Research any relevant technological advances
+- Include 2-3 key references to support your analysis
+
+Format your response using clear markdown headers and bullet points. Be concise yet thorough.
+"""
+
+st.title("🏥 Medical Imaging Diagnosis Agent")
+st.write("Upload a medical image for professional analysis")
+
+# Create containers for better organization
+upload_container = st.container()
+image_container = st.container()
+analysis_container = st.container()
+
+with upload_container:
+    uploaded_file = st.file_uploader(
+        "Upload Medical Image",
+        type=["jpg", "jpeg", "png", "dicom"],
+        help="Supported formats: JPG, JPEG, PNG, DICOM"
+    )
+
+if uploaded_file is not None:
+    with image_container:
+        # Center the image using columns
+        col1, col2, col3 = st.columns([1, 2, 1])
+        with col2:
+            image = Image.open(uploaded_file)
+            # Calculate aspect ratio for resizing
+            width, height = image.size
+            aspect_ratio = width / height
+            new_width = 500
+            new_height = int(new_width / aspect_ratio)
+            resized_image = image.resize((new_width, new_height))
+
+            st.image(
+                resized_image,
+                caption="Uploaded Medical Image",
+                use_container_width=True
+            )
+
+            analyze_button = st.button(
+                "🔍 Analyze Image",
+                type="primary",
+                use_container_width=True
+            )
+
+    with analysis_container:
+        if analyze_button:
+            image_path = "temp_medical_image.png"
+            with open(image_path, "wb") as f:
+                f.write(uploaded_file.getbuffer())
+
+            with st.spinner("🔄 Analyzing image... Please wait."):
+                try:
+                    response = medical_agent.run(query, images=[image_path])
+                    st.markdown("### 📋 Analysis Results")
+                    st.markdown("---")
+                    st.markdown(response.content)
+                    st.markdown("---")
+                    st.caption(
+                        "Note: This analysis is generated by AI and should be reviewed by "
+                        "a qualified healthcare professional."
+                    )
+                except Exception as e:
+                    st.error(f"Analysis error: {e}")
+                finally:
+                    if os.path.exists(image_path):
+                        os.remove(image_path)
+else:
+    st.info("👆 Please upload a medical image to begin analysis")

ai_agent_tutorials/ai_medical_imaging_agent/requirements.txt

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+streamlit==1.40.2
+phidata==2.7.3
+Pillow==10.0.0
+duckduckgo-search==6.4.1
+google-generativeai==0.8.3