mri-swarm 0.1.0
MRI-Swarm - TGSC
License: MIT
Requires Python: <4.0,>=3.10
Keywords: artificial intelligence, deep learning, optimizers, Prompt Engineering, swarms, agents, llms, transformers, multi-agent, swarms of agents, Enterprise-Grade Agents, Production-Grade Agents, Agents, Multi-Grade-Agents, Swarms, Transformers, LLMs, Prompt Engineering, Agents, Generative Agents, Generative AI, Agent Marketplace, Agent Store, quant, finance, algorithmic trading, portfolio optimization, risk management, financial modeling, machine learning for finance, natural language processing for finance, mri, medical imaging, medical diagnosis, medical imaging analysis, medical imaging diagnosis, medical imaging analysis

# MRI Swarm

MRI Swarm is an enterprise-grade collaborative system designed for comprehensive MRI scan analysis. It leverages a distributed network of specialized medical imaging agents, each focusing on different aspects of MRI interpretation, to provide detailed and accurate analysis of medical imaging data.

## Features

- **Multi-Agent Distributed Analysis**: Six specialized medical imaging agents working in coordination
- **Comprehensive Diagnostic Analysis**: From detailed anatomical structure to clinical correlation
- **Advanced Quality Assurance**: Integrated quality assessment and artifact detection protocols
- **Automated Clinical Reporting**: Generates detailed medical summaries with diagnostic insights
- **Flexible Input Processing**: Supports single and multiple MRI sequence analysis

## Installation

```bash
pip install -r requirements.txt
```

## Quick Start Guide

```python
from mri_swarm import mri_swarm

# Analyze a single MRI scan
result = mri_swarm(
    task="Analyze this brain MRI for signs of multiple sclerosis",
    img="path/to/brain_mri.jpg"
)
print(result)

# Analyze multiple MRI scans
results = mri_swarm(
    task="Compare these brain MRIs for progression of tumor",
    imgs=["scan1.jpg", "scan2.jpg"]
)
print(results)
```

## Agent Architecture

The system comprises six specialized medical imaging agents and one synthesis agent:

1. **Anatomical Analysis Agent**
   - Precise anatomical structure identification
   - Advanced brain region mapping and segmentation
   - Multi-tissue classification system

2. **Pathology Detection Agent**
   - Advanced tumor detection and classification
   - Comprehensive lesion identification
   - Disease marker evaluation protocol

3. **Sequence Analysis Agent**
   - T1/T2 weighted image interpretation
   - FLAIR sequence analysis
   - Diffusion-weighted imaging interpretation

4. **Quantitative Analysis Agent**
   - High-precision volumetric measurements
   - Signal intensity quantification
   - Advanced statistical analysis

5. **Clinical Correlation Agent**
   - Systematic symptom correlation
   - Treatment response assessment
   - Evidence-based outcome prediction

6. **Quality Control Agent**
   - Comprehensive image quality assessment
   - Systematic artifact detection
   - Protocol compliance verification

7. **Synthesis Agent**
   - Integration of diagnostic findings
   - Generation of comprehensive medical reports
   - Evidence-based diagnostic recommendations

## System Operation

1. User submits an MRI analysis task with imaging data
2. System initiates a coordinated analysis protocol
3. Specialized agents perform targeted analysis
4. Agents exchange diagnostic insights
5. Synthesis agent integrates findings
6. System generates comprehensive diagnostic report

## Implementation Examples

```python
# Case 1: Tumor Analysis
result = mri_swarm(
    task="Analyze this brain MRI for presence and characteristics of any tumors",
    img="tumor_case.jpg"
)

# Case 2: Multiple Sclerosis Assessment
result = mri_swarm(
    task="Evaluate these MRI sequences for MS lesions and disease progression",
    imgs=["ms_baseline.jpg", "ms_followup.jpg"]
)

# Case 3: Quality Assessment
result = mri_swarm(
    task="Assess the quality of this MRI scan and identify any artifacts",
    img="scan_quality_check.jpg"
)
```

## System Architecture Diagram

```mermaid
sequenceDiagram
    participant U as User
    participant S as MRI Swarm System
    participant C as Coordination Layer
    participant AA as Anatomical Analysis
    participant PA as Pathology Detection
    participant SA as Sequence Analysis
    participant QA as Quantitative Analysis
    participant CA as Clinical Correlation
    participant QC as Quality Control
    participant SYN as Synthesis Engine

    U->>S: Submit MRI Analysis Request
    S->>C: Initialize Analysis Protocol
    par Parallel Analysis
        C->>AA: Execute Anatomical Analysis
        C->>PA: Execute Pathology Detection
        C->>SA: Execute Sequence Analysis
        C->>QA: Execute Quantitative Analysis
        C->>CA: Execute Clinical Correlation
        C->>QC: Execute Quality Assessment
    end
    AA-->>C: Anatomical Analysis Results
    PA-->>C: Pathological Findings
    SA-->>C: Sequence Analysis Data
    QA-->>C: Quantitative Metrics
    CA-->>C: Clinical Correlations
    QC-->>C: Quality Assessment Report
    C->>SYN: Aggregate Analysis Data
    SYN->>S: Generate Comprehensive Report
    S->>U: Return Diagnostic Analysis
```


## API File

[Learn how to setup an API for MRI Swarm](./docs/api.md)

## Docker Setup

[Learn how to run MRI Swarm using Docker](./docs/docker.md)

## Contributing

We welcome contributions from the medical imaging and software development community. Please submit pull requests following our contribution guidelines.

## Todo

- [ ] Implement the ability to create detailed documents on the patient like a real-life MRI scan
- [ ] Implement unit tests for the main file
- [ ] Implement unit tests for the api

## License

This project is licensed under the terms specified in the LICENSE file included in the repository.