MRI Swarm

MRI Swarm is an enterprise-grade system built with Swarms, the leading production-ready multi-agent framework. It coordinates a team of specialized medical imaging agents to analyze MRI scans, with each agent focusing on different aspects of interpretation to provide detailed and accurate analysis. Using Swarms' proven infrastructure, MRI Swarm delivers blazingly fast and hyper-accurate medical imaging analysis.

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

pip3 install -U mri-swarm

Quick Start Guide

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

# 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

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

Loading

API File

Learn how to setup an API for MRI Swarm

Docker Setup

Learn how to run MRI Swarm using Docker

Connect With Us

Join the swarms community of agent engineers and researchers for technical support, cutting-edge updates, and exclusive access to world-class agent engineering insights!

Platform	Description	Link
📚 Documentation	Official documentation and guides	docs.swarms.world
📝 Blog	Latest updates and technical articles	Medium
💬 Discord	Live chat and community support	Join Discord
🐦 Twitter	Latest news and announcements	@kyegomez
👥 LinkedIn	Professional network and updates	The Swarm Corporation
📺 YouTube	Tutorials and demos	Swarms Channel
🎫 Events	Join our community events	Sign up here
🚀 Onboarding Session	Get onboarded with Kye Gomez, creator and lead maintainer of Swarms	Book Session

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Citation

If you use MRI Swarm in your research, please cite the projext with

@misc{SWARMS_2022,
  author  = {The Swarms Corporationn},
  title   = {{MRI Swarm: Fast, Scalable, and Accurate MRI Analysis with Multi-Agent Collaboration}},
  year    = {2022},
  howpublished = {\url{https://github.com/The-Swarm-Corporation/MRI-Swarm}},
  version = {latest}
}

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.