OrganelleVision

Overview

OrganelleVision is a specialized software toolkit for automating transmission electron microscopy (TEM) workflow, specifically designed for organelle identification and analysis. This project focuses on the automated detection and analysis of cellular organelles, with particular emphasis on mitochondria and vesicles in rodent ileum tissue samples.

Features

• Automated TEM workflow processing
• Specialized organelle detection algorithms
• Annotation metric extraction automation
• High-quality dataset management
• Manual annotation verification system

Dataset Specifications

• Size: 2000+ Regions of Interest (ROIs)
• Source Tissue: Ileum samples from mice and rats
• Primary Focus:
  • Mitochondria
  • Vesicles
• Quality Assurance: Hand-supervised and verified annotations
• Validation: Expert-reviewed data

Technical Details

Data Processing Pipeline

graph TD
    A[TEM Image Acquisition] --> B[Initial Image Pre-processing]
    B --> C[Manual ROI Labeling]
    
    subgraph "Training Phase"
        D[Dataset Preparation]
        E[Model Training]
        F[Validation]
    end
    
    C --> D
    D --> E
    E --> F
    
    subgraph "Evaluation Loop"
        G[Automated Prediction]
        H{Accuracy Review}
        I[Manual Correction]
    end
    
    F --> G
    G --> H
    H -->|Acceptable| J[Final Dataset]
    H -->|Needs Improvement| I
    I -->|Wrong Labels| C
    I -->|Model Issues| E
    
    subgraph "Quality Control"
        K[Expert Verification]
        L[Annotation Standards Check]
        M[Consistency Validation]
    end
    
    J -.-> K
    K -.-> L
    L -.-> M
    M -.->|Issues Found| I
    
    subgraph "Final Processing"
        N[Metric Extraction]
        O[Data Storage]
        P[Analysis Reports]
    end
    
    J --> N
    N --> O
    O --> P

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Annotation Process

• Manual supervision of annotations
• Expert verification
• Quality control checkpoints
• Standardized validation protocols

Development Status

Currently under active development and not open source.

Ongoing Development

• Code refactoring for improved maintainability
• Implementation of object-oriented design patterns
• Modularization of components
• Enhanced inter-module communication
• Comprehensive dataset evaluation tools

Roadmap

• Complete code refactoring
• Implement class-based architecture
• Modularize core functionalities
• Develop inter-module communication protocols
• Create dataset evaluation framework

Research Applications

This toolkit has been developed in conjunction with research published in Frontiers in Physiology. The associated research demonstrates its effectiveness in analyzing cellular structures in rodent tissue samples.

Key Research Outcomes

• Automated identification of cellular organelles
• Quantitative analysis of organelle characteristics
• Standardized workflow for TEM image processing
• Validated methodology for tissue analysis

Future Development

• Enhanced automation capabilities
• Extended organelle recognition
• Integration with other microscopy platforms
• Public dataset release
• API development

Technical Requirements

(To be added when the project becomes open source)

Installation

(To be added when the project becomes open source)

Usage

(To be added when the project becomes open source)

Contributing

Currently, this project is not open for external contributions. Future updates will include contribution guidelines when the project becomes open source.

License

(To be determined)

Contact

(Add appropriate contact information)

Acknowledgments

• Research team and contributors
• Associated research institutions
• Funding sources

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Note: This documentation is a work in progress and will be updated as the project develops and moves towards open-source status.