[feat] Blinking Classification

[Alejandro1400]

Implementation of Blinking Classification for STORM Imaging

Objective

To enhance our STORM Image Processing GUI with a Blinking Classification feature that categorizes localized molecules based on their blinking behavior across microscopy frames, as detailed in Binkley & Griffin (2021).

Requirements

• Classification Categories: Molecules must be classified into specific categories based on their blinking behavior:

  • Always On: Molecules that remain on throughout the observation period.
  • Blinks On Once: Molecules that turn on once and remain on.
  • Blinks Off Once: Molecules that turn off once during the observation period.
  • Photobleaching: Molecules that turn off permanently after an initial period.
  • Inverse Photobleaching: Molecules initially off, then turn on permanently.
  • Blinks Off: Molecules that blink off multiple times.
  • Blinks On: Molecules that blink on multiple times.
  • Uncharacterized: Molecules with irregular or unclassifiable blinking patterns.

• Interactive GUI Elements: The interface should provide:

  • A summary view showing the number of molecules in each category.
  • Options for users to delve deeper into the results of a specific category for further analysis.
  • Visual representations (e.g., temporal plots) behind each statistic to illustrate the typical blinking behavior of molecules in that category.

Goals

• Develop Blinking Pattern Analysis Tools: Implement algorithms to analyze and classify blinking patterns of molecules.
• GUI Enhancements: Update the GUI to display blinking classification results and interactive elements for detailed analysis.
• Performance Optimization: Ensure the classification process is optimized for handling large datasets typically used in STORM imaging.

Challenges

• Algorithm Complexity: Creating efficient algorithms capable of accurately classifying the blinking behaviors across potentially noisy and complex datasets.
• User Interface Clarity: Designing a clear and intuitive interface that allows users to easily navigate and interpret complex blinking data.

Milestones

1. Algorithm Design and Development: Research and develop algorithms for blinking classification.
2. Interface Design: Sketch and design the new interface elements that will accommodate the new classification features.
3. Implementation: Integrate the algorithms with the GUI, ensuring smooth functionality and data handling.
4. Testing and Validation: Rigorously test the feature with various datasets to validate accuracy and usability.
5. Deployment and Documentation: Finalize documentation and prepare the feature for deployment.

Expected Outcomes

• A robust Blinking Classification feature integrated into the existing STORM GUI that aids researchers in better understanding and analyzing the behavior of molecules in their experiments.
• Enhanced analytical capabilities within the GUI that allow for deeper insights into the data generated by STORM techniques.

Visuals and Mockups