Protein Crystallization Segmentation and Classification Using Subordinate Color Channel in Fluorescence Microscopy Images

Key points

• The accuracy of detecting protein crystals for fluorescence microscopy images is very critical for high throughput and automated systems.1
• Although the trace fluorescent labeling method could highlight protein crystals, reflection and emission from the fluorescence dye is not always due to crystal regions.1
• Hence, we have built a segmentation method based on the percentile intensity of the subordinate color for trace fluorescently labeled (TFL'd) protein crystallization trial images.1
• Our experiments show that using the subordinate channel may be more helpful for TFL'd protein trial image classification.1

Sources (1)

• [1]Protein Crystallization Segmentation and Classification Using Subordinate Color Channel in Fluorescence Microscopy Images
  arXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 11, 02:33 AM

  In this paper, we show that using the subordinate color intensity corresponding to longer wavelengths than the peak wavelength of the emission spectra could improve the accuracy of protein crystal detection.

  The accuracy of detecting protein crystals for fluorescence microscopy images is very critical for high throughput and automated systems.

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