Active contour-based cell segmentation during freezing and its application in cryopreservation.

Area of Science:

• Biophysics
• Cell Biology
• Image Analysis

Background:

• Plasma membrane water permeability is vital for cryopreservation protocols.
• Quantifying water permeability requires automated cell volume segmentation during freezing.
• Existing segmentation methods struggle with extracellular ice and variable backgrounds.

Purpose of the Study:

• To develop an efficient and accurate method for cell segmentation during freezing.
• To address the challenges posed by extracellular ice and complex backgrounds in image processing for cryopreservation.
• To enable precise quantification of water permeability by improving cell volume measurement.

Main Methods:

• A novel two-step approach for cell segmentation from temporal image sequences.
• Step 1: Greedy search strategy to track approximate cell locations in motion.
• Step 2: Localized competitive active contour model for precise cell contour extraction, using initial contours derived from the tracking step.

Main Results:

• The proposed method effectively segments cells from extracellular ice, even when attached or surrounding.
• Demonstrated efficiency and effectiveness in segmenting cells during the freezing process.
• Successfully eased initialization challenges for active contour models through motion tracking.

Conclusions:

• The novel segmentation approach provides an efficient and effective solution for cell image analysis during cryopreservation.
• This method facilitates accurate cell volume measurement, crucial for optimizing cryopreservation protocols.
• The technique overcomes significant image processing hurdles, advancing the field of cryobiology.