Image analysis on corneal opacity: a novel method to estimate postmortem interval in rabbits

Area of Science:

• Forensic Science
• Ophthalmology
• Image Analysis

Background:

• Corneal opacity is a key indicator for estimating postmortem interval (PMI).
• Current methods for assessing corneal opacity can be subjective.
• Objective and quantitative methods are needed for accurate PMI estimation.

Purpose of the Study:

• To develop and validate a new image processing method for quantifying corneal opacity.
• To establish the relationship between corneal opacity changes and PMI.
• To assess the reliability of image-based features for PMI estimation.

Main Methods:

• Corneal regions were extracted from rabbit eye images.
• Color-based and texture-based features were extracted to represent corneal changes.
• A K-Nearest Neighbors (KNN) classifier was employed to correlate features with PMI.

Main Results:

• The image analysis method successfully captured changes in corneal opacity.
• Extracted image features showed a significant association with PMI.
• The KNN classifier demonstrated the effectiveness of the proposed method.

Conclusions:

• The novel image analysis technique provides a reliable and effective approach for estimating postmortem interval.
• Quantifying corneal opacity through image features offers an objective alternative for forensic analysis.
• This method has the potential to improve the accuracy of postmortem interval determination.