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Automated mean linear intercept measurement: quantifying bias and parameter sensitivity in lung morphometry.

Atallah Madi1, Diego Politis1, Sina Salsabili1

  • 1Department of Systems and Computer Engineering, Carleton University, Ottawa, Ontario, Canada.

Physiological Measurement
|July 16, 2025
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Summary
This summary is machine-generated.

An automated system for measuring mean linear intercept (MLI) in lung morphometry reduces bias and improves efficiency. The direct method offers higher precision and is less sensitive to measurement parameters than the indirect method.

Keywords:
average chord lengthhistopathology imageslung structuremean linear intercept (MLI) measurement

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Area of Science:

  • Pulmonary and Respiratory Medicine
  • Biomedical Engineering
  • Computational Pathology

Background:

  • Mean linear intercept (MLI) is a key metric in lung morphometry.
  • Conventional indirect MLI assessment is labor-intensive, time-consuming, and prone to systematic biases.
  • Understanding biases and methodological parameter effects is crucial for accurate morphometry.

Purpose of the Study:

  • To examine systematic biases in the indirect MLI method.
  • To compare direct and indirect MLI methods and their sensitivity to parameters like field-of-view (FOV) number and guideline length.
  • To develop and validate an automated MLI measurement system.

Main Methods:

  • Developed an automated MLI measurement system utilizing a multiresolution semantic segmentation model.
  • Implemented both indirect and direct MLI measurement capabilities within the system.
  • Systematically varied the number of accepted FOV images (10-1000) and guideline length (19.4-349.5 µm).

Main Results:

  • The indirect method consistently overestimated MLI due to Septa Bias and Partial Chord Bias.
  • Increasing the number of FOV images reduced the standard error for MLI.
  • The direct method demonstrated a lower standard error and was less sensitive to guideline length compared to the indirect method.

Conclusions:

  • The automated system enhances efficiency and precision in MLI measurement.
  • The direct MLI method offers significant advantages, including lower standard error and reduced sensitivity to guideline length.
  • The accurate segmentation model facilitates advanced morphometry techniques and improved lung morphometric analysis.