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Mass Conservation and Flow Rate Measurements13:35

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Conservation of Mass in Finite Cotrol Volume01:16

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Stormwater detention basins are essential in managing runoff during heavy rainfall, particularly in urban areas where impervious surfaces increase the risk of flooding. Understanding the conservation of mass in these systems allows engineers to optimize basin performance, balancing inflow, outflow, and water storage.
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Related Experiment Video

Updated: Jan 19, 2026

Control Volume Analysis for Mass Conservation and Calibration of a Flow Passage
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Robust HU-based CT ventilation from an integrated mass conservation formulation.

Edward Castillo1,2, Yevgeniy Vinogradskiy3, Richard Castillo4

  • 1Department of Radiation Oncology, Beaumont Health Systems, Royal Oak, MI, USA.

Medical Physics
|September 13, 2019
PubMed
Summary
This summary is machine-generated.

A new mass-conserving volume change (MCVC) method improves computed tomography (CT) ventilation imaging. MCVC offers more reproducible ventilation estimates than standard Hounsfield Unit (HU) methods, reducing reliance on complex preprocessing steps.

Keywords:
4DCTcomputed tomographydeformable image registrationventilation

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Area of Science:

  • Medical imaging
  • Radiology
  • Pulmonary function testing

Background:

  • Computed tomography (CT) ventilation algorithms estimate lung volume changes during respiration.
  • Existing Hounsfield Unit (HU) methods approximate volume changes using HU variations, assuming air content changes solely drive volume changes.
  • These methods require deformable image registration, lung segmentation, vessel segmentation, and smoothing.

Purpose of the Study:

  • Introduce the novel mass-conserving volume change (MCVC) method for estimating voxel volume changes from CT image pairs.
  • MCVC provides subregional volume change estimates with controllable uncertainty, enhancing robustness to registration variations.
  • Eliminate the need for lung vessel segmentation and Gaussian smoothing inherent in traditional HU methods.

Main Methods:

  • MCVC defines subregional volume change estimates using mean density ratios.
  • Uncertainty is quantified using Gaussian statistics and standard error analysis.
  • A constrained linear least squares problem is solved for numerical implementation.
  • Reproducibility was assessed using 4DCT datasets and compared against the Integrated Jacobian Formulation (IJF) method.

Main Results:

  • MCVC ventilation images demonstrated perfect reproducibility (Pearson correlation of 1.00) across different registration solutions.
  • Standard HU ventilation (HUV) showed lower reproducibility (Pearson correlation of 0.94).
  • MCVC results showed higher correlation with the IJF method (0.81) compared to HUV (0.56).

Conclusions:

  • MCVC offers a more reproducible alternative to standard HU ventilation methods.
  • The subregional approach inherently removes the need for Gaussian smoothing and vessel segmentation.
  • MCVC's robustness and consistency suggest improved accuracy in CT-based ventilation imaging.