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Updated: Feb 6, 2026
09:47
Array Tomography Workflow for the Targeted Acquisition of Volume Information using Scanning Electron Microscopy
Published on: July 15, 2021
5.4K
Automated body volume acquisitions from 3D structured-light scanning.
Chuang-Yuan Chiu1, David L Pease2, Samantha Fawkner3
1Centre for Sports Engineering Research, Sheffield Hallam University, Sheffield, UK.
Computers in Biology and Medicine
|August 21, 2018
Summary
This study developed automated software to calculate whole-body and segmental volumes from 3D scans, reducing manual processing time and expertise needed. The software demonstrated good accuracy, with errors under 5% for most measurements.
Area of Science:
- Biomedical Engineering
- Medical Imaging Analysis
- Anthropometry
Background:
- Accurate body volume measurements are crucial for health and medical assessments.
- Traditional manual post-processing of 3D scan data is labor-intensive and requires specialized skills.
Purpose of the Study:
- To develop and validate bespoke software for automated calculation of whole-body and segmental volumes from 3D scanned data.
- To assess the accuracy and reliability of the developed software compared to manual methods.
Main Methods:
- Utilized Stitched Puppet model fitting to align template models with raw 3D scan data.
- Automated identification of segmental endpoints and boundaries for volume calculation.
- Compared software-derived volumes against manually processed reference data from 29 participants.
Main Results:
- The bespoke software achieved high accuracy, with errors below 5% for whole-body and most segmental volumes.
- Demonstrated reliability through intra-method and inter-method error analysis.
- Significantly reduced the need for technical expertise in post-processing 3D scan data.
Conclusions:
- The developed bespoke software offers an accurate and reliable automated solution for body volume quantification.
- This tool simplifies the process, making body volume analysis accessible for various health and medical applications.
- Potential to streamline research and clinical workflows involving anthropometric measurements.
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