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Related Experiment Video

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Cereal Crop Ear Counting in Field Conditions Using Zenithal RGB Images
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A Novel Ear Impression-Taking Method Using Structured Light Imaging and Machine Learning: A Pilot Proof of Concept

Kenneth Wei De Chua1, Hazel Kai Hui Yeo1, Charmaine Kai Ling Tan2

  • 1Department of Otorhinolaryngology-Head and Neck Surgery, Allied Health, Audiology, Changi General Hospital, Singapore 529889, Singapore.

Journal of Clinical Medicine
|April 9, 2024
PubMed
Summary

A new contactless ear scanning prototype shows promise for predicting ear canal information using structured light imaging and a deep neural network, potentially automating ear impression-taking for same-day 3D printing.

Keywords:
earear canalinnovationproof of concept studythree-dimensional scanning

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Area of Science:

  • Biomedical Engineering
  • Medical Imaging
  • Artificial Intelligence

Background:

  • Traditional ear impression-taking is invasive.
  • Contactless ear scanning methods are underdeveloped.
  • A correlation between external ear features and ear canal anatomy is proposed.

Purpose of the Study:

  • Develop a prototype for contactless ear scanning.
  • Create an algorithm to predict ear canal information.
  • Establish proof of concept for automated ear impression-taking.

Main Methods:

  • Structured light imaging prototype developed.
  • Correlation analysis using existing ear impression data.
  • Deep neural network for predictive algorithm creation.
  • Comparative study with traditional ear impressions.

Main Results:

  • Prototype successfully trialed; participants reported comfort.
  • Partial ear canal matching achieved from external images.
  • Predictive algorithm demonstrated a good standard of error.
  • Proof of concept for the novel method established.

Conclusions:

  • Further research needed to enhance algorithm predictive capabilities.
  • Optimization of prototype imaging positions is required.
  • Potential for automated ear impression-taking and same-day 3D printing of earmolds.